Altiscale

Altiscale INTRODUCTIONMartin: Hi. Today we are in Palo Alto in the Altiscale office. Hi, Raymie. Who are you and what do you do?Raymie: Hi. Yes, I’m Raymie Stata, the Founder and Chief Executive Officer of Altiscale. We do big data in the cloud using both Hadoop and Spark.Martin: What did you do before you started this company? And how did you come up with the idea for Altiscale?Raymie: Well, in many ways, the roots of Altiscale go all the way back to AltaVista. If you remember that search engine from the 1990’s. I was lucky enough to have a chance to work on that. I actually got out of college thinking that I would work in a research lab, and that research lab was at Digital Equipment Corporation where they created the AltaVista web search engine. So while I was there, I think pretty much everybody in that laboratory got pulled into the world of web search, and I was no exception. So I spent quite a few years working on AltaVista, getting experience in web search.And then after the dot co m crash in the early 2000’s, I actually started my first company which was Desktop Search Company, and we ran that for about four years and started to get some traction. Around 2004, that company was acquired by Yahoo. And about that time, actually slightly earlier, Yahoo had acquired a bunch of companies. They acquired Overture, and Overture, ironically enough, had just acquired AltaVista. So Yahoo had bought in all the old tech that I used to work with through Overture. They also bought the web search assets of FAST, which is a European search engine company, and a few other assets. So they were building up a search technology to go compete head to head with Google. And a little after those major acquisitions, they decided they wanted to have some Desktop Search as well, so they acquired my company.So that was 2004, and in the history of Hadoop, that was a significant year. That was the year that the MapReduce paper was published from Google. And for people in the search world, that was a really fascinating paper. I think for us, the basic technique that they were using, which was a cluster-wide search, was something that pretty much everybody in the search world had developed in a way. But the MapReduce paper took that basic technique and put it in a very elegant package where the mechanism of the MapReduce paradigm was very clearly separated from the application code. And so one could very easily develop and improve the framework code, the heart of the distributed system part, if you will, and pan it of the application code. And that very clean separation, I think, was missing in most of the search world.So it got our attention for sure at Yahoo and I think in other search companies at the time. But what was fascinating about that paper as well is it got the attention of, I think, a broader universe. At that time, Google was certainly in ascendance. People were beginning to think, “There’s some magic over there. They must know something we don’t kn ow.” And so that paper, I think, was seen as an insider’s look into the magic of Google. And so there was a lot of very broad fascination with that paper. So interestingly, other search engines, they were at that time a little bit more competitive in the world of search, so there were other search engines. I think other companies were interested in doing better than Google, so they all embarked on these very ambitious internal projects to do something better than Google.But there were a few of us at Yahoo who said, “Instead of trying to out-engineer Google, maybe what we can do is demystify this a little bit by basically taking that concept and implementing it in open source.” And I had known Doug Cutting prior to getting to Yahoo. We built some work with the Internet archive, and I got to know his work with the Nutch Foundation at the time. He had his own foundation. And so I was able to get Doug to come work at Yahoo first as a contractor and then ultimately as employee, a nd we decided, “Yes, we’re going to do the open source MapReduce.” And that complemented well work that was already in place in the Nutch search engine where they had also implemented this thing called the Google File System.So that was how Yahoo got involved with Hadoop. I think Yahoo over the years made massive investments in Hadoop that really made it the enterprise strength software that it is today. So I was actually just at the very beginning of my tenure at Yahoo that I was getting a project on the way. Through the years at Yahoo, I had a number of positions. So I started in the algorithmic web search team where I was the chief architect of that team. And then over the years, I was the chief architect of the search and advertising team, and then the chief architect of all of Yahoo, and ultimately became the CTO of Yahoo. And as I got broader and broader responsibilities at Yahoo, I helped drag Hadoop along with me to be used in broader and broader use cases across Yahoo . And as a result, by the time I left Yahoo, we had a very large central installation for Hadoop. We had 40,000 nodes of Hadoop over a thousand users being used for a very wide variety of use cases.When I started thinking about leaving Yahoo, since I had a lot of experience with Hadoop inside of Yahoo, I took a look to see, “Hey, what’s it like to use Hadoop outside of a company?” And not just Yahoo. I knew how folkswere using it at Facebook. Twitter wasn’t so big at the time, but eBay. And it was the same model, a large central cluster run by a very competent professional team. Outside of those larger Internet companies, what I saw was something very different, which was these small clusters, 20 nodes. Very often they were being supported, if at all, by an operations team. It was like a discretionary effort. They weren’t really full time. Usually there were other production activities that had more of a priority. So the users of these clusters were often stuck dealing wit h problems on their own.And one of the things that I didn’t fully appreciate until I left Yahoo and started looking outside Yahoo was just how much internal support our end users have for using Hadoop. So if something went wrong and they were not sure why, Hadoop likes to throw stack traces, for example, every time something goes wrong. At Yahoo, people just turn and say, “Hey, have you seen this before?” and there was a lot of people inside the company that had used it and had the experience for answering those questions. And ultimately, the central team that was operating Hadoop had seen pretty much everything that could ever go wrong and so could always answer a question for you.Again, on these small 20-node self-surved clusters, it’s a very different experience and people were spending days searching the web, desperately asking questions in these email forums to get some help in figuring out what’s going on. So in contrasting that experience of those larger Internet co mpanies where they had that professionally large scale Hadoop clusters to what I was saying in the industry, it became pretty clear that there was an opportunity to create a company that can offer Hadoop as a service the way you would experience it at Facebook or Twitter, in eBay or Yahoo. And that’s what we do at Altiscale.Martin: So Raymie, this means after you’ve left Yahoo, you’ve tried to validate your assumptions on whether there’s some kind of business need also because you have seen smaller companies which have been not very much focused on managing the cluster and so on. What was the next step then? So did you build some kind of MVP or did you just raise some money? What did you do?Raymie: By that point in time, I was a second time entrepreneur. There were investors who were interested in seeing what I was going to do next, so I had the benefit of having folks who were interested in backing me. So, I was able to raise a seed round fairly quickly. And we used that mo ney to start hiring because at the end of the day, getting the right talent is really the hardest part of the job and often causes the most delay, so that was very useful. And while we were doing that, even before I left Yahoo… In fact, my last title at Yahoo was entrepreneur in residence. I think I was Yahoo’s first and last EIR. And for various reasons, they gave me an opportunity to spend a few months starting to think about what my next steps were going to be. So I had the benefit of a couple of months of research upfront. And so I was able to validate that the issues that I saw indeed were pretty widespread.Martin: So once the investor wrote you a check, how did you go about acquiring your first employees? So how did you actually find them? Did you tap into a network? Did you post a job? Did you ask friends? What did you do?Raymie: By and large, it’s through networking, through people I knew directly. But there tends to be a transitive nature to that. So somebody I know i ntroduced me to who’s now our VP of Engineering, Ricardo Jenez. And even though we went to the same school, we both went to MIT, we didn’t quite overlap in time and we didn’t know each other at school but we got to know each other through a mutual friend. So sometimes it’s not quite that direct. I didn’t hire the friend but I hired the friend’s friend. So there’s levels of indirection there. And then once you hire… I hired Ricardo and our networks were slightly different. He spent some time at Google, for example, and was able to tap into the Google network a little bit more effectively than I could. So there is that spread of the corporate network as you bring people on. Your reach gets broader and broader.Martin: So Raymie, if you look back in time just by memory, the first 6 to 12 months, what was it really like? What type of obstacles did you really perceive in the day to day business where you say, “I think I’m not sure that this is the right business idea,â € or “There’re some kind of issue that I need to solve but actually I don’t know,” or something like that?Raymie: Yes. Let me think back. Again, getting that core initial team is always a big focus and at those stages where it’s literally three people and nothing, it’s a pretty big leap for people to sign up for that. And so that certainly took a fair bit of time. Altiscale is a bit unique as a technology company where a lot of technology companies, you’ve got some idea for some core IP and you hire a bunch of developers and they all go away, and you work on that IP for six months or so, and you really develop this relatively small compact piece of software that is really great in some dimension, and then you go out and you start to use it. And then you spend the next seven years putting layers of gunk around that beautiful center.At Altiscale, we inherited the Hadoop ecosystem, millions of lines of code. And so when you’re at that first three going on six technical people and you’ve got to own millions of lines of code, that’s a unique challenge for a startup. And so another aspect of our early struggles was to figure out how are we going to make that work and where are we going to start, because it felt like the problem was so big. And there were some false starts. One thing we ultimately decided to do was to restrict how much of the Hadoop ecosystem we would start with, with the idea of growing over time, and then really focusing in on deployment automation and not on multi-tenancy. It was the first technical problem we were going to tackle was another way in which we started to reduce the problem and the scope to something that a small team could work on.BUSINESS MODEL OF ALTISCALEMartin: Raymie, let’s talk about the business model. So you briefly touched on your target customers basically, which is more, as I understood, the smaller companies, right?Raymie: No. We don’t think of them as smaller companies per se. We really think of companies more in terms of how much data they have versus how many people they have. So ultimately when people say a big company versus a small company, you can measure in revenue, but often revenue is pretty directly correlated to the number of people. That’s the more traditional metric of “Hey, how big is a company?” But for us as a big data service provider, what matters a lot more is how much data you have versus how many people you have. It turns out that some of the smaller companies have much more data than some of the largest companies.So from that perspective, you can look at the amount of data, if you will, that an organization is ready and willing to put into a data processing system like Hadoop. You can maybe call it small, medium and large, where small is, say, 10 terabytes or less. Medium is maybe we can call it 20 terabytes or 15 terabytes, so medium is when you get into many tens of terabytes to hundreds of terabytes, maybe to a petabyte or so, but it’s not multiple petabytes. And large is multiple hundreds of terabytes. And for us, we tend to target the ones in the middle, the folks that have more typically a hundred to a few hundred terabytes to a petabyte or two. It’s a good range. As you get smaller than that, I think the problems of Hadoop become a little bit more self-manageable. As you get bigger than that, additional complexities start to come in that we’ll get to tackle over time, but again as a startup, you need to be focused. So that’s how we measure the size of our customers. It turns out that it’s a good swath of companies and it covers some of the largest companies in the world and it covers some of the smallest ones. It’s all over the map in terms of how big the company itself is.Martin: Raymie, can you briefly describe what is the value proposition that you are delivering to those target customers?Raymie: Sure. Well, at those scales, when you start to get into a hundred plus terabytes of data, maintaining your big data infrastructure. In our case, that’s anchored in the Hadoop Distributed File System. The Hive Metastore actually is an important component and then Spark and YARN sitting on top of that. So it’s the core platform. As you get to that hundreds to many hundreds of terabytes of data, keeping that operating well and, in particular, keeping jobs running fast and running reliably, completing it successful. It turns out to become harder and harder as you scale up. And I think it’s just the nature of distributed systems. There’s this kind of exponential issue where as you add more and more pieces, it gets exponentially more difficult to keep it all running reliably.And so the value proposition of Altiscale is to keep your big data infrastructure running well as you grow, as you scale, allowing your customers to focus on what they’re doing with Hadoop and not get wrapped up in running it day to day or worrying about how they’re going to grow it over time, which itself is a significant issue.Martin: But still the customer is providing the jobs, or are you supporting and inviting the job? Or is it only that you are trying to have some kind of maintenance or monitoring on whether the jobs are running correctly or not?Raymie: That’s a good question. I think that what we do not typically do is actually write the jobs themselves. Either the customers do that or there’s lots of software services companies out there who will help you write big data applications. So we’re really focused on keeping those jobs running well, which includes, as you point out, monitoring the jobs and helping to deal with problems. However, I think one unique service that we can provide is that a lot of times you’ve written a job but it’s not quite right, it’s not scaling well, it has performance problems, and so I think one service that we do provide is that where there are those particularly problematic jobs, we’ve got enough experience where we can say, “Hey, it looks like you have a skew problem or a memory problem or this or that.” We can give advice to help people quickly get that job working. And again going back to those founding stories of Altiscale where people were spending weeks at a time wrestling with Hadoop over what turned out to be a relatively trivial issue. We could really save customers a lot of time that way. And if what they had to do is go out and find some external consultant to come in to look at that, it would just be ridiculously expensive. But the fact is we’re sitting there and we’re monitoring the jobs. There’s certain telltale signs. There’s certain problems, so we can very quickly and easily say, “Hey, here’s a problem that you might want to look at.”Martin: Raymie, are those problems identified by humans or are you using something like machine learning and then automatic recommendation engines on what to do if that problem occurs?Raymie: Yes. Well, that’s a great question because in many ways it incorporates, I think, a standard assumption that people make. You either use humans or you use algorithms.Martin: Or both?Raymie: Yes, but I think the “or both” is not an insignificant point. I think that having a blend of people and machines is really the secret of doing a lot of things well. Part of that is indeed how we help customers. There are some automatic alerts that look for certain patterns, but there’s also more manual things, and there’s a whole spectrum there. But even if you look at how we operate the clusters themselves, we’re going back to “Hey, what were some of the challenges upfront?” I think we decided not to go start way over on the side of too much automation but rather start in a more moderate point, really have the automation and the human operators work hand in hand, and based on actual real world experience, use that to drive the technology and also to use that to say, “Hey, what are people best at? And let’s use what they’re good a t,” whereas “Where can we use machines to really ultimately just pull labor out of the activity?” So getting a good man-machine symbiosis, as we like to call it, is really core to our approach to a lot of problems here at Altiscale.Martin: Raymie, imagine you are going to a potential client and ask him whether he would like to buy an Altiscale product. How do you sell this kind of product over competitor products like other big data platform providers?Raymie: Sure. Well, I think it depends on who the customer is and what are their existing experiences with Hadoop. In the early days, all of our customers were actually what I would call Hadoop veterans. And what I mean by that is they’re not only people who have used Hadoop before but as an organization, they actually had Hadoop in production fairly successfully and yet they shifted over to us, which is a little bit counterintuitive, but there’s a reason for that. The reason is that over time Hadoop doesn’t get easier. It actually gets harder because you do more and you do more and the technology, it’s hard to believe but it actually changes faster and faster over time. The rate of improvement in the Hadoop ecosystem is just stunning. But if you’re trying to operate Hadoop cluster, keeping pace with all that change is very challenging.So if a customer prospect is already fairly experienced with Hadoop, we talk the same language. It becomes a lot easier. You can go in and say, “Hey, are you having this problem? Are you having that problem? Is it a pain? When is your next upgrade?” A lot of times, actually it’s the upgrade thing which tips them over because they’ll be a year out of date and we could say, “Hey, the latest Spark has all that stuff. Can we use it? Oh, no. My internal users are very upset.” And we have a common language that we can use and common experiences, and the dialogue actually is a little bit easier.A variation on that team is a lot of folks have set up a Hadoop clu ster initially for the focus of supporting some kind of what you might call production pipeline, some kind of ETL process where data comes in, it gets processed, it goes some place. That cluster was originally set up to just do this very mechanical thing, and that software itself is not evolving very quickly, so the people in charge of the cluster view it as a maintenance problem. But then what happens is some data scientists start to dig up because the data that’s running through those pipelines is very interesting to them. And before you know it, you’ve got a bunch of data scientists who are trying to use this cluster and it’s not working because it wasn’t set up for their active use, it doesn’t have the tools that they want to use, and they find themselves frustrated that they don’t have the kind of data science environment that they really like. So there are two we can relate to the actual grounded experiences that they have. A lot of times they say, “Hey, why donâ €™t you get a separate data science environment do that at Altiscale and leave the production part?” That’s fine to have too, and that’s very successful for us.I think it has been more challenging for organizations that are new to Hadoop. They say, “Hey, I think we ought to do Hadoop.” And in context, they don’t know what they don’t know. They don’t know how complicated Hadoop is going to be. They think of it more as a traditional software application where “Yes, in the first year or two, it’s a big pain and its going to cost us a lot of money. But once you get over the hump, it becomes easier. It goes into maintenance mode and we can be done with it.” And educating those customers that it doesn’t look like that, it just actually gets worse and worse, becomes a challenge to us because they don’t have those experiences. They don’t have the vocabulary. Fortunately, since we had those earlier customers, we can use them to provide some degree of testimony, an d that helps. Over time, we’ve been working on other ways to help educate people who are new to Hadoop that they should really think twice before they get too deep into running it themselves.Martin: So thinking about the Hadoop ecosystem, what are from your perspective the biggest misconceptions or mistakes the end users or companies are doing when they are interacting with Hadoop? You briefly touched on one.Raymie: Yes. Obviously for us, we think mistake number one is run it yourself. Let the experts do that for you. It saves you a lot of time and effort. I think that putting that one aside, I mentioned before that the rate of innovation in and around Hadoop is quite high, and I do think that another mistake people make is that they think they need to have the very, very latest, and a lot of times the latest new project that gets announced is really not ready to be used in a production way. So I think that’s actually another fairly common mistake.I think another mistake that pe ople have is they don’t understand very well what I would call the performance characteristics of various components. They understand the functional characteristics. When I put this query in, I’m supposed to get those results out. But they don’t understand the performance characteristics depending on how much data is in the table, for example. Is there a skew in the data? There’s a lot of factors that will determine what kind of performance you’re going to get. And I think there’s this unrealistic expectation that it’s just going to be fast for everything, and they don’t engineer their applications around a realistic expectation for what can be done. I think HBase actually is a particularly challenging technology in that regard. It’s great in many dimensions but I think people tend to think that it can do anything and it can’t and then get themselves in trouble. So understanding what are the performance characteristics and the failure characteristics to some degr ee and making sure that you engineer your application around those instead of making unrealistic expectations is another lesson for first time Hadoop users.ADVICE TO ENTREPRENEURS FROM RAYMIE STATA In Palo Alto (CA), we meet Founder CEO of Altiscale, Raymie Stata. Raymie talks about his story how he came up with the idea and founded Altiscale, how the current business model works, as well as he provides some advice for young entrepreneurs.INTRODUCTIONMartin: Hi. Today we are in Palo Alto in the Altiscale office. Hi, Raymie. Who are you and what do you do?Raymie: Hi. Yes, I’m Raymie Stata, the Founder and Chief Executive Officer of Altiscale. We do big data in the cloud using both Hadoop and Spark.Martin: What did you do before you started this company? And how did you come up with the idea for Altiscale?Raymie: Well, in many ways, the roots of Altiscale go all the way back to AltaVista. If you remember that search engine from the 1990’s. I was lucky enough to have a chance to work on that. I actually got out of college thinking that I would work in a research lab, and that research lab was at Digital Equipment Corporation where they created the AltaVista web search engine. So while I was there, I think pretty much everybody in that laboratory got pulled into the world of web search, and I was no exception. So I spent quite a few years working on AltaVista, getting experience in web search.And then after the dot com crash in the early 2000’s, I actually started my first company which was Desktop Search Company, and we ran that for about four years and started to get some traction. Around 2004, that company was acquired by Yahoo. And about that time, actually slightly earlier, Yahoo had acquired a bunch of companies. They acquired Overture, and Overture, ironically enough, had just acquired AltaVista. So Yahoo had bought in all the old tech that I used to work with through Overture. They also bought the web search assets of FAST, which is a European search engine company, and a few other assets. So they were building up a search technology to go compete head to head with Google. And a little after those major acquisitions, they decided they wanted to have some Desktop Search as well, so they acquired my company.So that was 2004, and in the history of Hadoop, that was a significant year. That was the year that the MapReduce paper was published from Google. And for people in the search world, that was a really fascinating paper. I think for us, the basic technique that they were using, which was a cluster-wide search, was something that pretty much everybody in the search world had developed in a way. But the MapReduce paper took that basic technique and put it in a very elegant package where the mechanism of the MapReduce paradigm was very clearly separated from the application code. And so one could very easily develop and improve the framework code, the heart of the distributed system part, if you will, and pan it of the application code. And that very clean separation, I think, was missing in most of the search world.So it got our attention for sure at Yahoo and I think in other search companies at the time. But what was fasc inating about that paper as well is it got the attention of, I think, a broader universe. At that time, Google was certainly in ascendance. People were beginning to think, “There’s some magic over there. They must know something we don’t know.” And so that paper, I think, was seen as an insider’s look into the magic of Google. And so there was a lot of very broad fascination with that paper. So interestingly, other search engines, they were at that time a little bit more competitive in the world of search, so there were other search engines. I think other companies were interested in doing better than Google, so they all embarked on these very ambitious internal projects to do something better than Google.But there were a few of us at Yahoo who said, “Instead of trying to out-engineer Google, maybe what we can do is demystify this a little bit by basically taking that concept and implementing it in open source.” And I had known Doug Cutting prior to getting to Yahoo. W e built some work with the Internet archive, and I got to know his work with the Nutch Foundation at the time. He had his own foundation. And so I was able to get Doug to come work at Yahoo first as a contractor and then ultimately as employee, and we decided, “Yes, we’re going to do the open source MapReduce.” And that complemented well work that was already in place in the Nutch search engine where they had also implemented this thing called the Google File System.So that was how Yahoo got involved with Hadoop. I think Yahoo over the years made massive investments in Hadoop that really made it the enterprise strength software that it is today. So I was actually just at the very beginning of my tenure at Yahoo that I was getting a project on the way. Through the years at Yahoo, I had a number of positions. So I started in the algorithmic web search team where I was the chief architect of that team. And then over the years, I was the chief architect of the search and advertisi ng team, and then the chief architect of all of Yahoo, and ultimately became the CTO of Yahoo. And as I got broader and broader responsibilities at Yahoo, I helped drag Hadoop along with me to be used in broader and broader use cases across Yahoo. And as a result, by the time I left Yahoo, we had a very large central installation for Hadoop. We had 40,000 nodes of Hadoop over a thousand users being used for a very wide variety of use cases.When I started thinking about leaving Yahoo, since I had a lot of experience with Hadoop inside of Yahoo, I took a look to see, “Hey, what’s it like to use Hadoop outside of a company?” And not just Yahoo. I knew how folkswere using it at Facebook. Twitter wasn’t so big at the time, but eBay. And it was the same model, a large central cluster run by a very competent professional team. Outside of those larger Internet companies, what I saw was something very different, which was these small clusters, 20 nodes. Very often they were being sup ported, if at all, by an operations team. It was like a discretionary effort. They weren’t really full time. Usually there were other production activities that had more of a priority. So the users of these clusters were often stuck dealing with problems on their own.And one of the things that I didn’t fully appreciate until I left Yahoo and started looking outside Yahoo was just how much internal support our end users have for using Hadoop. So if something went wrong and they were not sure why, Hadoop likes to throw stack traces, for example, every time something goes wrong. At Yahoo, people just turn and say, “Hey, have you seen this before?” and there was a lot of people inside the company that had used it and had the experience for answering those questions. And ultimately, the central team that was operating Hadoop had seen pretty much everything that could ever go wrong and so could always answer a question for you.Again, on these small 20-node self-surved clusters, it ’s a very different experience and people were spending days searching the web, desperately asking questions in these email forums to get some help in figuring out what’s going on. So in contrasting that experience of those larger Internet companies where they had that professionally large scale Hadoop clusters to what I was saying in the industry, it became pretty clear that there was an opportunity to create a company that can offer Hadoop as a service the way you would experience it at Facebook or Twitter, in eBay or Yahoo. And that’s what we do at Altiscale.Martin: So Raymie, this means after you’ve left Yahoo, you’ve tried to validate your assumptions on whether there’s some kind of business need also because you have seen smaller companies which have been not very much focused on managing the cluster and so on. What was the next step then? So did you build some kind of MVP or did you just raise some money? What did you do?Raymie: By that point in time, I was a seco nd time entrepreneur. There were investors who were interested in seeing what I was going to do next, so I had the benefit of having folks who were interested in backing me. So, I was able to raise a seed round fairly quickly. And we used that money to start hiring because at the end of the day, getting the right talent is really the hardest part of the job and often causes the most delay, so that was very useful. And while we were doing that, even before I left Yahoo… In fact, my last title at Yahoo was entrepreneur in residence. I think I was Yahoo’s first and last EIR. And for various reasons, they gave me an opportunity to spend a few months starting to think about what my next steps were going to be. So I had the benefit of a couple of months of research upfront. And so I was able to validate that the issues that I saw indeed were pretty widespread.Martin: So once the investor wrote you a check, how did you go about acquiring your first employees? So how did you actually fi nd them? Did you tap into a network? Did you post a job? Did you ask friends? What did you do?Raymie: By and large, it’s through networking, through people I knew directly. But there tends to be a transitive nature to that. So somebody I know introduced me to who’s now our VP of Engineering, Ricardo Jenez. And even though we went to the same school, we both went to MIT, we didn’t quite overlap in time and we didn’t know each other at school but we got to know each other through a mutual friend. So sometimes it’s not quite that direct. I didn’t hire the friend but I hired the friend’s friend. So there’s levels of indirection there. And then once you hire… I hired Ricardo and our networks were slightly different. He spent some time at Google, for example, and was able to tap into the Google network a little bit more effectively than I could. So there is that spread of the corporate network as you bring people on. Your reach gets broader and broader.Martin: So Raymie, if you look back in time just by memory, the first 6 to 12 months, what was it really like? What type of obstacles did you really perceive in the day to day business where you say, “I think I’m not sure that this is the right business idea,” or “There’re some kind of issue that I need to solve but actually I don’t know,” or something like that?Raymie: Yes. Let me think back. Again, getting that core initial team is always a big focus and at those stages where it’s literally three people and nothing, it’s a pretty big leap for people to sign up for that. And so that certainly took a fair bit of time. Altiscale is a bit unique as a technology company where a lot of technology companies, you’ve got some idea for some core IP and you hire a bunch of developers and they all go away, and you work on that IP for six months or so, and you really develop this relatively small compact piece of software that is really great in some dimension, and then you go out and you st art to use it. And then you spend the next seven years putting layers of gunk around that beautiful center.At Altiscale, we inherited the Hadoop ecosystem, millions of lines of code. And so when you’re at that first three going on six technical people and you’ve got to own millions of lines of code, that’s a unique challenge for a startup. And so another aspect of our early struggles was to figure out how are we going to make that work and where are we going to start, because it felt like the problem was so big. And there were some false starts. One thing we ultimately decided to do was to restrict how much of the Hadoop ecosystem we would start with, with the idea of growing over time, and then really focusing in on deployment automation and not on multi-tenancy. It was the first technical problem we were going to tackle was another way in which we started to reduce the problem and the scope to something that a small team could work on.BUSINESS MODEL OF ALTISCALEMartin: Raymi e, let’s talk about the business model. So you briefly touched on your target customers basically, which is more, as I understood, the smaller companies, right?Raymie: No. We don’t think of them as smaller companies per se. We really think of companies more in terms of how much data they have versus how many people they have. So ultimately when people say a big company versus a small company, you can measure in revenue, but often revenue is pretty directly correlated to the number of people. That’s the more traditional metric of “Hey, how big is a company?” But for us as a big data service provider, what matters a lot more is how much data you have versus how many people you have. It turns out that some of the smaller companies have much more data than some of the largest companies.So from that perspective, you can look at the amount of data, if you will, that an organization is ready and willing to put into a data processing system like Hadoop. You can maybe call it small , medium and large, where small is, say, 10 terabytes or less. Medium is maybe we can call it 20 terabytes or 15 terabytes, so medium is when you get into many tens of terabytes to hundreds of terabytes, maybe to a petabyte or so, but it’s not multiple petabytes. And large is multiple hundreds of terabytes. And for us, we tend to target the ones in the middle, the folks that have more typically a hundred to a few hundred terabytes to a petabyte or two. It’s a good range. As you get smaller than that, I think the problems of Hadoop become a little bit more self-manageable. As you get bigger than that, additional complexities start to come in that we’ll get to tackle over time, but again as a startup, you need to be focused. So that’s how we measure the size of our customers. It turns out that it’s a good swath of companies and it covers some of the largest companies in the world and it covers some of the smallest ones. It’s all over the map in terms of how big the company itself is.Martin: Raymie, can you briefly describe what is the value proposition that you are delivering to those target customers?Raymie: Sure. Well, at those scales, when you start to get into a hundred plus terabytes of data, maintaining your big data infrastructure. In our case, that’s anchored in the Hadoop Distributed File System. The Hive Metastore actually is an important component and then Spark and YARN sitting on top of that. So it’s the core platform. As you get to that hundreds to many hundreds of terabytes of data, keeping that operating well and, in particular, keeping jobs running fast and running reliably, completing it successful. It turns out to become harder and harder as you scale up. And I think it’s just the nature of distributed systems. There’s this kind of exponential issue where as you add more and more pieces, it gets exponentially more difficult to keep it all running reliably.And so the value proposition of Altiscale is to keep your big data in frastructure running well as you grow, as you scale, allowing your customers to focus on what they’re doing with Hadoop and not get wrapped up in running it day to day or worrying about how they’re going to grow it over time, which itself is a significant issue.Martin: But still the customer is providing the jobs, or are you supporting and inviting the job? Or is it only that you are trying to have some kind of maintenance or monitoring on whether the jobs are running correctly or not?Raymie: That’s a good question. I think that what we do not typically do is actually write the jobs themselves. Either the customers do that or there’s lots of software services companies out there who will help you write big data applications. So we’re really focused on keeping those jobs running well, which includes, as you point out, monitoring the jobs and helping to deal with problems. However, I think one unique service that we can provide is that a lot of times you’ve written a job b ut it’s not quite right, it’s not scaling well, it has performance problems, and so I think one service that we do provide is that where there are those particularly problematic jobs, we’ve got enough experience where we can say, “Hey, it looks like you have a skew problem or a memory problem or this or that.” We can give advice to help people quickly get that job working. And again going back to those founding stories of Altiscale where people were spending weeks at a time wrestling with Hadoop over what turned out to be a relatively trivial issue. We could really save customers a lot of time that way. And if what they had to do is go out and find some external consultant to come in to look at that, it would just be ridiculously expensive. But the fact is we’re sitting there and we’re monitoring the jobs. There’s certain telltale signs. There’s certain problems, so we can very quickly and easily say, “Hey, here’s a problem that you might want to look at.”Mar tin: Raymie, are those problems identified by humans or are you using something like machine learning and then automatic recommendation engines on what to do if that problem occurs?Raymie: Yes. Well, that’s a great question because in many ways it incorporates, I think, a standard assumption that people make. You either use humans or you use algorithms.Martin: Or both?Raymie: Yes, but I think the “or both” is not an insignificant point. I think that having a blend of people and machines is really the secret of doing a lot of things well. Part of that is indeed how we help customers. There are some automatic alerts that look for certain patterns, but there’s also more manual things, and there’s a whole spectrum there. But even if you look at how we operate the clusters themselves, we’re going back to “Hey, what were some of the challenges upfront?” I think we decided not to go start way over on the side of too much automation but rather start in a more moderate point, really have the automation and the human operators work hand in hand, and based on actual real world experience, use that to drive the technology and also to use that to say, “Hey, what are people best at? And let’s use what they’re good at,” whereas “Where can we use machines to really ultimately just pull labor out of the activity?” So getting a good man-machine symbiosis, as we like to call it, is really core to our approach to a lot of problems here at Altiscale.Martin: Raymie, imagine you are going to a potential client and ask him whether he would like to buy an Altiscale product. How do you sell this kind of product over competitor products like other big data platform providers?Raymie: Sure. Well, I think it depends on who the customer is and what are their existing experiences with Hadoop. In the early days, all of our customers were actually what I would call Hadoop veterans. And what I mean by that is they’re not only people who have used Hadoop before but as an organization, they actually had Hadoop in production fairly successfully and yet they shifted over to us, which is a little bit counterintuitive, but there’s a reason for that. The reason is that over time Hadoop doesn’t get easier. It actually gets harder because you do more and you do more and the technology, it’s hard to believe but it actually changes faster and faster over time. The rate of improvement in the Hadoop ecosystem is just stunning. But if you’re trying to operate Hadoop cluster, keeping pace with all that change is very challenging.So if a customer prospect is already fairly experienced with Hadoop, we talk the same language. It becomes a lot easier. You can go in and say, “Hey, are you having this problem? Are you having that problem? Is it a pain? When is your next upgrade?” A lot of times, actually it’s the upgrade thing which tips them over because they’ll be a year out of date and we could say, “Hey, the latest Spark has all that stuff. Can we use it? Oh, no. My internal users are very upset.” And we have a common language that we can use and common experiences, and the dialogue actually is a little bit easier.A variation on that team is a lot of folks have set up a Hadoop cluster initially for the focus of supporting some kind of what you might call production pipeline, some kind of ETL process where data comes in, it gets processed, it goes some place. That cluster was originally set up to just do this very mechanical thing, and that software itself is not evolving very quickly, so the people in charge of the cluster view it as a maintenance problem. But then what happens is some data scientists start to dig up because the data that’s running through those pipelines is very interesting to them. And before you know it, you’ve got a bunch of data scientists who are trying to use this cluster and it’s not working because it wasn’t set up for their active use, it doesn’t have the tools that they want to u se, and they find themselves frustrated that they don’t have the kind of data science environment that they really like. So there are two we can relate to the actual grounded experiences that they have. A lot of times they say, “Hey, why don’t you get a separate data science environment do that at Altiscale and leave the production part?” That’s fine to have too, and that’s very successful for us.I think it has been more challenging for organizations that are new to Hadoop. They say, “Hey, I think we ought to do Hadoop.” And in context, they don’t know what they don’t know. They don’t know how complicated Hadoop is going to be. They think of it more as a traditional software application where “Yes, in the first year or two, it’s a big pain and its going to cost us a lot of money. But once you get over the hump, it becomes easier. It goes into maintenance mode and we can be done with it.” And educating those customers that it doesn’t look like that, it j ust actually gets worse and worse, becomes a challenge to us because they don’t have those experiences. They don’t have the vocabulary. Fortunately, since we had those earlier customers, we can use them to provide some degree of testimony, and that helps. Over time, we’ve been working on other ways to help educate people who are new to Hadoop that they should really think twice before they get too deep into running it themselves.Martin: So thinking about the Hadoop ecosystem, what are from your perspective the biggest misconceptions or mistakes the end users or companies are doing when they are interacting with Hadoop? You briefly touched on one.Raymie: Yes. Obviously for us, we think mistake number one is run it yourself. Let the experts do that for you. It saves you a lot of time and effort. I think that putting that one aside, I mentioned before that the rate of innovation in and around Hadoop is quite high, and I do think that another mistake people make is that they think they need to have the very, very latest, and a lot of times the latest new project that gets announced is really not ready to be used in a production way. So I think that’s actually another fairly common mistake.I think another mistake that people have is they don’t understand very well what I would call the performance characteristics of various components. They understand the functional characteristics. When I put this query in, I’m supposed to get those results out. But they don’t understand the performance characteristics depending on how much data is in the table, for example. Is there a skew in the data? There’s a lot of factors that will determine what kind of performance you’re going to get. And I think there’s this unrealistic expectation that it’s just going to be fast for everything, and they don’t engineer their applications around a realistic expectation for what can be done. I think HBase actually is a particularly challenging technology in that rega rd. It’s great in many dimensions but I think people tend to think that it can do anything and it can’t and then get themselves in trouble. So understanding what are the performance characteristics and the failure characteristics to some degree and making sure that you engineer your application around those instead of making unrealistic expectations is another lesson for first time Hadoop users.ADVICE TO ENTREPRENEURS FROM RAYMIE STATAMartin: So Raymie, over the last two companies that you started, what have been the major learnings that you got and that you can share with other people interested in becoming an entrepreneur?Raymie: Well, I think one thing that you’ll hear over and over again and in some sense you can never do enough of it is that the more you can talk to and engage potential users of your product, the better off you are. And there’s no point in diminishing returns there. And so I would say that that would go to the top of the list because I think people alwa ys think they’ve done enough of that, and myself is no exception to that, and yet if you push yourself a little bit harder, you find out, “Wow, this is even better.” So I would say never be satisfied with the amount of customer input you get.I think on a related note, what I’ve noticed, in fact, if you compare, I’ve also consulted with another, I’ve been involved with startups in various capacities going back for many years actually, and one of the things that I’ve observed is I think the rate at which you can start to actually engage a customer in some type of activity, even as a paid customer, but if you put that aside, like “Hey, give this a try. I’m getting it to try this with folks” way, way earlier than you think is at all realistic.I think there’s a tendency to feel like, “Oh, you have to get to a certain point,” especially a few more engineering during the company. You have to get the thing to a certain point, and if you engage too early, it’s goi ng to be wasteful to the customer or to you. And I think that what time has shown, especially the last 10 to 15 years, is that in fact you can engage with folks by actually giving them software way earlier than the typical engineer thinks is possible and benefit from doing that. So I think that not only talking to a large number of customers early on but here you have to be a little bit mindful. You can’t do too manyof these, but engaging with one or two almost from the very beginning is really, really critical as well.Martin: When did you start engaging with customers?Raymie: When did we start engaging customers? Let’s see. I’d have to go back. I don’t know what the timing was. I do think it was probably six to nine months into starting. It’s pretty early but maybe it could have been even faster. But it was a nice little tiny startup itself. It was actually a hedge fund. And it was interesting because they had not that much data. It was less than a terabyte. But they were expecting that was a sample of a much larger data set they were going to get, which would have measured in a few tens of terabytes. Still not huge. And they were expecting that to come any minute now. So they were a little bit in a panic. As a hedge fund, it was the perfect customer for us because they were not at all interested in running Hadoop. Any smart people they had, they weren’t figuring out traits, not figuring out Hadoop, which was actually not the case in many other companies where if you’ve got smart people. In some sense smart people get bored in a lot of companies, and so you throw them on Hadoop to keep them challenged. And so that can sometimes be a challenge for us because we’re saying, “Hey, I know that’s interesting, but let us take that away from you. Find something else to do.” At hedge funds, that’s not an issue, so it was a great first customer for us.Another thing that was great about it is that there’s alleged tens of terabytes a day that wa s going to show up any minute now, it took a couple of months for that data to show up, so we had time to get seasoned and to get ready for that larger data set.Martin: What other type of advice can you provide, Raymie?Raymie: As I indicated, on the one hand, I was lucky to have a little bit of a track record and therefore the ability to raise money upfront, but I think that’s a mixed blessing. As soon as you raise money, there’s a clock that starts to tick and people want to say, “Okay, how many customers do you have?” And I think a more modern, quite honestly, kind of approach is for two to five people to really take a year to somehow figure out how to make that work for themselves personally from a financial perspective but to really take a longer period of time to find that idea to do the kinds of things that I was talking about, which is to talk to a number of people and to maybe even engage in a couple. So I think all things being equal, in this regard I’d suggest do ing something a little different from what I did, which is to be a little bit more patient in the beginning phases.One thing that I am happy that I did, it might seem a little bit mechanical, but in both cases, I took time to educate myself on some of, you might call it, the formalities of running a company in terms of getting the IT people work in place, getting a documentation system in place, having your records in good shape. For example, if you go down the path I just recommended, which is you spend a year doing stuff and you find pay dirt, like here is this thing and you find an investor that wants to go in, they’re going to put you through a due diligence process. And if you had all of your funds come in and hack on the weekends and there’s no clear ownership of the code and there’s no records or anything like that, you could find yourself either spending a lot of time trying to put all that back into place or taking a lot of risk, where essentially you say, “Hey, I p romise that if my friend who came hack for that weekend comes and sues the company after we’ve become a billion-dollar company, I will own that and I will take all of that risk,” which is not a good thing to do. So I think while I would recommend not necessarily being in a big hurry to raise a lot of money in an early company without seasoning your idea, I would say getting the formalities of the company in place early on and being very clean with respect to your records is important.Martin: Raymie, thank you so much for sharing the knowledge.Raymie: Sure. My pleasure.Martin: And if you are a company with lots of data but actually you don’t want to bother managing them yourself, check out Altiscale.Raymie: Thank you.

John P. Millis, Ph.D - ThoughtCo

Evolution Of Early And Modern Hominins Essay - 1537 Words

Evolution is a process in which living organisms develop across a period of time (Bourrat, 2014). It also shows how one species is genetically linked to another or how it has common attributes to other organisms (Bourrat, 2014). Throughout their course of life each species will go through a process known as natural selection. Natural selection serves as an ability to pass on better genes on to the offspring in order to maintain an increasingly higher genetic code (Bourrat, 2014). Evolution in most species occurs when the organism adapts to a constantly changing environment (Bourrat, 2014). This increases not only their chances of surviving, but also their ability to reproduce (Bourrat, 2014). Throughout the constant change of hominin species it has been said that humans evolved from apes. Although, humans may not be genetically linked to apes they do share some common characteristics which is bipedal locomotion (Bourrat, 2014). Furthermore, this research paper will discuss all the d ifferent ideas that helped identify the evolution of early and modern hominins, and how the origins of bipedalism came to be. Bipedal locomotion is the ability to walk upright by using only two legs (Richmond Jungers, 2008). Bipedalism is known to occur in mostly hominins (Richmond Jungers, 2008). Bipedalism is the connection that binds the idea that humans are related to apes since both species have the shared ability of bipedal locomotion (Richmond Jungers, 2008). There are manyShow MoreRelatedEvolution Of Humans : Human Biology And Early Culture Essay1336 Words   |  6 PagesEvolution of Humans No one can be absolutely sure when the first humans actually walked the Earth, only approximations can be made. Approximately 200,000 years ago species are developed in Africa. Most human species and most human biology and early culture in its broadest sense originated in Africa. Archaeologist and anthropologist may have been able to pinpoint exactly where the early human species lived and approximately how long ago they lived but are their assumptions correct? A huge part ofRead MoreThe Theories Of Hominin Evolution By Richard Potts ( 1999 )1056 Words   |  5 Pagesand dominant species? Scientists for years have sought to fully understand the physical and cognitive evolution of the hominin clade. If human evolution did start off with apelike habits, why are there human traits such as terrestrial bipedality, toolmaking, and larger brains? When did these traits emerge? What gave rise to these traits? In his article, â€Å"Environmental Hypotheses of Hominin Evolution,† Richa rd Potts (1999) presents various explanations to these questions. He discusses the hypothesesRead MoreThe Discovery Of A Fossil Specimen1472 Words   |  6 PagesAfter so many years of searching and excavating, my partners and I have discovered our first hominin fossil. After all the digging, cleaning, and cataloging of hominin discoveries is complete, we begin to start analyzing mysterious specimen #6. It looked a lot like a modern human but the skull features is slightly different and the molars is quite large. From what we have noticed at first sight, the incisors, canines and the premolars of the specimen are missing. Without analyzing and measuring theRead MoreSpeech : A Comparison Between Human And Primates1660 Words   |  7 Pages Then we question: where did we obtain this distinctive trait? Most animals make sounds and grunts to communicate. Are humans really the only species that can communicate in a form of spoken language? When it comes to evolution, humans evolved fro m apes. The first putative hominin is Sahelanthropus tchadensis from Chad, which is about 6-7 million years old, as noted by Michel Brunet among others in their 2002 paper in Nature, while our closest living relative to the Homo sapiens is the chimpanzeeRead MoreHistory And Evolution Of Africa850 Words   |  4 PagesAfrica played a pivotal role in human evolution. It’s the site of the beginning of human evolution, as they slowly evolved from their primitive ancestors and continued to evolve for millions of years. A majority of the fossils, some dating back almost 7 million years, are found in Africa. As ancient humans migrated out of Africa they stayed close to the coast. Scientists have been able to trace their migration to areas around the Indian Ocean, South Asia, and even as far down as Australia, also referredRead More The Important Discovery of Kenyanthropus Platyops - The Flat Faced Man of Kenya909 Words   |  4 Pagessemi-desert area, could hold bold new implic ation for the origin of man. The finding was the skull of a very early hominid which displays facial features of both modern man and early, more primitive ancestors. The findings have been dated to approximately 3.5 million years, a time period once thought to be dominated by human ancestors that did not posses any noticeable and unique characteristics held by modern man. The find was discovered by Meave Leakey of the National Museums of Kenya and her colleaguesRead MoreEvolution of Intelligence1228 Words   |  5 Pageshas evolved from the past. The innovation of fire furthered to the light bulb, as the hut became the skyscraper. This topic is worthy to investigate because modern humans have advanced so greatly, but how exactly had our genius evolved and where did our intelligence start. How are the intelligence of early humans different from that of modern humans, and what inferences can be made from this data? What is intelligence exactly? Intelligence is the ability to acquire and apply knowledge and skillsRead MoreHuman Evolutionary Traits and Behjaviours: Bipedalism Essay1319 Words   |  6 Pagesdifficult to determine. Controversy lies with the suggestion that bipedalism arose from as early as 5.8 million years ago, in the late Miocene era, but it can be scientifically defined that the first definite bipedal hominin was the Australopithecus anamensis in the Pliocene. These findings suggest that at 3.9-2.9 million years ago, bipedalism was evolving; certain conditions acted as influences upon the hominins to develop bipedality. As such, specific selection pressures have since been proposed duringRead MoreEssay on Relationship Between Modern Humans and Neanderthal 1593 Words   |  7 Pagesfossils belonged to an extinct human and our closest evolutionary relative (Hublin and Pà ¤Ãƒ ¤bo, 2006). Since then, questions about their relationship with modern humans have been fiercely debat ed between anthropologists. But what attracts most interest from scientists and popular media is the possibility of hybridization between Neanderthals and modern humans if, in other words, they were a genetically different specie or a single specie capable of producing offspring. The first morphological featuresRead MoreComplication Of Birth.1575 Words   |  7 Pagesadvanced cognitive functions. Culture nbsp;nbsp;nbsp;nbsp;nbsp;nbsp; In chapter eight quot;Early Hominisquot; of the textbook, quot;Introduction to Cultural Anthropologyquot; by Conrad Phillip Kottak discussed bipedalism traditionally has been viewed as an adaptation tobopen grassland or savanna country (Kottak, Phillip Conrad, 129). On the other hand, compared with contemporary humans, early hominis has very small brains (Kottak, Phillip Conrad, 129). Compared with the young of other primates

Quani’s Story Free Essays

Family Genealogy Paper A family that prays together stays together is an idiom passed down from generations to generations. My family stands firm on this phrase and will continue to pass it down to generations to come. As I conducted a few conversations with family members, from the maternal side of my family, I understood why they believed in the quote and I will continue to pass it down to my kids and family. We will write a custom essay sample on Quani’s Story or any similar topic only for you Order Now The reason I researched my mother’s side of the family was because they are arger than my father’s side and they are in close proximity of each other. My mom’s side of the family grew up in a small North Carolinian town called Pinetop. I went back as far as my great-great grandparents and their names were Edward and Rachael Crummedy. They were sharecroppers and they both passed away when my great-grandmother was 9 years old. My great-grandparents are the late Columbus and Clara Crummedy Dickens. Born in 1913, Columbus Dickens grew up to be a sharecropper and provider for his family. Columbus worked for a white man who wned the property that the Dickens family resided on. He would work on the farm all year long Just so that the family could stay on the farm and also have food to eat. His return pay would be a stipend at the end of the year that went towards the bills for the house, so he never really saw any money for his own good. During certain times of the year he had to hire other people to help him maintain the farm (who were usually family members) and they would receive their pay from whatever Columbus received. If Colu How to cite Quani’s Story, Papers

The Importance of Marketing to Organisations in the Twenty-First Century free essay sample

Although these tactics of marketing are true, they are ineffective with no the sound basis of knowledge about the market, the environment, and most importantly having a solid understanding of how customers behave, their motivation for purchase, their awareness and their preferences. All these strategies must be integrated to ensure that an organisation is successful in its operations. Nintendo Co. , Ltd. is a toy and home entertainment company that is famous worldwide for its popular home video games and revolutionary consoles. Nintendo has changed the concept of home entertainment all over the world. 1 Nintendo design, manufacture and manufacture a wide range of products ranging from the revolutionary battery-operated Game-Boy in the 1980’s, the Game Cube, and Super Mario Bros to name a few. Nintendo’s current line-up of video game systems includes the Nintendo DS Lite and Wii. Nintendo continues to create its unique software by ensuring that the ‘hardware and software are created with only one goal in mind, an enjoyable playing experience for all’. We will write a custom essay sample on The Importance of Marketing to Organisations in the Twenty-First Century or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page This approach has allowed Nintendo to produce products and characters beloved by people around the world. Marketing has become extremely important in the 21st century due to the changes in our modern society, where buyers and markets have become too diverse and complex to have one simple marketing strategy to meet the needs of them all. This is due to cultural changes and technological advancements, which has created a market that is fragmented. This change has been evident in Nintendo, as over the past two decades, the video game industry has grown ‘exceedingly, with annual sales rivalling box office eceipts for the movie industry’3. Therefore we can see that marketing is essential to Nintendo as due to the changes in their market size they have had to implement a strategy to persuade people from all over the world to play video games regardless of age, gender, culture, and even lifestyle. In order to understand the current significance of marketing to Nintendo, and other organisations we have to progress away from our prior understanding of marketing and move towards the new sense of ‘satisfying customer needs’. Figure 1. 0 Selling can only take place after the product has been produced; it is a forceful approach, which focuses on maximising profits through sales volume. On the contrary, marketing is instigated long before the company has even made the product. Marketing is an Integrated Plan, which includes product, price, promotion and distribution, backed up by a satisfactory environmental assessment, consumer research, and opportunity analysis with emphasis of maximising profits through customer satisfaction. During the 1960’s to the 1980’s Nintendo was a company that was product-led, it began a drive towards diversification and innovation, which eventually led to it becoming a household word in the late 1980s. They did this so that they could break in to the gaming industry and reduce their risks by having various products in their product line. However, Nintendo is a company, which has always been at the top of their game, even back then they understood that the success of marketing lies with the customers. An example of this can be found when they entered the United States, where the ‘of the U. S. home video industry had plummeted from a $3 billion peak in 1983 to a $100 million trough in 1985’5. However, Nintendo test marketed its games during the slum and found that the problems were caused by an excess of uninspiring, low-quality games therefore they took Seize of this opportunity and introduced sophisticated software to gain customer loyalty and enthusiasm. In order to look at how Nintendo’s marketing has changed in the 21st century, the core concepts of marketing will be taken into consideration and how Nintendo delivers value in each concept to those affected by its transaction. Figure 1. 1 The concept of ‘needs, wants and demands’ defines how individuals are influenced culturally and socially to satisfy a need which is not currently met. The demand is when the customers have necessary resources to obtain their wants. The second concept, ‘marketing offers’ are the value propositions companies offer ‘to satisfy human needs or demands’. The third concept of ‘value and satisfaction’ looks at how the product has satisfied consumer’s needs and it has met their expectations. This all leads to the fourth and fifth concept of ‘exchange, transactions and relationships’ leading to ‘markets’ where actual and potential buyers of the product, who have similar needs and wants meet. Nintendo has integrated these concepts of marketing in the 21st century to move away from the selling concept to the marketing concept. Think about the Nintendo Wii, which is outselling its rivals Playstation3, and the Xbox 360, the reason for this lies in Nintendo understanding consumer behaviour. Nintendo looked at how people who were not interested in consoles spent their time. Through market research they found that those people preferred to do sociable/physical activities, so they produced a physical product that requires a lot of exercise to play it. Thus their market offering of the Wii bundled the social activities of these groups, into one simple to use console. Through modern marketing approach of customer-led innovation they have given their customers value and satisfaction to ensure that they can but relationships with customers so that they become and remain loyal to Nintendo for the long-term. To understand the key concepts better and how firm must find ways to discover unfulfilled customer needs and brings products to the market to satisfy those needs can be understood by looking at the marketing process: Diagram2. 0 Situation Analysis Managers need information to determine customer-buying decisions so that they can tailor products to meet unfulfilled needs. The organisation also needs to examine the external (macro-environment) and the internal (microenvironment) environment so that they can meet opportunities and avoid threats. There are several frameworks that can be used to add structure to the situation analysis, however, the SWOT (strength, weakness, threats and opportunities) analysis will be used to assess the, most relevant problems and opportunities of Nintendo and how well equipped they are to deal with them. In regards to Nintendo, we have already seen that by analysing the market they have been able to find a gap in the market. However this is not enough for Nintendo as with only three main companies; Sony, Microsoft and Nintendo, the video gaming industry is highly competitive as the product life cycle of a console is about four to five years. 6 They must ensure that they offer different selections of innovative products, and features of their units, as threats of substitution and rivalry amongst the competitors is high. This is also due to the development of the ‘Digital age’ and the ‘Explosion of the Internet’ where kids can now play their friends on their PC’s. This is a main threat, is often unlicensed as a result companies such as Nintendo will need to take legal action which can lead to additional cost to the company. The weakness of the video gaming industry is that they do not appeal to older people and females. However, Nintendo have taken seize of this opportunity with the launch of the Nintendo DS which is designed for older demographics as well as females aged 5-17years old female gamers. Nintendo can match its own capability with the opportunities in order to satisfy customer needs better than the competition by implementing a ‘marketing strategy’. This is the second element of the marketing process, this is a three-way process of segmentation, targeting and positioning. Figure 2. 1 There has been a move from mass marketing to target marketing as buyers differ in wants needs and resources. Mass marketing is when the company treats the whole market as homogeneous group but offering the same product, promotion and distribution for all customers. Target marketing is when the total market is divided in to smaller segments, where products are developed to meet the characteristics of each segment. Segmentation is when the target market is divided in to smaller pieces based on meaningful and shared characteristics. Targeting is the evaluation of market segments to decide which to go for; an organisation must do this because they can not effectively serve all segments in the market. Positioning is developing a market strategy, which tries to influence how a particular market segment perceives a good or service compared to the competition. There are two ways to implement you position, by having a Unique Selling Point or by having an Emotional Selling Point so your product has a unique association to the customer compared to your competitors. The gaming industry is expanding for various ages, namely the older generation and even more rapidly for various ages within the female population. As you can see (figure 2. 1), Nintendo largely dominates the hand-held gaming industry for the male population between the ages of 5-17, however there is still a large gap in gaming as a whole. Figure 2. 2 Nintendo has adopted demographic segmentation. They have decided to target girls between the ages of 5-17 with their Nintendo Dogs and people over the age of 45 with their Brain Age Series on the Nintendo DS. The Brain Age series is said to ‘improve mental agility and even slow the onset of dementia and Alzheimers disease 7’ Targeting older gamers is proving a smart move by Nintendo as software makers are also trying to wean themselves off the shrinking teen market. However, Nintendo will have the advantage by being the only player in the market, thus having the ease of use, as they will not need to use aggressive discounts and to share the market with your competitors. Over the last century the demographics have changed dramatically; as about 20% of Japans 127 million people are 65 and older, and the number is expected to rise to almost 26% by 20158. This has added to the success of Nintendo, as without integrating the various elements of the Marketing Process they would not have been able to find this gap and sell millions of their products to segments which have been largely excluded. Another benefit of targeting the older demographics is very profitable segment as they have a higher purchasing power than teenagers and what is more important about this segment is that they are less likely to get pirate games. Nintendo success also lies in their use of differentiated targeting strategy. This is when one or more products are developed for several customer groups, this is extremely important for Nintendo as their customers are choosing amongst brands that are well known. Nintendo has chosen to position itself as a kid friendly brand to build strong relationships with the gamers as well as the parents. For example Nintendo’s approach to selling its new Wii games console, their guests were working women with families. These were women with a big say in the family decision-making, who could be persuaded of the family-friendly advantages of the games. 9 This illustrates that Nintendo have taken in to consideration the changes in our society where there is an increasing influence of mothers decision on family purchases. Figure 2. 3 Having this perception of the company is useful as it’s mainly the parents who purchase games for their children; as a result parents are more likely to buy products that are suitable for the whole family. This is incredibly important to modern marketing, as one of the functions of modern marketing is to ensure that your products improve both societies and customers well being. This is emphasised by the societal marketing process: The model argues that the pure marketing concept overlooks possible conflicts between short-term consumer wants and long-term individual and societal welfare. Figure 2. 410 Nintendo has recognised their responsibility and by offering educational and non-violent games thus, they can project a good image of the company, and thus gain a competitive advantage over their competitors, for example Grand Theft Auto has been widely criticised for being too violent. Furthermore, Nintendo uses various positioning strategies such as emphasising their product attributes and benefits offered, by allowing people to exercise their mind and body, to stay young and healthy. This also benefits the society, as the population of the UK is increasingly becoming over weight, therefore this allows people to have fun and loose weight. This integration of their marketing strategies helps keep their title for being the dominators of handheld gaming for kids, and also allow them to be market leaders in the future for products aimed at the female market segment. The third process of the marketing process is developing the ‘marketing mix’ which consists of the 4 P’s. This is everything a firm does to influence customers to purchase their products. Product Products are anything that is offered to the market for acquisition, use or consumption which may satisfy a need or want. 11 There are three levels of a product, and a company needs to ensure that needs are met on each of these levels. I will use the Wii as an example to illustrate how Nintendo meet the needs on each level. Figure 3. 0 Core product: The core benefits that consumers are really buying when they obtain a product. The core product is not the tangible, physical product as this is the benefit of the product that makes it valuable to you. For example the ease of use such as Wii sports allows women, children and seniors to take part, as games such as bowling only takes minutes to master. The wireless controller of the Wii allows users feel as if though they are actually playing the game. Although the Wii doesnt boast all the features and processing firepower of its rivals, its easy-to-use controller will gives it an edge. Actual Product: A products parts, quality level, features, design, brand ame, packaging and other attributes that combine to deliver core product benefits. Nintendo Wii is an actual product. Its name, parts, styling, features, packaging and other attributes have all been combined carefully to deliver the core benefit, which is a convenient and unique social gaming experience for the whole family. One of the main elements of the actual product is the branding. A brand is defined a s a name, term, symbol or design, or a combination of these, intended to identify the goods or services of one seller or group of sellers and to differentiate them from the competitors12. Branding is a vital part of a product, and it can be used as a differentiating, functional legal and symbolic device, it shows sign of ownership and can also be used as a risk reducer. Branding is especially important in the case of Nintendo, as they need to differentiate themselves from the competitors. Having a strong brand will allow them to create a unique position in the market as customers will believe that only they can provide certain benefits as a result customers will be willing to pay premium and refuse substitutes. Augmented Products: Additional consumer services and benefits built around the core and actual products. The Wii case it comes with consumer warranty, online support and help around the clock along with a free support number. In addition by being an international brand in a global market they are able to standardise their products and ‘sell in all national markets the same kind of products sold at home, or in their largest export market. ’ 13 this allows for Nintendo to keep the prices of their consoles low as they do not have to change and adapt their offerings every time they enter a new market. Price Price is the value customers give up or exchange to obtain a desired product. Pricing is important to marketing, as it is the only part of the marketing mix that brings in profit for the company. Nintendo’s products are innovative and provide benefits that competitors can not provide, therefore there are two pricing strategy they can take: Market skimming: using a high price, where there is uniqueness about the product over competition in order to generate maximum profit. Market Penetration: where Prices are initially set low, in order to gain market share. Figure 3. 1 Nintendo has used penetration pricing, as it has priced the Wii nearly ? 100 pound cheaper than it rival Playstation3. It has been able to do by having no HD, no DVD, no Dolby 5. 1, low processor speed compared to the Playstaion3, however, by having a strong value for innovation they have ensured that they do not loose out on sales. Promotion This is how the product is communicated to potential and existing customers. Marketing communication can take many forms from television commercials to blinking messages in football stadiums. Therefore it is essential that all part of the marketing communication to be integrated through a well co-ordinated marketing promotional programme. 14 This is essential as it ensures that a consistent, persuasive and unified message is projected to the customer. In order to ensure that effective communication can be carried out, a company must have a clear target audience, decide on which response is sought and determine which stage of the buyer readiness stage the consumer is at. Figure 4. 0 the Buyer readiness Stages. Awareness is when the communicator needs to build up awareness of the product through simple name recognition method so that customers will purchase the products. Nintendo created awareness designing an innovative Digital poster which is controlled and updated from Nintendo’s Head Office. 15 The technology allows for new promotional messages to be delivered to all stores remotely and in less than 10 seconds. This has allowed Nintendo to send a unified message to all customers and thus ensuring that their strategies are integrated. This shows that Nintendo have truly embraced the revolutionary impact of the internet as a result they are able to re-act quickly to competitive campaign and unforeseeable events, furthermore thy can re-enforce brand messages at the point of purchase to increase awareness and influence buying decisions. Other promotional strategies Nintendo use is the pull and push strategy. Figure 4. 1 Nintendos uses the push strategy to promote its products; this is where higher profit margins for retailers are used to encourage stores to promote a certain product. Nintendo will use celebrities such as Nicole Kidman to advertise their products, thus developing an attitude amongst its target audience that the product is a fashion statement or a lifestyle alternative; as a result this product has become desirable amongst its customers. Stores can push products by displaying the Wii more prominently on shelves and putting up special demo kiosks and supplementary display materials (as shown below). Wii displayed prominently in retail out-let. Demo kiosk of the Wii in retail out-let. However, Nintendo also use the pull strategy whereby the idea is to make the product seem more desirable to consumers first, through massive advertising and promotion by the manufacturer, which will then translate into customers going into the store and demanding that product Figure 4. 2 This strategy was used for the Wii as they are struggling to meet consumer demand for the Wii as the console continues to sell out at retail just as quickly as it arrives. 16 As a result customers will be demanding for the retailer to stock the Wii. Place The final element of the mix is Place. This is the distribution channel/ method the firm uses to make their products available to the final customer. It is critical for firms to be able to manage their distribution cannel as it ensure that products and services are delivered at the right time, right place and the right price. Most businesses use intermediaries to bring their products to market as Producers normally supply a narrow range of products in large quantities; however Consumers want a broad range of products in small quantities. In the marketing channels, intermediaries buy large quantities from many manufacturers and break them down into smaller quantities and broader assortments wanted by consumer, in order to match supply and demand. Figure 5. 0 Channel 1 is called a direct-marketing channel, since it has no intermediary levels. In this case the manufacturer sells directly to customers. For example Nintendo selling their products to the final customer through their website. The remaining channels are indirect-marketing channels. For example in channel 2 it contains one intermediary (retailer). An example of this is Nintendo selling to large retailers such as Curry’s and Dixons, who then sells it to the final customer. The final stage of the marketing process is implementation and control. This occurs after the marketing plan has been completed and the product has been launched and offered to the market. The company takes feedback of the product form customers and by making a competitor marketing analysis. As result the marketing mix can be adjusted if needed to maintain or sustain competitive advantage. Nintendo are constantly respond to what their consumers are saying about their products, furthermore they have frequently asked questions section and advice pages on their website, thus providing personal relationships with their consumers. Marketing in the 21st century Changes in technology have revolutionised marketing, due to the rise of E-business/marketing/commerce, globalisation and social groups. As a result a new marketing is needed for a new kind of society. This has created the notion of relationship marketing where companies are using he internet to tailor products as closely as possible to each individual’s unique needs. Relationship marketing views ‘the consumer as a highly active agent’ unlike the traditional approach which perceives the consumer as ‘passive and receptive object’. 17 . Nintendo have embraced these changes and changed the ways in the way they sell their products, ranging from internet to retail stores, whilst constantly updating their website to keep customers informed. Nintendo have embracing the changes the changes in the marketing environment and trying to build a long-term relationship with customers. For example Nintendo are planning to allow the Wii to stay connected to the Internet in a mode that allows activation on a 24-hour basis form Nintendo. This would allow Nintendo to send monthly promotional demos for the DS, to the Wii consoles in each household. The key merit here is having promotional material delivered to our homes, instead of having to go collect it themselves and it also keeps the company and the customer connected. In conclusion, it is evident that marketing is essential for success in the 21st century where our society culture and values are changing very fast. Marketing allows for a business to understand consumers, and it allows for the company to get feedback so they can understand who and why consumers reject or accept your product. Marketing allows for a business to understand that in the 21st century building relationships outside the sales context is crucial. Giving customers the capability to relate with you as a brand, rather than a business, will offer opportunities to bring those customers close, but to get the most value out of this it is crucial that each customer can direct and define their communications with you.

How to Talk About Your Family in Italian

How to Talk About Your Family in Italian While Italians are passionate about a lot of things- food, calcio, fashion, to name a few- family is one of the most important. Since it is such an essential part of Italian culture, you’re  going to be asked about your family when you start to chat with natives, and it’s a great conversation starter. So what specific vocabulary words do you need to know, and which phrases will help the conversation flow smoothly? Basic Vocabulary - Family Members aunt la zia boy il ragazzo brother il fratello brotherinlaw il cognato cousin (female) la cugina cousin (male) il cugino daughter la figlia daughterinlaw la nuora family la famiglia father il padre fatherinlaw il suocero girl la ragazza grandchild il nipote granddaughter la nipote grandfather il nonno grandmother la nonna grandparents i nonni grandson il nipote husband il marito mother la madre motherinlaw la suocera nephew il nipote niece la nipote parents i genitori relative il parente sister la sorella sisterinlaw la cognata son il figlio soninlaw il genero stepfather il patrigno stepmother la matrigna step brother; half brother il fratellastro step sister; half sister la sorellastra uncle lo zio wife la moglie Conversational Phrases A casa tutto bene? - Is everything good at home?A casa here is used as in a figurative way to mean, â€Å"family†.​   Another option is to ask: Come sta la sua famiglia? - How is your family? If you want to ask informally, you can say, â€Å"Come sta la tua famiglia?† Come stanno i suoi? - How are your (parents)? If you want to ask informally, you can say, â€Å"Come stanno i tuoi?† FUN FACT: Italians shorten â€Å"i tuoi genitori† to â€Å"i tuoi†, so you can say â€Å"i miei† instead of â€Å"i miei genitori† and sound  more Italian. Ha fratelli o sorelle? - Do you have brothers or sisters? If you want to ask informally, you can say, â€Å"Hai fratelli o sorelle? Ha dei figli? - Do you have any kids? If you want to ask informally, you can say, â€Å"Hai dei figli?† Ho due maschi e una femmina. - I have two boys and one girl.Si chiama†¦ - His/her name is...Hai una famiglia numerosa! - You have a big family!Sono figlio unico. - I’m an only child. (male)Sono figlia unica. - I’m an only child. (female)Lei à ¨ sposato/a? - Are you married? If you want to ask informally, you can say, â€Å"Sei sposato/a?†. Use â€Å"sposato†, ending in -o, if you’re asking a male. Use â€Å"sposata,† ending in -a, if you’re asking a female. La mia famiglia viene dalla (Sardegna). - My family is from (Sardegna).Mio figlio si à ¨ appena laureato! - My son just graduated!Vado a trovare la mia famiglia (in Calabria). - I’m going to visit my family (in Calabria).Che lavoro fa (tuo marito)? - What does your husband do for work?Mia madre fa (l’insegnante). - My mother is a (teacher).Dove abita? - Where does he/she live?Le presento (mio marito). -   Let me introduce my husband to you. If you want to say this informally, you can say, â€Å"Ti presento (mia moglie)†. Mi saluti sua moglie! - Say hello to your wife for me! If you want to say this informally, you can say, â€Å"Salutami (tua moglie)!†. Practice Dialogue The best way to learn the language is to see the phrases and the vocabulary in action, so below you’ll find a practice dialogue between two friends who have run into each other on the street. Person 1: Ciao! Come stai? - Hey! How are you?Person 2: Sto bene, e tu? - I’m doing well, and you?Person 1: Tutto a posto, come sta la tua famiglia? - Everything is good, how is your family?Person 2: Sta bene, mia figlia si à ¨ appena laureata! - They are good, my daughter just graduated!Person 1: Complimenti!! E tuo marito? - Congratulations!! And your husband?Person 2: Lavora moltissimo, ma andr in pensione fra un anno. E tua figlia? - He’s working a lot, but he’ll be retiring in a year. And your daughter?Person 1: Giulia? La settimana scorsa ha compiuto sedici anni. - Giulia? Last week she turned 16 years old.Person 2: Davvero? Lei à ¨ cresciuta troppo in fretta! - Really? She grew up too fast!Person 1: Lo so, à ¨ cosà ¬. Allora, devo andare, à ¨ stato bello vederti, a presto! - I know, that’s how it is. Well, I’ve got to go, it was great to see, talk soon!Person 2: A presto! - Talk soon!

6 Tips to Boost Your Energy Levels While Writing a Paper

6 Tips to Boost Your Energy Levels While Writing a Paper 6 Tips to Boost Your Energy Levels While Writing a Paper One nationwide study found almost 40% of respondents admitting that workplace fatigue impacts negatively on their productivity. This is just as much a problem for college students as elsewhere, so it’s important to keep your energy levels high when writing a paper. There are lots of ways you can do this, including both quick-fixes and longer-term solutions. 1. Fuel Up Make sure to give your body the fuel it needs. While writing, this might include having snacks and a drink to hand as well as stopping to eat regular meals. More generally, eating a healthy, balanced diet can improve your overall energy levels. It’s also important to drink plenty of water during the day, not just coffee! 2. Have a Plan As well as planning your essay to ensure efficiency, having a regular work routine and taking a structured approach to the day can boost productivity in the long run. 3. Soak Up Some Sunshine Spending too much time indoors can leave you drained, partly due to a lack of vitamin D. Exposure to natural sunlight boosts your body’s vitamin D production, so getting outside regularly can help if you’re feeling run down. If youre not sure how to sunbathe, just copy this lemur. 4. Get Active Even in the short-term, getting up and going for a walk is a great way of refreshing if you’re struggling for energy while writing a paper. In the long-term, regular exercise has been shown to increase energy levels and reduce vulnerability to fatigue, so staying active will ensure you’re always at your best. 5. De-Stress Another common reason we feel run down is stress, which can lead to physical and mental exhaustion. It’s therefore important to know the symptoms of stress, as then you can take action before it affects your productivity. 6. Rest Easy (And Well) The amount of sleep you get also influences your energy levels and you may struggle to concentrate on your work if you don’t get enough. Eating healthily and exercising regularly will help, as will foregoing caffeine and electronic products (TV, computers, phones, etc.) immediately before bed. On another note, napping has been shown to enhance energy levels and concentration among students. So, if all else fails, a quick snooze may be just what the doctor ordered!