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In Building a Culture of Big Data, Zynga Grabs Huge Volumes and Makes the Analytics Open to All Employees to Pursue an Innovation Edge

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Transcript of a Briefings Direct discussion on how gaming companies can gain a competitive advantage in grabbing and analyzing data in near real time.

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In Building a Culture of Big Data, Zynga Grabs Huge Volumes and Makes the Analytics Open to All Employees to Pursue an Innovation Edge

  1. 1. In Building a Culture of Big Data, Zynga Grabs Huge Volumes and Makes the Analytics Open to All Employees to Pursue an Innovation Edge Transcript of a Briefings Direct podcast on how gaming companies can gain a competitive advantage in grabbing and analyzing data in near real time.   Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator for this ongoing sponsored discussion on IT innovation and how it’s making an impact on people’s lives. Once again, we're focusing on how companies are adapting to the new style of IT to improve IT performance and deliver better user experiences, as well as better business results. We're here to learn directly from IT and business leaders alike how big data, cloud, and converged infrastructure implementations are supporting their goals. Our next innovation case study interview highlights how Zynga in San Francisco is depending on big-data analytics to improve how it does its business and provide its gaming services to its customers. Become a member of myVertica today Register now Gain access to the free HP Vertica Community Edition To learn more about how big data impacts Zynga in the gaming industry, please join me now in welcoming our guest. We're here with Joanne Ho, a Senior Engineering Manager at Zynga. Welcome, Joanne. Joanne Ho: Hi. Gardner: And also, Yuko Yamazaki, Head of Analytics at Zynga. Welcome, Yuko. Yuko Yamazaki: Thank you. Gardner: Let’s start with you, Joanne. Tell us a little bit about what Zynga needs to do with big data in order to improve your business. How important is big data analytics to you as an organization? Gardner
  2. 2. Ho: To Zynga, big data is very important. It's a main piece of the company and as a part of the analytics department, big data is serving the entire company as a source of understanding our users' behavior, our players, what they like, and what they don’t like about games. We are using this data to analyze the user’s behavior and we also will personalize a lot of different game models that fit the user’s player pattern. Gardner: What’s interesting to me about games is the people will download them. They're also upgradable and they are changeable. People can move so that the feedback loop between the inferences, information, and analysis you gain, and then what you can do with it is rather compressed, compared to many other industries. What is it that you're able to do in this rapid-fire development and in release? How is that responsiveness important to you? Real-time analysis Ho: Real-time analysis, of course, is critical, and we have our streaming system that can do it. We have our monitoring and alerting system that can alert us whenever we see any drops in user’s install rating, or any daily active users (DAU). The game studio will be alerted and they will take appropriate action on that. Gardner: Yuko, what sort of datasets we are talking about? If we're going to the social realm, we can get some very large datasets or you might have actual data that’s coming directly from your apps. What's the volume and scale we're talking about here? Yamazaki: We get data of everything that happens in our games. Almost every single play gets tracked into our system. We're talking about 40 billion to 60 billion rows a day, and that's the data that our game product managers and development engineers decide what they want to analyze later. So it’s already being structured and compressed and comes into our database. Gardner: That’s a very impressive scale. Is there a visualization approach? It’s one thing to have a lot of data, but it’s another to be able to make that actionable. What do you do once that data is assembled and you've got the analysis underway? Yamazaki: The biggest success story that I will normally tell about Zynga is that we make data available to all employees. From day one, as soon as you join Zynga, you get to see all the data through our visualization to whatever we have. Even if you're FarmVille product manager, you get to see what Poker is doing, making it more transparent. There is an account report that you can just click and see how many people have done this particular game action, for example. That’s how we were able to create this data-driven culture for the Zynga. Gardner: And Zynga is not all that old. Is this data capability something that Ho Yamazaki
  3. 3. you’ve had right from the start, or did you come into it over time? I suppose the question is how early on in your organization did this data imperative become clear? Yamazaki: Our analytics has been going on since the beginning. Our cluster scaled 70 times since then. Ho: It started off with three nodes, and we've grown to 230 node clusters. Gardner: So you're performing the gathering of the data and analysis in your own data centers? Yamazaki: Yes. Gardner: When you realized the scale and the nature of your task, what were some of the top requirements you had for your cluster, your database, and your analytics engine. How did you make some technology choices? Biggest points Yamazaki: When Zynga was growing, our main focus was to build something that was going to be able to scale and provide the data as fast as possible. Those were the two biggest points that we had in mind when we decided to create our analytics infrastructure. Gardner: And any other more detailed requirements in terms of the type of database or the type of analytics engine? Become a member of myVertica today Register now Gain access to the free HP Vertica Community Edition Yamazaki: Those are two big ones. As I mentioned, we wanted to have everyone be able to access the data. So SQL would have been a great technology to have. It’s easy to train PMs instead of engineering sites, for example, MapReduce for Hadoop. Those were the three key points as we selected our database. Gardner: What are you hearing from HP that’s of interest? Are there future directions and requirements that you have? Are there things that you’d like to see from HP in order to continue to be able do what you do at increasing scale? Ho: We're interested in real-time analytics. There's a function aggregated projection that we're interested in trying. Also FlexTable sounds like a very interesting feature that we also will attempt to try. And cloud analytics is the third one that we're also interested in. We hope HP will get it matured, so that we can also test it out in the future.
  4. 4. Gardner: While your analytics has been with you right from the start, you were very early in the Vertica ecosystem? Ho: Yes. Gardner: So now we've determined how important it is, do you have any metrics of what this is able to do for you? Other organizations might be saying they we don't have as much of a data- driven culture as Zynga, but would like to and they realize that the technology can now ramp-up to such incredible volume and velocity, What do you get back? How do you measure the success when you do big-data analytics correctly? Yamazaki: Internally, we look at adoption of systems. We we have 2,000 employees, and  at least 1,000 are using our visualization tool on a daily basis. This is the way to measure adoption of our systems internally. Externally, the biggest metric is retention. Are players coming back and, if so, was that through the data that we collect? Were we able to do personalization so that they're coming back because of the experience they've had? Gardner: These are very important to your business, obviously, and it’s curious about that buy- in. As the saying goes, you can lead a horse to water, but you can't make him drink. You can provide data analysis and visualization to the employees, but if they don’t find it useful and impactful, they won’t use it. So that’s interesting with that as a key performance indicator for you. Any words of advice for other organizations who are trying to become more data-driven, to use analytics more strategically? Is this about people, process, culture, technology, all the above? What advice might you have for those seeking to better avail themselves of big data analytics? Visualization Yamazaki: A couple of things. One is to provide end to end. So not just data storage, but also visualization. We also have an experimentation system, where I think we have about 400-600 experiments running as we speak. We have a report that shows you run this experiment, all these metrics have been moved because of your experiment, and A is better than B. We run this other experiment, and there's a visualization you can use to see that data. So providing that end-to-end data and analytics to all employees is one of the biggest pieces of advice I would provide to any companies. One more thing is try to get one good win. If you focus too much on technology or scalability, you might be building a battleship, when you actually don’t need it yet. It's incremental. Improvement is probably going to take you to a place that you need to get to. Just try to get a
  5. 5. good big win of increasing installs or active users in one particular game or product and see where it goes. Gardner: And just to revisit the idea that you've got so many employees and so many innovations going on, how do you encourage your employees to interact with the data? Do you give them total flexibility in terms of experiments? How do they start the process of some of those proof-of-concept type of activities? Yamazaki: It's all freestyle. They can log whatever they want. They can see whatever they want, except revenue type of data, and they can create any experiments they want. Her team owns this part, but we also make the data available. Some of the games can hit real time. We can do that real-time personalization using that data that you logged. It’s almost 360-degree of the data availability to our product teams. Gardner: It’s really impressive that there's so much of this data mentality ingrained in the company, from the start and also across all the employees, so that’s very interesting. How do you see that in terms of your competitive edge? Do you think the other gaming companies are doing the same thing? Do you have an advantage that you've created a data culture? Yamazaki: Definitely, in online gaming, you have to have big data to succeed. A lot of companies, though, are just getting whatever they can, then structure it, and make it analyzable. One of the things that we've done that do well was to make a structure to start with. So the data is already structured. Product managers are already thinking about what they want to analyze before hand. It's not like they just get everything in and then see what happens. They think right away about, "Is this analyzable? is this something we want to store?" We're a lot smarter about what we want to store. Costwise, it's a lot more optimized. Gardner: Great. We'll have to leave it there. We have been hearing about how Zynga in San Francisco has, right from its inspection, created a very strong culture around big data and grabs as much as they can from the volumes and then makes the results of that data acquisition available across the board to its employees. Become a member of myVertica today Register now Gain access to the free HP Vertica Community Edition I'd like to thank our guests. We've been joined by Joanne Ho, Senior Engineering Manager at Zynga. Thank you, Joanne. Ho: You’re welcome. Gardner: And also Yuko Yamazaki, Head of Analytics at Zynga. Thank you, Yuko. Yamazaki: Thank you.
  6. 6. Gardner: And a big thank you to our audience as well, for joining us for this special new style of IT discussion. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP sponsored discussions. Thanks again for listening, and come back next time. Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP Transcript of a Briefings Direct podcast on how gaming companies can gain a competitive advantage in grabbing and analyzing data in near real time. Copyright Interarbor Solutions, LLC, 2005-2015. All rights reserved. You may also be interested in: • How Waste Management Builds a Powerful Services Contiunuum Across Operations, Infrastructure, Development, and IT Processes • GSN Games hits top prize using big data to uncover deep insights into gamer preferences • Hybrid cloud models demand more infrastructure standardization, says global service provider Steria • Service providers gain new levels of actionable customer intelligence from big data analytics • How UK data solutions developer Systems Mechanics uses HP Vertica for BI, streaming and data analysis • Advanced cloud service automation eases application delivery for global service provider NNIT • HP network management heightens performance while reducing total costs for Nordic telco TDC • How Capgemini's UK financial services unit helps clients manage risk using big data analysis • Perfecto Mobile goes to cloud-based testing so developers can build the best apps faster • Software security pays off: How Heartland Payment Systems gains steep ROI via software assurance tools and methods • HP ART documentation and readiness tools bring better user experiences to Nordic IT solutions provider EVRY

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