Subscribe / Unsubscribe Enewsletters | Login | Register

Pencil Banner

A quest for big data discovery

Terry Smagh | June 18, 2013
The volume of digital information is expected to nearly double every two years between today and 2020, reaching 40 trillion gigabytes, in just seven years according to analyst firm IDC.

To put it into perspective, I can illustrate this idea by pointing to the case of, best known as the founder of Candy Crush Saga. is a global leader in casual social games and offers over 150 exclusive games in 14 languages to over 40 million monthly players and more than 3 billion games played per month worldwide. uses a Hadoop-based big data solution to store massive amounts of gaming activity and customer data. Hive is leveraged as a data warehouse system for Hadoop to run ad-hoc queries, and the analysis of large datasets. Each user's 'event' is first logged locally on the game servers and then the information is copied hourly to a centralized log server and subsequently logged in a Hadoop before the magic of business analytics even begins.

The social gaming giant wanted to extract data from a variety of sources and customize metadata to be applied as external tables from different sources and be used with big data extracted from the Hadoop system. Built-in associative search data models and capability extract and merge data from different data sources helps's BI team become a metadata driven business intelligence unit.

Making data discovery possible's gaming system generates 2 billion rows of data per day and this volume continues to grow. Analyzing data without disturbing the game load was a key performance requirement for the company. Another requirement was to have a simplistic analytics and reporting system that allows game development teams to be geographically separate from the platform development. Finally, as its business grows, the requirements for analytics were more sophisticated than ever. Having the data available for complex queries and analytics with fast performance was a necessity.'s IT department was challenged to empower business users with self-service analytics and give them a gaming experience that will keep them coming back for more. Business users from different job functions wanted to explore the data relevant to their job, and able to slice and dice the data by many permutations of the hundreds of dimensions available in the big data.

By giving business users more control, they have more freedom to navigate and analyze their data, not a pre-determined data set that traditional BI delivers. Gartner researchers call this new category of BI 'Data Discovery' — we call it 'Business Discovery'.

The solution also provided 'speed of thought' analysis of's big data. Since all the data needed for analysis is in memory, business users can explore a relevant piece of big data immediately. Zero wait time as user-driven BI performs the calculations needed to deliver the analysis users request. More importantly, they can literally see relationships in the big data with the unique associative search capability and leverage all of the dimensions of the big data with any combinations during analysis. With a user-driven BI environment, can now analyze 40 million customers' gaming behavior to target new games and customers.


Previous Page  1  2  3  Next Page 

Sign up for CIO Asia eNewsletters.