One of the challenges of running an analytics company like ours, where we’re dealing with terabytes of big data, is managing the horsepower required to crunch such enormous volumes of data in real-time and deliver it in a simple and easy to use interface that makes business sense to our users.
To help, we’ve partnered with Google as one of the early users of Google BigQuery, a web service that enables us to do interactive analysis of massively large datasets. The service enables us to process billions of rows of social and mobile game events data in mere seconds.
BigQuerywas initially developed as an internal tool to help the company process its own data more efficiently, and it was launched at last year’s Google I/O conference after they realized it would be useful for other companies in need of big data analytics as well. The premise is that using SQL-like commands via a RESTful API, you can do things like quickly explore and understand massive historical datasets, analyze network logs, identify seasonal sales trends, or, as in our case, analyze billions of social app events taking place every minute.
Earlier this week, Google announced some big improvements to the BigQuery service, making it even more powerful and easier to use. As posted on the Google Developer blog, they’ve made updates such as:
A few of the above changes are very important for us to address some really advanced use cases around real time campaign, ads and user engagement analytics – that further contribute to near immediate closed loop actionability for social and mobile games. Extremely important for all those publishers who want to be the next Zynga in the mobile space!
BigQuery is currently available by invitation-only to a limited number of enterprises and developers, and we are honored to be among those testing it out. We can unequivocally say that we’ve been very impressed, and that the service has been integral in helping us deliver the real-time data and actionable insights that our customers have come to expect from us.
The Claritics blog offers insights and analysis on the rising social commerce wave and how app developers can leverage social intelligence for their Reach, Retention and Revenue campaigns.