Unlocking the Value of Real-Time Analytics

Chapter 5. Case Studies

We have looked at the benefits of a bitmap index combined with columnar data, but how well does it work? What companies have incorporated this method, and what benefits have they seen? In this next chapter, we will examine some companies that use columnar data, sharding, and bitmap indexing to store and analyze their data. We will see how the changes made an impact and how they have improved productivity as a result.

Case Study I: Technology-Driven Video Advertising

A global leader in cable and video advertising collects data from more than six billion devices. This data is accurate, rich, and valuable as part of its strategy for providing customized, targeted advertising. The problem was that this data was huge, and the resources required to provide near-real-time targeted advertising were immense. To meet the need, the company established several hundred Hadoop servers and used them to batch process and pre-aggregate the data. Still, with this huge investment in hardware and tools, the process took one to three days to send a targeted ad to a customer.

Solution

The company needed a solution that could handle the huge amounts of data inflowing into its system while also being able to query at near-instantaneous speeds. It contacted several technology providers to find a solution that met the throughput and latency it demanded. In the end, the company implemented a solution that combined the four requirements of real-time analytics. The results were incredible: ...