How EMC Uses Big Data to Deliver Value to the Business

Harnessing Big Data is an important strategy for all companies in today’s information-driven world. But where do you begin in choosing a project to utilize this vast resource effectively?

Much has been written about the three Vs of Big Data – Volume, Velocity and Variety. But the unsaid fourth V – Value – is the one where we have to direct our focus. It only makes sense to start where Big Data analytics will have a big impact right away. At EMC, we have seen that there are at least three types of use cases to consider — those involving business data (customer data, product data, quotes and orders, financial data), data center data (events from networks, storage, servers, applications) or security (events from firewalls, IDS, antivirus, etc.). Chances are, like EMC, your company has already taken steps to consolidate your data and found that traditional data stores or standard analytics tools still do not provide the agility that you need.

At EMC, for our first Big Data use case, we chose to focus on the business side of the house in a project to bolster our Customer Quality (CQ) effort. This is a critical focus that touches on all aspects of our business. Utilizing Big Data analytics here promised to be an early and substantial win.

The CQ team tracks quality and analyzes performance data, including information on data availability sent back to EMC from all hardware installed in customer environments via a dial-home system. We use this data, along with customer surveys, to help gauge customer satisfaction.

Leveraging EMC’s Greenplum Unified Analytics Platform for data quality provided both the technology to quickly load incoming data and the tools to generate reports in near real-time. The results were undeniably fantastic. The CQ team can now load millions of dial-home records generated in a span of minutes vs. the four to six days that it used to take. They can also produce reports they need on demand and pursue questions and shape reports to meet their specific needs like never before.

What’s more, we have built on this experience to offer Business-Analytics-as-a-Service (BAaaS), a model we recently introduced to allow business units to work in their own analytics workspace with information from our data warehouse and other sources to pursue research questions they never could before.

While this project has really shown the power of Big Data, it is only the beginning of our journey to leverage the benefits of Big Data analytics and BAaaS. We have also made significant progress in predicting certain types of failure events within the data center hours before they happen and in dealing with security threats. With the help of data science we expect to unlock the predictive value of our data to hone our business strategy for the future.

About the Author: KK Krishnakumar