Actionable Insights From APT's Financial Services Practice
Header

Solving Big Data Challenges

November 1st, 2013 | Posted by JDouglass in Financial Services

In a recent Wall Street Journal article, Dr. Jordan of Penn State’s Smeal College of Business, discusses the challenges of Big Data for companies. APT’s software suite has been designed to solve many of the challenges outlined in the article, as evidenced by the more than 100 leading organizations that leverage APT daily.

“These are great tools, but who has the skills to use them?”

This article suggests that companies must hire “Big Data experts” to use specialized Big Data tools. APT is designed for use by business analysts. It takes only a few hours of training, and doesn’t require an advanced degree in Computer Science or Statistics. The article gets one aspect absolutely right when it suggests that for Big Data to be useful, analysts must understand the industry. While APT has gained a deep understanding of each of the industries in which it serves, we believe that institutionalizing a Big Data analytics process within the organization and empowering internal users always yields better results than outsourcing analysis to vendors with black box solutions.

“What do we do with all these numbers?”

We agree that standard spreadsheets can’t scale to make sense of Big Data. However, the answer to “what do we do with all these numbers?” is clearer. APT focuses on helping banking executives make decisions that will drive significant bottom line improvements. The outputs of APT are designed to answer three key questions to help make more profitable decisions: 1) Will our new idea work? 2) Will it work better in some situations than others? And, 3) How can we tailor and target a rollout for maximum profitability going forward?

To learn more about how APT continues to solve the Big Data challenge, click here to read a Forbes article written by APT’s Chairman, Jim Manzi. And click here to watch a video of APT’s CEO, Anthony Bruce, discussing testing’s role in Big Data.

Be Sociable, Share!

You can follow any responses to this entry through the RSS 2.0 Both comments and pings are currently closed.