Making Good Things Happen at Wells Fargo
In conjunction with MapR, Datanami presents Wells Fargo with this month’s “Big Data All Star” award.
When Paul Cao joined Wells Fargo several years ago, his timing was perfect. Big Data analytic technology had just made a major leap forward, providing him with the tools he needed to implement an ambitious program designed to meet the company’s analytic needs.
Wells Fargo is big – a nationwide, community-based financial services company with $1.8 trillion in assets. It provides its various services through 8,700 locations as well as on the Internet and through mobile apps. The company has some 265,000 employees and offices in 36 countries. They generate a lot of data.
Cao has been working with data for twenty years. Now, as the Director of Data Services for Wells Fargo’s Capital Markets business, he is creating systems that support the Business Intelligence and analytic needs of its far-flung operations.
“We receive massive amounts of data from a variety of different systems, covering all types of securities (equity, fixed income, FX, etc.) from around the world,” Cao says. “Many of our models reflect the interactions between these systems – it’s multi-layered. The analytic solutions we offer are not only driven by customers’ needs, but by regulatory considerations as well.
“We serve the company’s data needs across the entire banking business and so we work with a variety of data types including reference data, market data, structured and unstructured data, all under the same umbrella,” he continues. “Because of the broad scope of the data we are dealing with, we needed tools that could handle the volume, speed and variety of data as well as all the requirements that had to be met in order to process that data. Just one example is market tick data. For North American cash equities, we are dealing with up to three million ticks per second, a huge amount of data that includes all the different price points for the various equity stocks and the movement of those stocks.”
Cao says that given his experience with various Big Data solutions in the past and the recent revolution in the technology, he and his team were well aware of the limitations of more traditional relational databases. So they concentrated their attention on solutions that support NoSQL and Hadoop. They wanted to deal with vendors like MapR that could provide commercial support for the Hadoop distribution rather than relying on open source channels. The vendors had to meet criteria such as their ability to provide utmost in security, ease of ingest, ability to scale, high performance, and – particularly important for Wells Fargo – multi-tenancy.
Cao explains that he is partnering with the Wells Fargo Enterprise Data & Analytics and Enterprise Technology Infrastructure teams to develop a platform servicing many different kinds of capital markets related data– including files of all sizes and real time and batch data from a variety of sources within Well Fargo. Multi-tenancy is a must to cost-efficiently and securely share IT resources and allow different business lines, data providers and data consumer applications to coexist on the same cluster with true job isolation and customized security. The MapR solution, for example, provides powerful features to logically partition a physical cluster to provide separate administrative control, data placement, job execution and network access.
“The new technology we are introducing is not an incremental change – this is a dramatic change in the way we are handling data,” Cao says. “Among our challenges is to get users to accept working with the new Hadoop and NoSQL infrastructure, which is so different from what they were used to. Within Data Services, we have been fortunate to have people who not only know the new technology, but really know the business. This domain expertise is essential to an understanding of how to deploy and apply the new technologies to solve essential business problems and work successfully with our users.”
When asked what advice he would pass on to others working with Big Data, Cao reiterates his emphasis on gaining a solid understanding of the new technologies along with a comprehensive knowledge of their business domain.
“This allows you to marry business and technology to solve business problems,” he concludes. “You’ll be able to understand your users concerns and work with them to make good things happen.”