Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Optimizing the data warehouse at Visa

Nandu Jayakumar (Visa), Ewa Ding (Cloudera)
2:05pm2:45pm Wednesday, September 27, 2017
Enterprise adoption, Strata Business Summit
Location: 1A 18 Level: Intermediate
Secondary topics:  Financial services, Platform

Who is this presentation for?

Architects, IT Managers, C-Level

Prerequisite knowledge

- A general understanding of traditional data warehousing, big data platforms, and BI (and how they are implemented at enterprises) - Familiarity with SQL and the workflows of typical data analysts at enterprises

What you'll learn

- Gain insight into how Visa is optimizing their data warehouse landscape with Hadoop - Understand how to develop an offload strategy and best practices for offloads

Description

As it relates to the topic of big data and technologies such as Hadoop, there tends to be a lot of talk around enabling the next-generation use cases or advanced analytics. While those applications should play a role in any enterprise’s data strategy, much of the initial value and benefits of a modern data platform can often come from simply offloading the analytic workloads you’re running today. However, where do you start when developing an offload strategy? Which workloads are better suited for Hadoop? And how do you offload complex analytic workloads?

At Visa, this process of optimizing the enterprise data warehouse and consolidating data marts by migrating these analytic workloads to Hadoop has played a key role in the adoption of the platform and how data has transformed Visa as an organization. During this talk, Nandu (Visa) and Ewa (Cloudera) will look at Visa’s experience optimizing their data warehouse landscape by moving to Hadoop and provide some best practices and guidance for organizations looking to migrate workloads to Hadoop.

In particular, Nandu will discuss Visa’s approach to bringing Hadoop into their business, their offload strategy, and lessons learned from the experience. In addition, he will also discuss how they’re using new technologies to help better understand the legacy workloads running today and prioritize migrations to continue to alleviate costs and pressures on these systems. Finally, he will showcase the successes thus far and look at what’s in store for the future.

Photo of Nandu Jayakumar

Nandu Jayakumar

Visa

Nandu Jayakumar is a software architect and engineering leader at Visa, where he is currently responsible for the long-term architecture of data systems and leads the data platform development organization. Previously, as a senior leader of Yahoo’s well-regarded data team, Nandu built key pieces of Yahoo’s data processing tools and platforms over several iterations, which were used to improve user engagement on Yahoo websites and mobile apps. He also designed large-scale advertising systems and contributed code to Shark (SQL on Spark) during his time there. Nandu holds a bachelor’s degree in electronics engineering from Bangalore University and a master’s degree in computer science from Stanford University, where he focused on databases and distributed systems.

Photo of Ewa Ding

Ewa Ding

Cloudera

Ewa is responsible for SQL workload optimization solutions including traditional data warehouse workloads offload, and Impala/Hive workloads optimization. She manages product direction and strategy of Navigator Optimizer (formerly known as Xplain.io). Prior to Cloudera, Ewa held leadership positions driving product strategy and product design for several enterprise SaaS applications, including Xplain.io.

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