Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

The changing role of the CDO: Three keys for success (sponsored by MapR)

Jim Scott (NVIDIA)
11:00am–11:40am Thursday, March 8, 2018
Sponsored
 Location: LL21 A
Tags: mapr_session
Average rating: **...
(2.00, 1 rating)

What you'll learn

  • Explore successful practices every CDO should know

Description

Many organizations have put stock in collecting and organizing data in a central store or data lake to support widespread analysis. However, CDOs who treat data as an asset simply to accumulate actually face the greatest risk for themselves and their organizations. The value of data is not strictly a function of its size but rather is in the value that can be extracted from it. Jim Scott explains how to identify the right data to leverage to monitor the pulse of fast changing business environments, the importance of cross-application data flows, and the best way to integrate analytics into your business to improve outcomes. Whether you are a CDO or simply aspire to have an impact on your organization with data, this session will detail three keys for your success.

Topics include:

  • How to identify important data flows and their impact
  • How to create value across enterprise silos
  • How to successfully share data between users and across functions and locations while maintaining governance
  • The best ways to inject analytics into business processes

This session is sponsored by MapR.

Photo of Jim Scott

Jim Scott

NVIDIA

Jim Scott is the head of developer relations, data science, at NVIDIA. He’s passionate about building combined big data and blockchain solutions. Over his career, Jim has held positions running operations, engineering, architecture, and QA teams in the financial services, regulatory, digital advertising, IoT, manufacturing, healthcare, chemicals, and geographical management systems industries. Jim has built systems that handle more than 50 billion transactions per day, and his work with high-throughput computing at Dow was a precursor to more standardized big data concepts like Hadoop. Jim is also the cofounder of the Chicago Hadoop Users Group (CHUG).