Delivering Data Faster: Innovations in Integration Tools NEW!

Duration: 3 to 4 Hours

Innovations in data integration technology are unlocking new business capabilities, reshaping data architecture, and shifting development workflows to new participants. Join Mark Madsen for an in-depth review of modern data integration techniques and to learn what solutions are the best match for your business.

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Conference Replay | Digital Course Book Included

Data integration is usually the slowest and most complex part of any data environment, whether it’s a one-off analytics project done by end users or a data warehouse built by IT. The market for data integration is in the midst of change as new technologies challenge assumptions about how integration should be done and who can do the work. It’s now possible for analysts to access, clean, and analyze data without IT involvement.

This course focuses on some of the tools and technologies that speed up the process of delivering data to users. Some of these are analyst focused, like self-service data preparation and analysis tools. Others are focused on challenges in the technology architecture, enabling IT to make data available more quickly.

Topics in this session include self-service data integration, data preparation, exploratory profiling, data virtualization, automation, testing and test data management, making streaming data available to nonprogrammers, and rethinking assumptions about data integration and architecture.

You Will Learn

  • The latest innovations for integrating and preparing data
  • How these new technologies fit into your environment
  • What to look for when evaluating these new technologies

Geared To

  • Architects, analysts, and BI managers who want to understand the new integration technologies

Continuing Professional Education Credits: 4

Apply these credits toward your CBIP recertification. Not certified? Learn more about CBIP and how to get certified here.

Instructor

 

 

Mark Madsen

Mark Madsen is a fellow at Teradata in the Technology and Innovation Office. He focuses on data science and analytics ecosystems, problems of large-scale application, and complex systems. Prior to that he was president of Third Nature, where he advised organizations on strategy and technology for data science and analytics.

Mark spent most of the past 25 years working in the analytics field, starting with AI at the University of Pittsburgh and autonomous robotics at Carnegie Mellon University. He is also involved in technology research, speaks internationally, and chairs several industry conferences.