1 / 4

Challenges & Opportunities in Data Integration and Automation Discussion

Join Stacy Kowalczyk in this workshop as she discusses the challenges and opportunities in data integration and automation. Gain insights on standards, policies, technology, and resources needed for successful projects. The workshop includes a case analysis to identify bottlenecks and potential collaboration opportunities.

hanesr
Download Presentation

Challenges & Opportunities in Data Integration and Automation Discussion

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Discussion of Challenges & Opportunities BrainstormingStacy Kowalczyk

  2. Part I: Eight Questions (1:15) • Standards Used • Standard Needed • Policies Used • Policies Needed • Technology Used (DB, software, etc.) • Technology/Services Needed • Resources/Expertise/Services Offered • Desired Outcomes of this Workshop

  3. Part II: Case Analysis • Better understanding of the bottlenecks in data integration and visualization projects • See if there are emerging “patterns” • Use that as input for a next session on the potential future of data integration and automation • Potential collaboration on some issues

  4. Part II: Case Analysis (30 min) • Take your last (current) data analysis project • Write down the various steps (with a description of the data source) you went through (search, retrieve, combine, clean-up (disambiguate, validate, estimate), transform, analyze, visualize, etc.) • Rank the steps on basis of effort (time, resources)

More Related