Why Automated Data Lineage Is a Must-Have for BI and Analytics
Webinar Speaker: Philip Russom, Senior Research Director for Data Management
Date: Wednesday, September 30, 2020
Time: 9:00 a.m. PT, 12:00 p.m. ET
Determining data’s origins and transformations is a way of understanding its business value, trustworthiness, quality, and applicability for specific use cases.
“Where the heck did the data in this report come from and how has it been aggregated and transformed?” That’s definitely one of the most common questions asked by end consumers of BI reports, analyses, data sets, and other data-driven products.
If users do not receive credible answers, they will not trust and consume the data and BI products. In turn, the resulting low adoption of data solutions signals that your work is a failure. Hence, it behooves data management and analytics professionals to put data lineage solutions in place that can accurately answer these and other questions about data’s history, usage, condition, and trustworthiness.
Data lineage records the journey that data takes as it moves from original sources, gets repurposed (via aggregation and transformation), and goes into BI and analytics products, plus other targets. In addition to tracking individual data flows, data lineage also puts them all together to draw a comprehensive data map that many types of users and applications can access. Automated data lineage automatically tracks, records, and catalogs, thereby boosting developer productivity and assuring an up-to-date map of data across an enterprise.
Webinar attendees will learn:
- Numerous uses cases for data lineage, especially those in BI daily operations and analytics
- How data lineage assists data exploration and discovery, solution development, auditing, data governance, and migrations
- How automated data lineage complements metadata management, extends data cataloging, and enables root-cause and impact analysis
CEO & Co-founder of Octopai
Amnon is the CEO and Co-Founder of Octopai, a leader in metadata management automation for Business Intelligence. He has over 20 years of leadership experience in technology companies.
Mark Horseman, Enterprise Information Management
NAIT (Northern Alberta Institute of Technology)
Mark is an IT professional with nearly 20 years’ experience. Mark moved into Data Quality, Master Data Management, and Data Governance early in his career and has been working extensively in BI since 2005. Mark is currently leading an Information Management initiative at NAIT.
Philip Russom, Ph.D.