Making Sense of Fragmented Data Sources within a Big Data Analytics Hub

The presentation provides insight into both Enterprise and Business Unit level governance of data in conjunction with the alignment of disparate data sources into a Big Data Analytics Hub to enable business analytics. A use case focusing on Marketing Spends Analytics will highlight Intel’s best practices dealing with governing and aligning fragmented, geographically distributed, inconsistent data sources to drive insights into marketing effectiveness.

Differentiation of enterprise versus business unit level data
Different governance practices for the enterprise or business unit level data
Strategies to identify a common dimensions/pivots at both the enterprise and business unit level
Strategies to resolve data granularity challenges with business direction to enable consistent meaning
Strategies for data matching/conformance
Streamlined architecture for loading and organizing the information in the Big Data Analytics Hub to enable multiple business perspectives
Marketing Spends Analytics Use Case
Key learnings

David has 27 years of experience as a Developer, Data Analyst/Architect, and Enterprise Architect spanning manufacturing, finance, and sales & marketing. He is currently the Enterprise Architect for Retail Marketing at Intel Corp.

Stacie has over 30 years of experience as a Data Analyst/Architect and Enterprise Architect. Currently, she is the Customer and Supplier Master Data Architect at Intel Corp.