For over three decades, organizations have relied on data warehouses to support the needs for descriptive analytics of business information consumers to help inform about the current state and to help influence ongoing business decisions. Although organizations are augmenting their analytics programs with machine learning and advanced algorithms for predictive and prescriptive analytics, they will continue to rely on data warehouses to support their needs for descriptive and operational analytics applications. What has changed over time, though, is the increasing sophistication of the data consumers and their growing awareness of the breadth and depth of corporate data assets.
Business intelligence (BI) consumers are no longer the customers of the data warehouse team. Rather, they are their partners. And this suggests that the best way to empower business information consumers is to provide accessibility to organizational data configured in ways that both simplify producing analytics and speed time to knowledge.
To empower the consumers of data requires some key aspects of operational data governance, including:
- Enterprise data intelligence
- Collaboration among the data architects, data stewards, and business data consumers
- A searchable catalog of enterprise data assets, all of which support the simplified engineering of a business intelligence solution
Read the 9-page whitepaper “Data Catalogs, Business Glossaries, and Data Governance for Customer BI Enablement” by David Loshin to explore the historical approaches to developing data warehouses. Also, discover how growing end user sophistication has increased the criticality of ensuring data clarity and consistency of the semantics across a variety of data sources. The whitepaper then discusses the concept of enterprise data intelligence, and how the use of a data catalog facilitates that. Automated data catalogs are excellent for data discovery and documentation. However, they are enhanced with corporate knowledge that data architects can use to supplement and expand enterprise data awareness. And this whitepaper examines how a modern enterprise data catalog will capture and document a broad array of metadata that help the data architects and practitioners enable data consumers. When considering how data catalogs enhance the context for reporting and analytics, we identify two insights that can influence the modern business intelligence stack. The whitepaper provides some recommendations associated with the characteristics of data intelligence tools. And we look at ways that data models, data governance tools, and data catalogs should inter-operate to help re-envision how data governance can drive business intelligence solutions.