For more than three decades, organizations have relied on data warehouses to support business information consumers’ needs for descriptive analytics to help inform about the current state and to help influence ongoing business decisions.
Although organizational analytics programs are increasingly augmented with machine learning and advanced algorithms for predictive and prescriptive analytics, the ongoing need for business intelligence (BI) supporting descriptive and operational analytics applications will remain.
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 BI consumers are no longer the “customers” of the data warehouse team – 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 the production of analytics and speed time to knowledge.
Empowering the data consumers requires some key aspects of operational データガバナンス, including:
These aspects collectively 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 historical approaches to developing data warehouses and how growing end-user sophistication has amplified the need for data clarity and semantic consistency across diverse data sources.
The paper delves into the concept of enterprise data intelligence and highlights how automated data catalogs facilitate data discovery and documentation. These tools are further enriched by incorporating corporate knowledge, enabling data architects to expand enterprise data awareness.
A modern enterprise data catalog captures and documents a wide array of メタデータ. This empowers data architects and practitioners to support data consumers by enhancing the context for reporting and analytics.
The paper concludes with a discussion on how データモデル, data governance tools, and data catalogs should interoperate to transform data governance into a driver for business intelligence solutions.
The whitepaper discusses:
Click here to read the whitepaper.
The presenter, David Loshin, is the President of Knowledge Integrity, Inc., a consulting and development company focusing on customized information management solutions, including information quality solutions consulting, information quality training, and business rules solutions.
David is a recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master データ管理, and business intelligence. Along with consulting on numerous data management projects over the past 20 years, David is also a prolific author regarding business intelligence best practices, with numerous books and papers on data management.
ER/Studio Enterprise Team Edition is the leading business-driven data architecture solution that combines multi-platform data modeling, business process modeling, and enterprise metadata for organizations of all sizes.
