Cost of Data Warehousing: Conventional Wisdom Versus Reality September 23, 2022 by Bill Inmon Conventional wisdom claims that data warehouses are expensive to build. That's certainly been the case for many organizations. But is it always the case?
The Biggest Mistake in E-Commerce: More Data Means More Business Value September 16, 2022 by Bill Inmon It doesn't matter how much data you have. If your data doesn't provide business value, you're wasting your time. Computer scientist Bill Inmon explains more.
Why is Data Integration Important in a Data Management Process? September 12, 2022 by Hannon Brett Data management is only as effective as the quality of your data, but how does data integration ensure data integrity and actionable business insights?
Blending Data in the Data Warehouse September 09, 2022 by Bill Inmon Learn more about analytical processing using blended data and addressing the issue of analyzing data from several different environments.
Optimize Driver Behavior to Reduce Fuel Consumption September 07, 2022 by Felix Knott Learn how optimizing driver behavior reduced fuel consumption for a Canadian firm using API and ETL technology in our latest case study
Burying the Data Warehouse — Why? | Integrate.io September 02, 2022 by Bill Inmon Learn why so many people loathed the idea of the data warehouse, and how they subsequently, yet unintentionally, bolstered its architecture.
Avoiding Data Integration August 26, 2022 by Bill Inmon For many years now, vendors and consultants have avoided the practice of data integration. Integrating data is complex. Systems are often undocumented, which makes searching for them difficult.
How To Improve Data Observability for Better Business Insights August 22, 2022 by Mark Smallcombe What is data observability for Ecommerce teams, and how can you improve it? Learn best practices for observability and how Integrate.io automates the process.
ETL Methodologies: A Guide to Our Data Warehouse Integration Platform August 15, 2022 by Donal Tobin Without integration processes like ETL, today's businesses wouldn't be able to make sense of the streams of data flowing into their tools.