Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...

The "data" part of the terms "data lake," "data warehouse," and "database" is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...

Data quality is paramount in data warehouses, but data quality practices are often overlooked during the development process. The true measure of an effective data warehouse is how much key business ...

Despite the rise of big data, data warehousing is far from dead. While traditional, static data warehouses may have indeed seen their day, an agile data warehouse — one that can map to the needs of ...

A data warehouse is a central repository of corporate data derived from operational systems and external data sources. The main function of a data warehouse is to support strategic business decisions ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

The most important test of a data architecture is not how it performs on day one. It is how it behaves when the business changes.

The Manage Data Model button may be missing for several reasons. You might be using an unsupported Excel version, such as Excel for the web or a one-time retail ...