In this era of data-driven decision making, data quality holds immense significance. Accurate data has been gauged to be a priority factor in customer experience enhancement and creating a business…
Decoding the Abstraction Layer in Data Warehousing
Before the Xbox and iPhone, prior to the first Facebook Like or Tweet, and well before the cloud and tablets, there was the data warehouse. For over 30 years, businesses…
Justin
Great post....
Normalization and Denormalization – Differences through Use Cases
Introduction Today, the most common argument among data warehouse managers is determining which schema is more performance-oriented. However, it’s critical to know that neither of the normalization or denormalization approaches…
What Is Data Engineering? | Boost Labs
[…] is possible to build denormalized data tables from fact tables and dimensio...
[…] through column entries.This relationship between database objects is visually represe...
Making Sense of Data Warehouse Architecture
Business intelligence and database teams have a range of options when conceptualizing their data warehouse design. You could go with either the Kimball or Inmon route and decide whether to…
An Overview of Logical Data Warehousing
Popularized by Gartner IT analyst Mark Beyer in 2011, the term “logical data warehousing” is defined as an architectural layer that combines the strength of a physical data warehouse with…
[…] from different source systems. That’s why data virtualization layer is also referre...
[…] is not possible without significant data conversion and transformation, triggering th...