Introducing the data warehouse and business intelligence industry to dimensional modeling in its current form in 1996, the Kimball Group has since published numerous articles and tips that cover dimensional…
Star Schema vs. Snowflake Schema | Data Warehouse Information Center[…] two types of schemas in a dimensional data warehouse that we’ll discuss in this ar...
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…
Types of Data Integration | Data Warehouse Information Center[…] from different source systems. That’s why data virtualization layer is also referre...
Logical Architecture for Analytics | Data Warehouse Information Center[…] is not possible without significant data conversion and transformation, triggering th...
Starting off in the early 90s for data warehousing, large companies that ran substantial transactions and had huge user base used Extract-Transform-Load (ETL) processes to consolidate transactional data across all…
Data modeling refers to the exploration of data-oriented structures. It is a process that involves documenting a complex software design in a comprehensive diagram, using symbols and texts, to represent…
Testing for Agile Data Warehouse Environment | Data Warehouse Information Center[…] develop a test strategy, you need to understand data modeling, and map data from sour...
Understanding Dimensional Modeling| Data Warehouse Information Center[…] to change or extend data models to reshape them as business requirements change, givi...