Which Data Integration Approach is Right for You?

An enterprise uses an average of 928 applications, along with many other on-premise systems. This means that you can have about a thousand source systems from different vendors, each storing…

Data warehouse

Which Data Extraction Approach is Best for Your Data Warehouse?

After the initial phases of gathering requirements and conceptualizing data warehouse design, the execution phase begins. Extract-Transform-Load from source data systems to destination staging database or data warehouse. The process…

Data warehouse vs marts vs lakes

Data Marts, Lakes, and Warehouses – Understanding the Differences

Too many buzzwords, too little understanding. With the ubiquity of data and analytics, IT vocabulary is expanding fast, and terms like data marts, data lakes and data warehouses are being…

Modeling Your Dimensional Data Warehouse: Star Schema vs. Snowflake Schema

A schema refers to the structure or organization of a database. It contains a logical description of the entire database, which includes names and descriptions of tables, records, views, and…

Dimensional modeling

Understanding Dimensional Modeling: The Basics of a Kimball Data Warehouse

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…

Data Warehouse

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…