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…
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Change Data Capture (CDC) is a technology that continuously scans source data systems for changes, identifies them, and delivers those changes to the data warehouse in real-time, so business intelligence…
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…
Date Virtualization for Agile Data Warehousing | Data Warehouse Info[…] Data virtualization serves as an alternative to ETL and traditional data warehousing ...
Data is getting bigger every second, with research firms predicting that each person will generate at least 1.7 megabytes of data every second by 2020. So it’s no surprise that…
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…
Testing for Agile Data Warehouse Environment | Data Warehouse Information Center[…] testing begins by identifying source data. The identified and extracted source data i...
Role of Data Warehouse Components | Data Warehouse Information Center[…] Methods of extraction […]...
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…
4 Data Warehouse Optimization Mistakes to Avoid | Data Warehouse Info Center[…] true that analytics experts have used the snowflake and star schemas to get better vi...
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...
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…