Built to serve as the enterprise’s single source of truth, the Enterprise Data Warehouse (EDW) integrates data from disparate sources and applications, optimizes it for analytics and reporting, and presents…
Automate Development, Deployment, and Execution with Data Warehouse Automation
From their role as merely a repository for disparate data sources, data warehouses have evolved to become the lynchpin to manage business decisions and outcomes. The modern data warehouse is…
Deliver Changes to Your Data Warehouse in Real-Time with Change Data Capture (CDC)
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…
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…
Where is Big Data Headed? Our Top 3 Predictions
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…
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 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…
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…