Enterprises, owing to their operations in diverse global markets, can no longer depend on traditional data warehouse architectures to fulfill their Business Intelligence (BI) requirements. This is because of the…
Traditional vs. Cloud – Comparing the Shift in Data Warehouse Architecture
Data warehouse architecture is changing, and it has been changing for some time now. The traditional on-premise deployment model was succeeded by cloud deployment. However, cloud-based data warehouses are different…
Iqbal Ahmed Alvi
Thank you....
kumari
Thanks for the informative blog...
The 5 Key Components of an Enterprise Data Warehouse
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…
Metadata Repositories: The Managers of a Data Warehouse
[…] data management and serves as a descriptor for an object that holds some data or info...
[…] immense amount of sensitive information stored in data warehouses makes them attracti...
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…
[…] recent developments in the construction of data marts allow integration of web and en...
What is Data Virtualization?
At its core, data virtualization falls within the domain of data integration. But unlike traditional data integration where Extract-Transform-Load (ETL) processes are used to physically move copies of data from…
[…] with the help of emerging data warehousing techniques like data warehouse automation ...
[…] data virtualization, the data rests at one place and is not moved or replicated to an...