In a short few years, data warehouse has become an indispensable and integral part of all business activities. To ensure that it remains effective and keeps serving its primary objectives,…
Multidimensional Data Modeling – OLAP Cubes
OLAP (short for Online Analytical Processing cubes) refers to multidimensional databases optimized for data warehouse requirements and specific OLAP applications. The OLAP cube is a technique of storing data (or…
4 Data Warehouse Optimization Mistakes to Avoid | Data Warehouse Info Center
[…] manner. The ever-growing data complexity and the endless user needs are difficult to ...
SQL Vs. NoSQL: Which Database Approach is Better?
When it comes to database technology, there are two common categories: SQL and NoSQL or relational and non-relational database respectively. They are called SQL and NoSQL referring to whether they…
Metadata Repositories: The Managers of a Data Warehouse
Metadata helps with data management and serves as a descriptor for an object that holds some data or information. In data warehouses, it is collectively organized in a catalog called…
Gauging Agility: Testing for Agile Data Warehouse Environment
In this era of data-driven decision making, data quality holds immense significance. Accurate data has been gauged to be a priority factor in customer experience enhancement and creating a business…
Normalization and Denormalization – Differences through Use Cases
Introduction Today, the most common argument among data warehouse managers is determining which schema is more performance-oriented. However, it’s critical to know that neither of the normalization or denormalization approaches…
[…] is possible to build denormalized data tables from fact tables and dimensio...
[…] through column entries.This relationship between database objects is visually represe...
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 virtualization serves as an alternative to ETL and traditional data warehousing ...
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...