It wouldn’t be far fetched to claim that relational database management systems (RDBMS) are the operational backbone of every modern business nowadays. Storing business-critical data, its speedy retrieval when required,…
Decoding the Abstraction Layer in Data Warehousing
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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How Data Masking Provides Security within a Data Warehouse
The immense amount of sensitive information stored in data warehouses makes them attractive targets for data hackers. This means that securing a data warehouse efficiently is of high importance. At…
Best Security Practices For Data Warehouses | Data Warehouse Information Center
[…] information about security protocols and ensuring all the personnel in the proximity ...
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...
The 3 Stages of Data Cleansing to Ensure Data Accuracy in Your Data Warehouse
Are you embarking on a cleansing journey for your data warehouse initiative? In this article, we will cover the 3 phases of data cleansing to help you define a process…
[…] analysis. This blog post is focused on the importance and challenges associated with ...
[…] when accessed. Different view levels can be offered to different tiers of users. More...
Do You Need a Logical Architecture for Big Data Analytics in Your Organization?
“The world is getting more distributed and it is never going back the other way.” Ted Friedmann, VP Research, Gartner If you’ve been actively researching big data analytics, you are…
[…] logical level, as the name implies, is the logical design of the data warehouse, and ...
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…