Data Warehousing Guide

Data warehouse design is crucial in deploying a data warehouse that serves the needs of all stakeholders.

Business analytics leverages Big Data sets to help organizations receive insights around key business metrics and behaviors.

In the not so recent past, cloud data analytics was a small back-office domain inside many organizations.

Today’s manufacturers and retailers are increasingly using data to optimize the supply chain for a competitive advantage. Learn how here.

A comprehensive data strategy will support your business goals, enabling you to overcome challenges and take advantage of opportunities. Learn how here.

What kind of data should be taken into account when companies are deciding on their own data loss protection/prevention strategy? Read here.

Data governance is an organization’s management of its data availability, usability, consistency, and data integrity and data security.

While Data Mart is focused on a single department, Data Warehouse is enterprise-wide and ranges across multiple areas. More differences explored in our guide.

Data wrangling aims to eliminate faulty or incomplete data before analysis. By cleaning up and augmenting existing data, business teams can make better decisions.