Data warehousing Data warehouses ... or “models,” often take the form of entity relationship diagrams (ERDs). More advanced techniques include the star schema and snowflake data model concepts.

A data warehouse is an electronic system for storing information in a manner that is secure, reliable, easy to retrieve, and easy to manage.

But if the shape of data warehousing projects can come in extremes, their basic management blueprint will not be too dissimilar. And they invariably stem from a few common--and common sense ...

Enterprises choose data warehousing solutions to discover data-driven opportunities, Bearman said. It’s time to rework the data warehouse architecture format. Must-haves include: Real-time updates: ...

Because “putting a data warehouse between two Tier 1 apps is a [bad] idea.” Companies tend not to treat their analytical systems “like Tier 1, business-critical components.” ...

Emerging Trends in Data Warehousing and Data Time Series Data Mining Time series-based data mining techniques help businesses to mine data to analyze periodic trends.

Before the iPhone and Xbox, prior to the first Tweet or Facebook “Like,” and well in advance of tablets and the cloud, there was the data warehouse. For 30 years, businesses have centrally ...

Data warehouse modernization, including cloud journeys — 53% Support for real-time analytics — 49% Getting more analytics value from a data lake — 40% IoT analytics — 34% ...

For users, the benefits of data warehousing can go far beyond the cost savings or revenue generation an effective IT project can bring, she said. Usually, ...

Forbes contributors publish independent expert analyses and insights. The days are numbered for on-premise data warehousing solutions like Teradata, Oracle, SQL Server and DB2. Cloud data ...