With the tremendous growth in the amount of data being processed and analyzed, data warehouses are more important than ever. A data warehouse is a data management system designed to support business intelligence (BI) activities, and to handle analytics.
The data warehouse acts as the underlying engine used by middleware business intelligence environments that serve reports, dashboards and other interfaces to end-users.
Data warehouses perform queries and data analysis. They usually contain large amounts of historical data. A data warehouse is often considered an organization’s “single source of truth.”
To achieve the goal of enhanced business intelligence, a data warehouse works with data collected from multiple sources. The source data may come from internally developed systems, purchased applications, and third-party data sources.
It may involve transactions, production, marketing, human resources and more. In today's world of big data, the data may be many billions of individual clicks on web sites or the massive data streams from sensors built into complex machinery.
Business users want to "slice and dice" data in multiple ways and an efficient data warehouse will be flexible enough to support that work. While sometimes they need aggregated data, at other times they want need to drill down to details.
Without a data warehouse, it would be next to impossible to centralize and consolidate massive amounts of data from multiple sources. Its analytical capabilities make it possible for organizations to gain deep insights from their data, and this improves decision-making.
Data Warehouses often include the following:
Training is important if you really want to understand the capabilities of Oracle Data Warehousing. Oracle University offers two courses that are specifically geared to those who build and use data warehouses:
Explains database warehouse extraction, transformation, and loading techniques. Learn the challenges involved in planning, designing, building, populating, and maintaining a successful data warehouse. Learn how to improve performance or manageability in a data warehouse using various Oracle Database features.
Use Analytic SQL to aggregate, analyze and report, and model data. Learn how to interpret the concept of a hierarchical query, create a tree-structured report, format hierarchical data, and exclude branches from the tree structure. The course also covers the use of regular expressions and subexpressions to search for, match, and replace strings.
Over time, a data warehouse becomes a valuable historical record that gives data scientists and business analysts valuable insights that benefit the business. Consider taking one of the above-mentioned courses to hone your data warehouse skills.