Datawarehouse

At its simplest, data warehouse is a system used for storing and reporting on data. The data typically originates in multiple systems, then it is moved into the data warehouse for long-term storage and analysis. This storage is structured such that users from many divisions or departments within an organization can access and analyze the data according to their needs.

A data warehouse contains data from many operational sources. It is used to analyze data.

Data warehouses are analytical tools, built to support decision making and reporting for users across many departments. They are also archives, holding historical data not maintained in operational systems.

Data warehouses work to create a single, unified system of truth for an entire organization. Unfortunately, as you might imagine, trying to maintain accuracy and thoroughness in such a system is incredibly difficult.

So, if data warehouses are so complex to build and maintain, why do organizations bother?

Data warehouses can provide:

• A single point of access for all data, rather than requiring users to connect to dozens or even hundreds of systems individually
• An assurance of data quality
• A history of the data they store
• Separation between day-to-day operational systems and analytical systems, for security reasons
• A standard set of semantics around data, for example: consistency in naming conventions, codes for different types of products, languages, and currencies, and so on

Storing comprehensive data in structured relationships, means that data warehouses can also provide answers to a whole variety of complex questions, like:

• How much revenue has each of our product lines brought in per month over the past ten years, broken out by city and state?
• What is the average transaction size at one of our ATMs, broken out by time of day and total customer assets?
• What is the percentage employee turnover for the past year in stores that have been open for at least three years? How many hours did those employees work per week?