What is a Data Warehouse?

 

A combination of different types of strategic data aids, Data Warehousing (DWH) is a process that collects and manages data within a system. More often than not, Data Warehouses gather data from multiple sources while acting as a core designed for analysis and generating reports. Data Warehousing helps business leaders make better decisions, faster.

Data Warehouses are not particular products but an entire ecosystem. They allow users to find past and present information in a more organized manner compared to traditional operational databases. A well-designed data warehouse can access information faster and create better reporting processes.

Data Warehouse Data Structures

Data Warehouses take information from various sources and acts as a repository. There are three types of data in Data Warehouses: structured, semi-structured, and unstructured.

Before users can make use of the data through Business Intelligence tools, it first has to be processed through Data Mining. Data Mining looks for meaningful patterns from the Data Warehouse to create a holistic view of the business and give better recommendations to relevant business units.

Types of Data Warehouses

There are three main types of Data Warehouses: Enterprise Data Warehouse, Operational Data Store, and Data Mart.

The Enterprise Data Warehouse (EDW) is a business’ central data warehouse that classifies data while giving access to the right users. While Operational Data Stores (ODS) are real-time data often used for routine activities, and Data Mart is Data Warehouses made for specific business units.

What are Data Warehouses used for?

Data Warehouses are used by businesses to sort through data from various sources and organize them by context to become usable. Data Miners use them as a preliminary step to find a meaningful pattern.

Many industries regularly use Data Warehousing to improve their operations and data mining practices. From retail chains looking to track items and manage inventory to airlines that need to keep track of repeat customers and route profits, there are infinite ways that Data Warehousing aids businesses from all over the world.

The Struggles of Implementing Data Warehouses

Data Warehousing is not without issues. Data Mining becomes increasingly common, so are the restrictions that come with the amount of data that companies are allowed to store.

The beginning stages of building a Data Warehouse can also be an overwhelming process for companies that did have a good data management foundation. It can be time-consuming and require additional training to adjust people to their usage.

Many large companies also struggle with organizing a large amount of complex data that may not find in the existing cloud storage solutions and may need physical storage that entails additional maintenance, hiring of personnel, and use of space.

Conclusion

While Data Warehousing may seem like a resource-intensive process, it’s an investment that will be useful for years to come. It can help users efficiently access critical data, and integrate systems that would otherwise be a pain to consolidate.

Overall, Data Warehousing should be standard practice and creates a good foundation for Data Mining.