Data Warehousing Concepts And Tools
Data warehousing concepts are used to design, create and manage a data warehouse that provides a centralized company database. Data warehouses were first developed in the late 80s and early 90s as a response to the need for business analysis that could not be effectively met by current operational database systems. To meet this need, the process of the recording, collecting, filtering and loading of data into a database was revised, streamlined and customized to support analysis and decision-making. This serves to differentiate these data repositories from the regular transactional systems that are central to operations.
Distinguishing Characteristics
Purpose is the distinguishing characteristic of these specialized data repositories, not form. This means that the form of the stored data or the type of the database used can vary widely. Data can either be normalized or de-normalized and the database itself can take on a number of forms from an object database to a hierarchical database, relational, flat file or multidimensional. The data itself can change a number of times and the database should be designed to accommodate this, but the most important basis for design is in the way it is set up to support decision-making for a specific action or entity.
Design and Implementation Challenges
The implementation challenge starts with the collection of disparate data from several sources, including but not limited to the transactional and operational databases. This database structure must be able to merge old or existing data with new data and transform it into a standard format compatible to the data warehouse platform. Integrating disparate data requires resolving conflicts in areas such as naming and grouping protocol, units of measuring and maybe even time zones.
Benefits and Rewards
Because an efficient database need to be both customized to meet a specific need and flexible enough to handle disparate and changing data, database design can be complicated. The rewards for successfully putting together and running a good database far outweighs the challenges though. Some of these benefits include the following:
- providing a standardized data format for different data sources and interest areas, which will not only streamline analysis and reporting but also make the data reusable for different departments, interest groups and levels
- allowing for more user control over data paving the way for necessary purges and safer storage
- faster data retrieval that does not impede or slow down operations
- streamlines data processing for performance assessment, trend analysis and forecasting reports
- strengthens and speeds up decision making processes for both core business operations and customer relationship management
In essence, data warehousing solutions are meant to enhance data collection and integration to enable accurate and timely reporting. Since good design translates to improved information handling and management, it supports quick, efficient and informed business analysis and decision-making, which are essential to staying competitive and profitable. With such clear benefits to data warehousing, companies should commit resources and develop a strong enterprise vision to ensuring that a workable data warehouse is put into place and maintained.
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