A data warehouse holds a history of the enterprise. It contains all the experiences and reference materials accumulated by the enterprise. ECM seeks to convert these into meaningful business knowledge that can help manage business processes more effectively. ECM also seeks to make this knowledge available to authorized persons as decision-support information.
What’s Special About a Data Warehouse?
A data warehouse is distinct from application databases. The latter have a different orientation and are normalized for fast online transaction processing. On the other hand, data warehouses are typically designed for querying and analysis.
Data warehouses contain data created by various business applications in use by the organization. The data is not changed or deleted once it is committed to the warehouse, and is used for historical reporting when called upon. Trend reporting and comparisons with previous years are examples of such reports.
Factors such as the need to have enterprise-wide reporting facilities, instead of compartmentalized system-specific reporting, and the increasing need for management information that needs complex processing (which would have slowed down transactional systems), make separate data warehouses increasingly popular.
Data Warehouses Store Enterprise-Wide Content of All Types
Data warehouses accommodate unstructured content like word-processed documents, spreadsheets, and graphic objects, as well as the structured content from operational applications like accounting, payroll, production control, and so on. The result is that data warehouses become more comprehensive repositories of the content generated by enterprises.
Using the Internet, data warehouses can also accept content being generated all across the enterprise. This remains important for modern global enterprises with operations in many countries.
Business Benefits of Data Warehousing
Data warehouses improve access to all kinds of data for end users, as it accommodates both structured and unstructured content. This provides more comprehensive information about the topic under review.
Data warehousing enables trend reporting with its historical data and trends are highly important information for decision-makers.
Both the above features are of high value in enhancing the effectiveness of business managers and operating staff.
Likely Problems with Data Warehousing
The need for complex design, including tackling security concerns posed by Web access, and compatibility with existing systems can pose problems for implementing data warehousing. Careful management is essential for success of the data-warehousing project.
Data mining involves sorting through large amounts of data and extracting relevant information. With the huge volumes of all kinds of content in data warehouses, data mining produces valuable business intelligence through proper mining.
Data mining is facilitated through the use of metadata that is associated with data sets. Metadata includes such things as tags or index fields indicating the nature of the content and executive summaries or short descriptions of the content.
Using modern sophisticated algorithms, data mining can reveal significant business trends revealed by the historical data in the warehouse.
These identified trends are often projected into the future to forecast future business scenarios.
Data mining is more than just a template-based data analysis in that it involves some degree of intelligence in producing the informational result.
A data warehouse is a repository that stores structured content from the operational applications of the organization, as well as unstructured information in various forms. This warehouse is mined to extract meaningful information, such as historical trends. An Enterprise Content Management system uses data warehouses and data mining to create meaning out of the vast collection of content being generated all across the enterprise.