Data Warehouses

Intelligence is enhancing the Information Technology architecture and systems, providing the opportunity for enhanced services and automated management.

Large data warehouse projects are dominating IT strategy today, in spite of standards and open integration of tools being less than ideal. The sheer size of such programs of work, means starting now, in an imperfect technology is essential if companies are to stay competitive in the future.

Data Warehouse

A data warehouse is the main storage server hosting an organizations historical data, its corporate memory. It is distinct from operational or transactional systems supporting the business functions.

The datawarehouse is used to contain the raw data for management's decision support systems [business intelligence tools].

The main benefit of a data warehouse is that complex queries and analysis, such as data mining, can be made on organisational information without slowing down the operational or transactional systems.

A data warehouse can be defined in the following terms:

• Subject-oriented - The data in the database is organized so that all the data elements relating to the same real-world event or object are linked together.
• Time-variant - The changes to the data in the database are tracked and recorded so that reports can be produced showing changes over time.
• Non-volatile - Data in the database is never over-written or deleted - once committed, the data is static, read-only, but retained for future reporting; and
• Integrated - The database contains data from most or all of an organization's operational applications, and that this data is made consistent.

While operational systems are optimized for simplicity and speed of modification [Online Transactional Processing, or OLTP] through heavy use of database normalization and an entity-relationship model, the data warehouse is optimized for reporting and analysis [online analytical processing, or OLAP].

Data in data warehouses are often heavily denormalised, summarised or stored in a dimension-based model. This is not always required to achieve acceptable query response times.

• Benefits of Data Warehouses
• Data Warehouse Architecture
• Developing A Data Warehouse
• Measuring Data Warehouse Quality
• OLAP, MOLAP, ROLAP, HOLAP

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Data Warehouse Index | OLAP | Developing A Data Warehouse | Measuring DW Quality | DW Glossary