How does data warehousing differ from traditional database systems?

Data warehousing differs from traditional database systems by focusing on data storage, analysis, and reporting rather than transaction processing.

Data warehousing and traditional database systems are both methods of managing data, but they serve different purposes and have different structures. Traditional database systems are designed to handle daily transactions and operations of a business, such as sales or inventory management. They are optimised for performing simple, repetitive tasks quickly and accurately. The data in these systems is often volatile, changing frequently as new transactions are processed.

On the other hand, a data warehouse is a system used for reporting and data analysis. It is a central repository of data which is created by integrating data from one or more disparate sources. Data warehouses store current and historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons. The data stored in a warehouse is uploaded from the operational systems such as marketing, sales, etc., and usually goes through a cleansing process to ensure data quality.

The structure of a data warehouse is different from a traditional database. Data warehouses use a different design, called a schema, which optimises the data for reading and analysis. The most common schema types are star schema and snowflake schema. These schemas organise data into facts, which are measurable and quantitative data points, and dimensions, which are reference information that gives context to the facts.

In terms of data storage, traditional databases usually store data in rows, while data warehouses often use columnar storage. This makes data warehouses faster for complex queries, as they can scan and aggregate data more quickly.

Lastly, data warehouses are designed to handle large volumes of data and complex queries. They use techniques such as partitioning, indexing, and denormalisation to improve performance. Traditional databases, on the other hand, are not typically designed to handle these types of workloads.

In summary, while both data warehouses and traditional databases are crucial for data management, they serve different purposes. Traditional databases are designed for transaction processing and operational tasks, while data warehouses are designed for data analysis and reporting.