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What are the Different Ways to Improve Data Warehouse Performance?

By Katriena Knights
Updated: May 16, 2024
Views: 9,821
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As data warehousing has become more and more important to businesses, increasing data warehouse performance has become vital. A company's data warehouse contains information about clients, trends, sales and many other elements of business intelligence that help executives and other company decision makers determine company strategy. With many people depending on the data in the data warehouse to do their jobs, data warehouse performance can have a profound impact on overall company performance. Many companies rely on numerous ways to improve this performance, including clearing obsolete data, increasing storage space and improving overall data warehouse architecture and design, to keep the data warehouse and the company functioning at their best.

Data warehouse performance tends to degrade as more data is collected over a period of time. Increased data mining, while important to the business, increases the overall load on the system. More people making use of the system also increases the load as a larger number of queries are made by various employees. Removing obsolete information means that queries can be processed more quickly and return more relevant results, making overall data warehouse maintenance an important part of improving data warehouse work.

Infrastructure is another important factor in data warehousing. A data warehouse system can be functioning at the highest possible level for the available technology, but three or even only two years later, it can be considered obsolete. Improving the data warehouse architecture, both on a hardware level and a programming level, also can greatly increase data warehouse performance. Updating processors, adding additional storage space and using newer, more streamlined query protocols can greatly improve performance. In addition, these changes in overall data warehouse design can make a dramatic difference in the amount of data that can be stored as well as the speed at which the system can process individual queries.

Another approach that can help improve data warehouse performance is training. Data warehousing originally was designed to support decision making on a high executive level, but the overall usefulness of business intelligence has led to many other people using the data for a variety of purposes. In some cases, these employees have not received adequate training and do not know how to construct efficient queries to retrieve the information they need. For these employees, training on the use of the system and how to effectively query the data can lead to great improvement in data warehouse performance.

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Discussion Comments
By miriam98 — On Dec 26, 2011

@Mammmood - I believe in optimizing the database but I am all for increased storage space. The fact is, there is no reason not to do that. With terabyte hard drives becoming cheaper in price I think you should have multiple drives for your data warehouse system.

Increased processor speed would help too but I think storage space is the real concern. I work on a server at work and often hit space limitations because I am building another database.

My administrator just tells me to delete the old databases that we don’t need, which I do, but I don’t think it would hurt to get the maximum storage space possible. I think we can afford it.

By Mammmood — On Dec 25, 2011

I am not a data warehouse manager but I do know something about databases. One of the things that slows down performance on a database is not having enough indexes on your tables.

Indexes are like the appendices in the back of a book. They help the database engine to quickly find the data just as an appendix would help you quickly locate information.

Without an index, the database would have to search through every record in order to find the information that you are looking for. Of course database administrators understand this and do use indexes, but I think it’s possible over time they may need to add more indexes, as the data increases in size.

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