Data Warehouse Design Strategies

To build an effective data warehouse, it is important for you to understand data warehouse design principles. If your data warehouse is not built correctly, you can run into a number of different problems.

The proper methods for building a powerful data warehouse are based on information technology tactics. First off, it is important that you and your organization understand the importance of having a data warehouse. If workers feel that a data warehouse is unnecessary, they may not use it, and this could cause conflicts. Everyone in your organization should understand the importance of using the system.

After you have got your colleagues behind the concept of using a data warehouse, you will want to next focus on data integrity. You will want to avoid designing a data warehouse that will load data that is not consistent. It is also important to avoid creating a database that will replicate data. The goal of your organization should be to integrate data and create standards that will be used and followed. After data integrity, you will next want to look at implementation efficiency. This basically means that you will want to design at system that is simple to use. It doesn't matter how well designed your data warehouse is if your workers have a hard time using it.

If your workers have a hard time using the data warehouse, it will slow down the speed and productivity of your operation. When it comes to creating a data warehouse, you will want to make it as simple as possible. All of your workers should be able to use it without problems. Implementation efficiency is a principle that naturally leads to the next topic you will want to focus on, and this is user friendliness. This is a concept that is an important part of your business. The reason for this is because end users will not utilize a program that is too difficult to use. It is important for you to keep them in mind. Use a design which is friendly and easy to learn.

Once you have designed a data warehouse that is user friendly, you will next want to look at operational efficiency. Once the data warehouse has been created, it should be able to carry out operations quickly. In addition to this, it should not have errors or other technical problems. When errors or technical problems do occur, they should be simple to fix. Another thing you will want to look at is the cost involved with supporting the system. You will want to keep these costs low as much as possible.

The design principles that have been discussed in this article so far are more related to business than information technology. However, there are a number of IT design principles that you will want to follow. One of these is scalability. This is a problem that many data warehouse designers run into. The best way to deal with this issue is to create a data warehouse that is scalable from the beginning. Design it in a way which will allow it to support expansions or upgrades. You should be able to adapt it to a number of different business situations. The best data warehouses are those which are scalable.

The data warehouse that you design should fall under the guidelines of information technology standards. Every tool that you use to build your data warehouse should work well with IT standards. You will want to make sure it is designed in a way that makes it easier for your workers to use. While following the guidelines in this article won't allow you to always be successful, it will greatly tip the odds in your favor. You should be wary of companies that promise you perfect results if you use their design methods. No matter how well designed your data warehouse is, you will always run into problems. However, following the right principles will make the problems easier to recognize and solve.

When it comes to using a data warehouse, it is not a matter of "if" you will run into problems. It is matter of "how" and "when." When your data warehouse is well designed, you will be better equipped to solve any problems you encounter.

SOURCE:http://www.exforsys.com/tutorials/data-warehousing/data-warehouse-design-strategies.html