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Tuesday, 16 July 2013

Issues in Data warehousing

By on 12:48:00

There are some issues surrounding data warehouses that companies need to be prepared for. The failure to prepare for these issues is one of the main reasons why many of the data warehouse project is unsuccessful. One of the first issues companies need to face is that they are going to spend a considerable amount of time loading and cleaning the data.

Some experts said that the typical data warehouse project will require companies to spend 80% of their time doing so. While the percentage may or may not be as high as 80%, the only thing you must realize is that most sellers reduce the amount of time you'll have to spend to do so. While cleaning can be complicated data, and extract it can be more difficult.

No matter how well a company is preparing to manage the project, and we must face the fact that the scope of the project is likely to be longer then they estimate. While most of the projects will start with the specified requirements, and will conclude with the data. Once end users see what can be done with the data warehouse once finished, it is very likely that they will put a high demand for it. While there is nothing wrong with this, it is best to find out what the users of the data warehouse next need instead of what they want at the moment. Another issue that companies will have to face is having problems with their systems put the information in the data warehouse.

When a company enters this stage for the first time, you will find that the problems that had been hidden for years suddenly appears. Once this happens, the business managers have to make the decision as to whether or not the problem can be fixed through a transaction processing system or a data warehouse that is read only. It should also be noted that the company will be often responsible for storing data that have not been collected by the existing systems they have. This can be a headache for developers who encounter a problem, and the only way to solve it is by storing the data in the system. Many companies also find that some of their data is not validated by transaction processing programs.

In such a situation, you will need the data to be validated. When data is placed in the warehouse, and there will be a number of contradictions that will occur within the fields. Many of these areas have information that descriptive. When of the most common issues is when the controls are not put under the names of clients. This will cause headaches for the user repository would want in the data warehouse for ad hoc query to select the name of a particular client. Developer of the data warehouse may find itself forced to change transaction processing systems. In addition, there may be a need for them also bought some forms of technology.

One of the most important problems a company can face is a transaction processing system that feeds information into the data warehouse with few details. This may occur often in the data warehouse that is tailored towards the products or customers. Some developers may refer to this as a matter of granular. Regardless, it is a problem that will want to avoid at all costs. It is important to make sure that the information that is placed in the data warehouse is rich in details.

Many companies also make the mistake of not enough high-budget resources that are related to the structure of the feeding system. To deal with this, the companies want to build part of the logic to clean the platform for the feeding system.

This is important especially if it happens to be a platform mainframe. During the cleaning process, you will be expected to do a lot of sorting. The good news about this is that central facilities often be proficient in this area. Some chosoe users to build within the aggregates since the central assembly will also require a lot of sorting. It should also be noted that many of the end user will not use the training they receive for the use of the data warehouse. However, it is important to teach the basics of using it, especially if the company wants them to use the data warehouse frequently.


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