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How To Rate Your Data Warehouse
Article Posted On Date : Wednesday, February 3, 2010
How To Rate Your Data Warehouse
Data warehouses have greatly evolved over the last 10 years. They now have their own transaction systems as well as their own design structures. The dimensional design has become the most prominent method of construction for data warehouses in the 21st century. Despite this, it is important for companies to take the time to rate their data warehouses. By doing this, the company will have a good idea of the efficiency of their systems. One of the first things a company will want to pay attention to is the ETL, which stands for extract, transformation, and load. It is important for a company to make sure the data warehouse is comprised of parallelism, since this will speed up the ETL process. Most companies place an emphasis on the data they obtain within the company rather than data that is obtained from external sources. In my opinion, this can be a costly mistake, because external pieces of information can be just as valuable as the information that is gained within the company. When a database is designed, it isimportant for a company to place an emphasis on external data. When data is brought into the data warehouse, it is crucial for it to be properly maintained. The process of transforming data can be very costly, and processing extensive amounts of data will generally need to be done via VLDBs, or very large databases. One way to rate your data warehouse is to determine if you've laid down strict rules for the maintainence of data. Data consistency is one of the mostimportant factors in the success or failure of a data warehouse, and it is something that a company will not want to take lightly. It should also be noted that various decisions will be made based on differing views on the information that is stored within the data warehouse. The input data should be consistent with the decisions and the goals of the organization as a whole. When you analyze the various input systems, it isimportant for you to come up with criteria to determine how much transformation each piece will need. Another important part of the data warehouse that you will want to pay attention to is the structure of the data, as well as partitioning. Structuring the data properly will be crucial for the total performance of the data warehouse. In some cases, it may be possible to partition certain elements within the data warehouse by breaking data into dual columns. Each column will act as a key, and it can be partitioned to the data that has been split. A partial index key is powerful because it will allow you to either combine or split the data throughout the database. A partial key can be created by simply taking one column and breaking it into two columns. However, this must be done carefully so that the end user access is not harmed. It should also be noted that it is possible to create keys from an algorithm. This is a very effective method when you want to randomize information throughout the database. The second column can be used for the purpose of data partitioning, and it may be possible to spread the data across dozens of segments within the database. The numbers could be evenly distributed in numerous places within the database. The ability fora company to rate its database is critically important. If the data is not managed properly, it could easily lead to disaster. It is important for companies to realize that they will make crucial decisions based on the data that is contained within their warehouse. If the data is inconsistent, or it hasn't been cared for properly, this can lead to situations where poor decisions are made based on the information that is presented. This could hurt the productivity of the company, and this will inevitably lead to a loss in profits. Being able to effectively implement a data warehouse is not enough. The data within the warehouse must be properly maintained. Having said that, it could be said that a data warehouse can be rated based on the procedures thata company uses when dealing with it. Learning how to rate your data warehouse is very important.