subject: Challenges Of Data Warehousing [print this page] The importance of business development is always of high priority for the owners and managers of an organizations since it is one of the key elements which supports the chances of future survival. The driving force for business development practice is business intelligence, which is a continuous process of finding and studying the patterns in available data. However, as the number of channels & data pipelines have increased with the advancements of technology, the volume of data have exploded & so deeper data analytic became necessary.
This has changed the basis of warehousing management systems to store, process and report data. The data in a data warehouse is routed from operational databases or sources which is further created by various operational departments like marketing, administration, sales etc. A data warehouse usually houses the data collected over a long period of time on quarterly basis, half-yearly basis or yearly basis. With increasing data source, the data analytic systems starts taking long duration to process the repository of databases and slows down the pace of business intelligence activities. This eventually affects business development and growth rate of an organization adversely.
User expectation: As the volume of data in a warehouse increases, warehouse management systems need to move deeper in warehouses for data analysis. The end-user in these cases demands and expects more accurate and refined results in return of processing, however that is not the case with warehouse systems. The performance decreases with exploding data and so the efficiency of the system reduces.
Systems optimization: Regressive utilization of business intelligence tools require frequent maintenance and fine tuning of whole system in order to meet users' expectations. Carefully designed and configured data analysis tool helps in providing better results for effective business development decisions.
Data structuring: Proper processing of data requires structuring it in a desired format so that further operations can be executed. As the volume of data increases the task of structuring the unstructured data add-on in slowing down the processing capabilities of system and eventually becomes hectic for the system manager to qualify the data for analytic purpose.
Prefabricated vs. Custom warehouse: The varieties of warehouses available in market, create ambiguity about which type to choose or go for. Where custom warehouse saves the time of building the warehouses from various operational databases from weeks to days or even hours, prefabricated warehouses saves the time of initial configuration and installation.
Resource Balancing: In order to draw benefit from data warehousing, most departments inside an organization tend to access the processing capabilities of the warehouse. This eventually reduces the performance of the system and decreases the efficiency as the stress on the system increases. Access control and security are some techniques which can be used to maintain a balance between the utilization and performance of warehouse systems.
Changing business and data requirements cannot rely on data warehousing instead there must be a flexibility to adapt and accept the technology in order to make use of it for business intelligence and business development. This ensures that the technology is not the master or driving force for the business rather a supporting force. It's the human intelligence which drives a business and makes it successful.
