Optimizing ETL: The Key to Accelerating Data-Driven Business Decisions

When we are trying to access, understand and decipher data, the time that goes by in the entire process has direct implications on revenue, or the loss of it. One could be involved in analyzing information from a data warehouse, reviewing click-stream data to understand recent trends, or running a query string on current sales figures. The time lost under these processes can be curtailed with the use of ETL-related steps. These steps can be followed by the user in order to curb the amount of time required to manage the data and to work on these various applications. The time that is saved with these ETL steps not only leads to saving of revenue, it also saves precious time. Simultaneously, these steps can help to improve business processes and support decision-making activities. With important decisions being a part of daily routine today, each minute counts. Therefore, it is important that the data required to take that decision is easily accessible. For the same, the data warehouse should have tremendous capacity and it should not take too long to load. A recurring problem in the case of database management is that with over-abundance of data, the need for streamlining, reformatting, or regrouping is enhanced. This paper delves on the ways in which we can reduce time spent on data hunt and improve results when processing the data.