Data Warehouse Project Planning
There are several steps involved in installing, implementing and maintaining a data warehouse. The first step entails evaluating the objectives of a company. These objectives make it possible to know what the firm needs to achieve them, what will need to be tracked, key performance indicators to be monitored and a numeric assessment of the firm’s activities that it can take note of and evaluate where they need to begin. The second step is analyzing the existing system. This is where clients and the different stakeholders are asked pointed questions-this is in an effort to collect information of performance they presently have in place that is or is not effective (Kimball et al., 2011). The third step is information modeling of primary processes of business. An information model is conceptual, and it makes it possible for a company to create ideas of what processes of business need to be interrelating and how to link them. Because the data warehouse is a compilation of structures that correlate, developing a concept of the indicators that need to be interlinked to build top performance levels is a crucial step in the information modeling phase.
The fourth step is design and track. This is where data is moved into the warehouse structure and tracked where it originates from and what it relates to. As such, it is vital to plan how to link data in the separate databases so as to ensure the data is linked as it is loaded into the data warehouse tables (Kimball et al., 2011). The fifth step is implementing the data warehouse plan. Notably, the scope of data warehouse project can be big. Therefore, there is the need to implement this project through phased delivery schedules; the phases are then fitted together after they are completed (Kimball et al., 2011). The last phase relates to maintenance. Because the data warehouse will retain data for long stretches at numerous granularity levels, week and monthly grain storage systems are set up.
Reference
Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., & Becker, B. (2011). The data warehouse lifecycle toolkit. John Wiley & Sons.
