Reference no: EM133202019 , Length: Word count: 2 Page
Assignment Task: Support proper formulation of decision-making criteria using Business Intelligence assets.
Scenario:
You work for a tourism board at a top destination within the United States that, among other tasks, acts as a third-party reseller of attraction tickets in one of the world's top vacation destinations. The organization has an e-commerce presence where tickets are sold online and a physical store location where people can go to purchase physical tickets in person. In all instances, the ticket purchases are recorded and referenced back to various marketing databases that allow the organization to see how well different promotional campaigns have done, which products sell better than others, and what time of year the sales are highest and lowest, to name but a few. Jeff, a junior financial analyst, conducts reviews of the ticket sales data with painstaking detail, often producing reports that show detail lines for each sale from the online web storefront and the physical store. Strategic decisions regarding sales are often made based on a few small examples of individual rows from the report and often do not reflect the sales trends accurately. The board director does not see any issue with the reports that Jeff presents, hailing his work as the best analysis they have ever seen. You have been asked to discuss the current reporting practice with the board, including Jeff, in hopes you can offer some suggestions on how the data can be better presented and explain why there is too much detail in the reports to support effective decision making.
Instructions:
Create an executive summary to the board addressing the following:
Explain the concepts contained within the DIKW (Data/Information/Knowledge/Wisdom) Triangle.
Demonstrate how DIKW applies in the decision-making process for ticket sales.
Determine the appropriate level of data gain necessary for effective reporting and decision making.
Apply business intelligence assets to appropriate a business strategy on how ticket sales data may be better presented through aggregation over months, quarters, and years for future planning.