Techcorp Pty Ltd - Data Storage, Management, and Tracking Methods - Assignment Example

TECHCORP PTY LTD. Name: Course: Instructor: Institution: City: Date: Table of Contents Introduction 3 Data Storage, Management, and Tracking Methods 3 Kimball’s Bottom-Up Technique 3 Inmon’s Top-Down Technique 4 Kimball’s vs. Inmon’s 4 Questions to be answered by the Data 4 How Best the Data can answer the Questions Efficiently 6 Conclusion 7 References 8 Introduction The success of any business is largely dependent on how well the business plans itself strategically. In fact, strategic planning is fundamental in projecting the business’ performance in the years to come. Such planning relies heavily on information gathered by the business on its operations through enterprise reporting. This is where business intelligence comes in handy. For that reason, business intelligence may be understood as a tool used by the executives of a business to easily and suitably interpret the performance of their businesses in a timely manner. Specifically, business intelligence reports are important in the projection of sales as well as production, monitoring progress in sales, understanding client commitment, understanding trends in profits, and providing knowledge on the consumption trend of customers. This report, therefore, seeks, on behalf of Techcorp Pty Ltd., to provide an overall reporting solution with which the client can generate daily/monthly reports for informed decision making and strategic planning for their business. Data Storage, Management, and Tracking Methods The field of manipulation of data for decision making in business is one whose foundation has been majorly developed by two experts – Ralph Kimball and William Inmon. Whereas the former’s philosophy has been coined around developing “Data Marts” first, the Inmon’s philosophy revolves around “Data Warehousing” first as clearly explained hereunder. Kimball’s Bottom-Up Technique Kimball’s method is commonly referred to as the ‘Bottom-Up Approach’ because of the fact that his philosophy proposes that the data management process begins by first designing a number of data marts for use by the various departments in an organization. The designed data marts can then be brought together for the bigger functionality of the entire business enterprise in form of a Data Warehouse via Information Bus. The main focus of this method, therefore, is in the use of data marts to address the various departmental issues. Inmon’s Top-Down Technique Inmon’s approach, on the other hand, proposes that while setting up a data management system, it is advisable to develop one that takes care of the whole enterprise first – which he referred to as a ‘Data Warehouse’. From the data warehouse, Inmon proposes that several data marts can then be established to take care of the requirements of the various departments, hence the name ‘Top-Down technique’. Kimball’s vs. Inmon’s Bottom-Up Approach Top-Down Approach 1. Less complex to design -More complex to design 2. Has a slowly changing time frame -Its time frame doesn’t change slowly 3. Links data (in data marts) on the same event together -Links warehouse data on the same event together 4. Has dimensional tools -Has relational tools 5. Doesn’t employ a normalized data technique -Employs a normalized data technique 6. Faster data warehouse building -Consumes a lot of time to build 7. Prone to redundancy -Easy to maintain 8. Relatively lower initial costs -High initial costs are involved 9. Initialization process takes a shorter time -Initialization takes quite some time 10. Its expert requirements are lower -It requires highly skilled experts to design Table 1: A comparison of the Top Down and Bottom Up Techniques Questions to be answered by the Data The data in the overall reporting solution will aim at answering certain specific questions that will lead it into clearly helping solve the business needs as expected by the client. The data in this report should focus on four fundamental questions are discussed below: 1. Which was the overall highest daily/monthly/quarterly/annual sale for the business? – The data stored should be able to help the business gain an understanding on their greatest sales in all its products within any given period of time. By so doing, the business will be better placed to strategically plan on how best it can increase its production during the projected high-sale periods. 2. Which was the highest daily/monthly/quarterly/annual sale for a particular product line in the business? – The data should be able to ensure that the business interprets and understands how its individual products perform in terms of sales, and when does each product specifically experience highest sales. Such information will be important for the business in terms of knowing its best performing products and their respective peaks. 3. Which was the highest daily/monthly/quarterly/annual sale in terms of customers for the business? – The data stored will also be important to the business in establishing the best days/months/quarters/year for which the business receives a huge number of customers. With such information, the business will be able to plan accordingly on how to increase the number of its customer service representatives in order to efficiently handle the many customers coming in during such times. 4. Which product had the greatest daily/monthly/quarterly/annual sales? – Unlike the highest daily/monthly/quarterly/annual sale for a particular product line in the business, this question will be fundamental in facilitating the business to know which one of its various products generally sells more, and during what times. Such information will be essential in helping the business know the product lines it should channel much of its production efforts. How Best the Data can answer the Questions Efficiently Based on the aforementioned questions in the previous section of this report, this report recommends the following proposals on how best the data can be used to answer those questions. First, the data stored in the designed reporting and analysis solution will accomplish its first objective by keeping records of all sales for the business in terms of daily sales, monthly sales, quarterly sales, and yearly sales. These figures can then be compared over time, and the highest sales for each of the four parameters can then be established founded on the available data. Here, bar graphs may be used to clearly identify the specific time lines in which the business’ overall sales were highest. To answer the second question, this reporting and analysis tool will be designed in such a manner that every product for the business can be reported and analyzed separately. The data therein will be stored and managed separately for every product so that the daily/monthly/quarterly/annual sales for every individual product in the business can be handled and manipulated separately. That way, the data will establish the highest sales for every product, and when these peaks actually occurred. The data will answer the third question by recording daily/monthly/quarterly/annual consumption of all business products by its customers. Such records can then be manipulated within any given timelines in order to come up with specific times when the business generally received the highest number of customers. Finally, the last question will be answered by designing the solution in such a way that the database records the peak sales for every product in the business, and then comparing those peaks. Through such comparison, the data will be in a position to display the highest of all the recorded product sales peaks. Conclusion Whereas the proposed reporting and analysis solution may seemingly appear to be tailor-made for particular types of businesses, it may be amended to meet certain needs for other businesses too. Important to note, however, is the fact that the parameters to be included in the design largely differ from one type of business to another depending on the business needs to be captured by the reporting and analysis solution as requested by the client. In conclusion, therefore, it will be prudent to have this proposal critically and thoroughly scrutinized by our client prior to the actual design process of the reporting and analysis solution. That way, the bugs in the database will be minimized, and the efficiency and effectiveness of the reporting database kept beyond the client’s expectations. References Imhoff, C., Galemmo, N., & Geiger, J. G. (2003). Mastering Data Warehouse Design. New Jersey, John Wiley & Sons. http://www.123library.org/book_details/?id=10211 Inmon, W. H. (2005). Building the Data Warehouse. Hoboken, John Wiley & Sons. http://public.eblib.com/choice/publicfullrecord.aspx?p=239420userid=^u Sabherwal, R., & Becerra-Fernandez, I. (2009). Business intelligence. Hoboken, N.J., Wiley. Sherman, R. (2014). Business intelligence guidebook: from data integration to analytics. http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk &AN=543732 Thierauf, R. J. (2001). Effective business intelligence systems. Westport, Conn. [u.a.], Quorum Books. Whitehorn, M., & Whitehorn, M. (1999). Business intelligence: the IBM solution ; [Datawarehousing and OLAP]. London [u.a.], Springer. Read More