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The Return of Investment (roi) of Datawarehousing

Essay by   •  November 30, 2010  •  Research Paper  •  1,905 Words (8 Pages)  •  1,541 Views

Essay Preview: The Return of Investment (roi) of Datawarehousing

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TABLE OF CONTENTS

I. INTRODUCTION - p. 3

II. HISTORY - p. 3

Definition - p. 3

Timeline - p. 3-4

III. ROI OF DATA WAREHOUSING

Aspects of ROI - p. 4

Measuring the ROIT of IT - p. 4-5

ROI Impact for a Data Warehouse - p. 5-6

IV. New Technology

Hardware - p. 6

Software - p. 6-7

V. Conclusion - p. 8-9

VI. Bibliography - p. 10

This paper will present the return on investment (ROI) of data warehousing (DW). The history of data warehousing is based on the definition and timeline. Then, detailed information about return on investment will be discussed. Following, will be information about data warehousing new technology of hardware and software. Data Warehousing is a new term in my department where we use the Network Appliance (NetApps) Netfiler storage devices/units. The information read was very informative and helpful in my understanding data warehousing better. Finally, a conclusion about the return on investment of data warehousing.

According to Ralph Kimball's article, www.dwinfocenter.org/defined.html, "a data warehouse is a copy of transaction data specifically structured for querying and analysis." The author has two quibbles with the Ralph's definition and they are: "1) sometimes non-transaction data are stored in a data warehouse - though probably 95-99% of the data usually are transaction data and 2) querying and reporting rather than "query and analysis" because the main output from data warehouse systems are either tabular listings (queries) with minimal formatting or highly formatted "formal" reports." "Queries and reports generated from data stored in a data warehouse may or may not be used for analysis." The author states, "he especially like about Ralph's definition is what he does not say which is the form of the stored data has nothing to do with whether something is a data warehouse." A data warehouse can be normalized and de-normalized. It can be a relational database, multidimensional database, flat file, hierarchical database and object database. Data warehouse data often gets changed and often focus on a specific activity or entity. The timeline for data warehousing is very difficult to calculate because depending on how much time an organization is willing to spend on research, analysis, and design will determine the exact timeline required to start utilizing a data warehouse. The data warehouse comes ready for use, but an organization has to get prepared to use it. The main factor is data warehouse usage. A data warehouse can be used for decision making for management staff.

Article, www.coppereye.com/data_warehousing, states the aspects of return on investment of data warehouse is "the architectures have typically placed a premium on storing large volumes of data, and being able to execute queries very rapidly against this data." Real-time, with current information, is what is available with all the new data warehouse technology. Also, the article states, "it is common practice that loading the data is done overnight, and in many cases taken much longer with the growing success of data warehouse projects." Another aspect is, "business owners are no longer willing to accept reporting on last week's or even yesterday's performance, but want immediate access to data and reports about what is happening in the business to make ever more time-critical decisions.":

The website article, www.generation5.ca/mwm, discusses measuring the ROI of information technology (IT). "Sales growth can be affected by many factors - innovation, client benefits, competition, etc." "Price optimization for any company, can be either a very lucrative endeavor or an expensive failure." "Armed with the power of proper analysis, an organization can quickly capitalize on the opportunities the market place offers." "Customers have different needs, and they are willing to pay accordingly."

"Also, increasing sales is glamorous but it is not the only, nor always the best way, to increase your profits." The following are examples how to lower your costs. "Reducing the costs of analysis and modeling, yet dramatically improving speed and quantity." "Minimize downtime by enabling you to do preventive maintenance." "Eliminating unused capacity by providing you with accurate forecasts of utilization. Organizations sometime have unique situations and need to contact professionals in this field of work in order to assist customer with optimizing their costs. According to the article, "data mining and predictive analytics are an essential component of today's competitiveness." "The unprecedented combination of speed and accuracy has empowered clients to analyze their data in a simple, quick and cost-effective manner and take enterprise decision making to the next level."

To compute the ROI impact for a data warehouse, you can use a ROI calculator. In website article, http://datawarehousing.knowledgestorm.com/search/, " this ROI calculator uses a Microsoft Excel workbook and has been developed to evaluate the value of an enterprise data warehouse." "It is designed to help you build a business case by evaluating the impact to your business's bottom line based on the implementation costs, time frame, and the benefits gained." "You enter your cost and benefit information across 6, 12, 24, and 36 months development time periods is immediately available." In article it states, "while intelligence generally costs less than stupidity, many organizations still significantly overpay for the results they get." A main ROI impact is "how you can turn your data into data assets in a cost-effective and efficient manner."

In article, http://www.coppereye.com/data_warehousing, "the CopperEye hardware can quickly and cost-effectively solve several of the most vexing challenges facing data warehousing and business intelligence professions in all industries." "Using CopperEye, companies can: (a) provide a means to quickly get data into the warehouse

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