Why Build a Data Warehouse in .NET framework

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Why Build a Data Warehouse
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Since the rst application systems were built, businesses have struggled with the proliferation of data Systems have been implemented to automate business processes such as order processing, policy administration, shipping, and manufacturing scheduling Each of these applications captures a lot of data This data has the potential to be used in several ways: To understand what is really happening in the business To identify historical trends To predict future opportunities To measure performance Originally, business requests for data were run directly against production application systems This was not an ef cient way to gather data For example, a request for data might query which days over the last three years have the highest ATM transaction rates in the Midwest Unfortunately, in order to gather this data, the data query slowed or worse, interrupted the ability of the application systems to perform their primary function It is unacceptable to reduce the speed with which the ATMs complete transactions, even to support the corporate marketing department Needless to say, the ability to run these reports against the production application systems was revoked However, understanding the results of such a request was valuable, so a copy of the production data was made to enable reporting and basic analysis to be done without affecting the actual operational systems When working with a copy, modi cations were made to how the data was stored in order to make reporting easier In addition, if historical data was not retained in the operational systems, then the history was kept in the copy New system design techniques were developed to improve how the copy of the data was created and organized Speci c hardware, software tools, and technologies also emerged These have grown into what we know as the data warehousing industry today In spite of these technical advancements, organizations still struggle with some basic data issues: Direct data access: You can t directly access the data; you have to request it from a data systems department
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Part I
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The Essentials of Data Warehousing
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Data usefulness: You can t get the data you need; what is collected is not useful for your purposes Poor data quality: The data, if and when you get it, is often not correct You can t rely on it Facilitating exception reporting: There is too much data; you have to dig through it to nd what s important Timeliness of data: By the time reports get to you, the window of opportunity no longer exists Flexibility: You need total exibility to look at data from a variety of perspectives Data integration: You need to perform analysis across all lines of business but the data is stored all over, so you can t easily compare it Silo reporting environments: Different departments use different reporting tools and you can t share reports Unclear de nitions of data: Everyone has their own report, but the gures do not match and you don t know why These basic data problems that drove the initial work in the data warehousing industry are the same core problems facing businesses today If anything, the problems are compounded by ever-increasing mountains of data While addressing basic data-related issues is certainly a big part of the rationale to build a data warehouse, there are also bigger, more critical business issues that need to be addressed The data warehouse can provide a vehicle to deliver the information needed to help a business address these issues, which is what drives the true value
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The Value of Data Warehousing
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Data warehousing is much bigger than simply delivering reports in a timely manner It is not the data, the technologies, or the reports that impact the business Rather, it is the ability of your staff to harness the information to make better, fact-based, insightful decisions The data warehouse is simply a tool that enables your staff to be more effective The types of things that can be done using a data warehouse include the following: Tracking and trending key performance indicators: A data warehouse can provide reports that indicate which product lines are popular in various regions, which employees have generated the most sales, or whether certain ad campaigns are correlated with successful sales Measuring business performance: Using reports from the data warehouse, actual and forecasted performance can be compared For example,
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