Book Image

Turning Spreadsheets into Corporate Data

By : Bill Inmon
Book Image

Turning Spreadsheets into Corporate Data

By: Bill Inmon

Overview of this book

Spreadsheets are a popular way to store and communicate business data, but, although they are easy to create and update, they are not reliable enough to be used for making important corporate decisions. With this book, you can gain insight into how to maintain spreadsheets, how to format them, and then convert them into a database of reliable and useful information. Turning Spreadsheets into Corporate Data starts with a quick history of spreadsheet usage. You’ll learn the basics of formatting spreadsheets, including how to handle special characters and column headings, and how to convert the spreadsheet first into an intermediate database and then into corporate data. You will also learn how to utilize the mnemonic dictionary that is created along with the intermediate database. The later chapters discuss the immutability of data and the importance of organizational and political considerations during the data transformation. By the end of this book, you’ll have the skills and knowledge needed to convert your spreadsheets into reliable corporate data.
Table of Contents (16 chapters)
Free Chapter
13: Case Study

Aligning Data from Different Spreadsheets

The modeling of spreadsheet data gives rise to another important question: what if two (or more) spreadsheets have a difference in the significance of data that should be closely aligned?

Furthermore what if there must be a resolution of the numbers? In some cases resolution is not important. Differences can be overlooked. Or differences can simply be ignored. As an example of the case when a number can be ignored, suppose the results of a football game were being discussed. The spreadsheet says that the score was 35-14 in favor of Dallas. In fact the score might have been 35-21. As long as the winner is recorded correctly, the exact score is not of a great concern (except perhaps to a bookmaker).

But in other cases, structural differences between data cannot be ignored. In such a case, how can a resolution be made?

There are lots of possibilities when it comes to resolving data differences. The easiest option is to find the data that...