Summary

From this chapter, you should understand the following:

• Text files, spreadsheets, and file-based and server-based databases are the primary data sources that organizations analyze to make better business decisions. Although text files and spreadsheets are easy to create and share, they lack robust data storage and administrative features such as disaster recovery and concurrent data analysis task requests.

• The quality of business decisions can be improved when an organization improves its overall data gathering and analysis strategies. Be sure to include the right people from your organization and your customers as you design these strategies.

• To use Microsoft data analysis tools effectively, you might have to convert or import your existing data into a compatible format. To reduce data entry and analysis errors, you should fill in empty holes in your data by adding “Empty” or “N/A” where no data exists.

• Each Microsoft data analysis software application has its strengths: Excel contains a wide array of data analysis tools; Access is designed to analyze relational data; the Office Web Components are good for analyzing data over the Web; SQL Server is designed to store very large sets of data; the SQL Server Desktop Engine brings many SQL Server features to the desktop; SQL Server 2000 Analysis Services is designed to store hierarchical data; and Data Analyzer is uniquely designed to analyze hierarchical data.

In Chapter 2, “Basic Data Analysis Techniques,” you will learn

• Fundamental data analysis features that can be used to filter, sort, format, import, export, query, chart, and pivot data.

• Simple skills to work with data lists, multidimensional and hierarchical data, and Extensible Markup Language (XML) data.