![]() ![]() Figure 1Ī series of data manipulation steps is applied to change this data to the desired format as show in Figure 2. The data is exactly what is needed, but the format of the data does not work well for the type of analysis desired. state population data as found on the Internet. (See the section on Power Pivot.)Īs an example, Figure 1 shows U.S. The transformed data can be loaded into an Excel spreadsheet or into a PowerPivot data model. Merge data from multiple data extractions into a single table.Once the data is extracted, it can be transformed into a format appropriate for analysis. Databases including SQL Server, Oracle, and IBM DB2.Text files including comma-separated values (CSV) and XML.Power Query can extract data from a wide range of sources, including: Along the way, the data can be manipulated from its native form into a format that is more conducive for analysis. Power Query makes it possible to extract data from a wide variety of locations and assemble it into a data model. Second, the data model stores the data in such a way that it can be retrieved and navigated quickly. ![]() No complex language required to query the data. No weird table and field names to decipher. First, it presents the data to the business user in a manner that they are familiar with. Gather and Modelįor ease and speed of analysis, data is gathered from various sources and placed in data model. Microsoft has Power tools for all of these areas. I’ll try to clarify so you can choose the right Power tool for the job.įor purposes of this article, I’m going to divide the business intelligence process into three areas: Gather and Model Visualize and Analyze Share All of that “Power” can get a bit confusing. ![]() Everything is “Power” this and “Power” that. These days, looking at the business intelligence section of can make a person feel as if they stumbled into the web site for the local hardware store. ![]()
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