For typical data entry and storage, data usually appear in flat tables, meaning that it consists of only columns and rows, as in the following example showing data on cooling tower water:
While tables such as these can contain a lot of data, it can be difficult to get summarized information from them. A pivot table can help quickly summarize the data and highlight the desired information. The usage of a pivot table is extremely broad and depends on the situation. The first question to ask is, "What am I looking for?" In the example here, let us ask, "How does water pH vary in each cooling tower over time?":
A pivot table usually consists of row, column and data (or fact) fields. In this case, the column is Observation Time, the row is Point of Interest and the data we would like to see is (average of) Observation Value. The pivot table allows you to quickly filter and summarize data. This allows you to run different scenarios, compare results under different conditions and identify trends. This type of analysis allows you to use your data to solve problems and improve your operations.
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