To add the category to a flat Excel worksheet, you would have to copy in the column that contained the category names. For example, suppose you find that your data contains product IDs, but not the names of products or their categories. Usually the category table is linked to the fact data by some kind of key. However, in a relational system, hierarchies such as categories for products are often stored in a different table than the fact or value table. When you build groups in Excel, you must manually type or select the groups you want to use from among the columns in your worksheet. If the data does not already contain values that you can use for grouping, such as a product category or the name of the geographical region where the store is located, you might want to introduce groups to your data by adding categories. To create a calculation that answers these questions, you must have detailed data that contains the numbers to count or sum, and that numeric data must be related in some way to the groups that you will use to organize the results. Minimum and maximum values Which sales districts were the top five in terms of units sold? For example, aggregations can answer the following questions:Ĭounts How many transactions were there in a month?Īverages What were the mean sales in this month, by salesperson? The decision of how to group the data is driven by the business question. If you then create a ratio of this year over the previous year and present those as percentages, it is a different type of aggregation. For example, when you create a total for a year, you are creating an aggregation. When you aggregate data, you group data by attributes such as product, price, region, or date and then define a formula that works on all the data in the group. Understanding Aggregations in Power Pivot Choosing Groups for Aggregation Other types of aggregations, such as AVERAGEX, COUNTX, COUNTROWS, or SUMX return a table, and require a formula created using Data Analysis Expressions (DAX). Most common aggregations, such as those using AVERAGE, COUNT, DISTINCTCOUNT, MAX, MIN, or SUM can be created in a measure automatically by using AutoSum. An important part of data modeling is to define aggregations that simplify, abstract, or summarize patterns in answer to a specific business question. This lack of summaries or structure might make it difficult to discover patterns in the data. When you start with raw data from tables or other data sources, the data is often flat, meaning there is lots of detail, but it has not been organized or grouped in any way. Aggregations are a way of collapsing, summarizing, or grouping data.
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