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A pivot table usually consists of row, column and data (or fact) fields. In this case, the column is ship date, the row is region and the data we would like to see is (sum of) units. These fields allow several kinds of aggregations, including: sum, average, standard deviation, count, etc.
Data Type. Tableau express automatically data types and fields. Tableau will make use of the data type that the data source has defined if it exists, or it will choose a data type if the data source does not specify one. In Tableau, the following data types are supported [29] Text (string) Value; Date Value; Date and Time Value; Numerical Value
Allegedly, One of Tableau's biggest advantages is how much data it can hold. Tableau can hold an unlimited amount, whereas an Excel spreadsheet has a capacity of 1,048,576 rows. However, it is possible to hold and analyze effectively billions of rows in Excel, using its Power Pivot feature.
Data cleaning is the process of preventing and correcting these errors. Common tasks include record matching, identifying inaccuracy of data, overall quality of existing data, deduplication, and column segmentation. [23] Such data problems can also be identified through a variety of analytical techniques.
A spreadsheet consists of a table of cells arranged into rows and columns and referred to by the X and Y locations. X locations, the columns, are normally represented by letters, "A," "B," "C," etc., while rows are normally represented by numbers, 1, 2, 3, etc. A single cell can be referred to by addressing its row and column, "C10".
SELECT list is the list of columns or SQL expressions to be returned by the query. This is approximately the relational algebra projection operation. AS optionally provides an alias for each column or expression in the SELECT list. This is the relational algebra rename operation. FROM specifies from which table to get the data. [3]
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$33,000, being "average daily sales for Los Angeles Store for year 2005" "Average daily sales" is a measurement that is stored in the fact table. The fact table also contains foreign keys from the dimension tables , where time series (e.g. dates) and other dimensions (e.g. store location, salesperson, product) are stored.