Preparing & Cleaning Data in Tableau Desktop

Tableau Desktop    |    Intermediate
  • 10 videos | 42m 57s
  • Includes Assessment
  • Earns a Badge
Discover how to prepare, control, and clean up data before you start working with it to ensure that you get the most out of your analyses in Tableau Desktop in this 10-video course. Learners begin by observing how to manage data types for columns in Data Source page, then take a look at unioning data, and using unions to combine data from different locations and appending values in a single table. Tableau works best with clean data, so next you will explore how to work with data interpreter to identify data anomalies and clean up data. Learn how to split data fields using the split and custom split in the Tableau Data Source Page; use the pivot tool to prepare data for extraction into the Tableau Data Engine, and filter data at the data source level. Delve into managing data sources in a Tableau workbook; replace data sources from the Data Source Page and worksheet view in Tableau Desktop, and refresh live data sources. The course concludes by helping learners discover how to append data to extracts.


  • Demonstrate managing data types for columns in data source page
    Use unions to combine data from different locations and append values in a single table
    Work with data interpreter to identify data anomalies and clean up data
    Split data fields using the split and custom split in the tableau data source page
    Use the pivot tool to prepare data for extraction into the tableau data engine
  • Filter data from the connected data source via the tableau data source page
    Adjust data sources and connections in a tableau workbook
    Replace data sources from the data source page and worksheet view in tableau desktop
    Refresh live data sources and data extracts that are connected in tableau desktop
    Append data from a data source or file to an existing data extract in tableau desktop


  • 4m 22s
    Data type refers to the type of information stored in fields, such as text, dates, integers, and geographic coordinates or values for maps. The data type that you use in Tableau Desktop has an impact on the accuracy of your data. Tableau can analyze your data and assign data types automatically, but you can also change the data type manually, via the Data Source page, if you need to. FREE ACCESS
  • 4m 31s
    If your data is spread across multiple locations, either across Excel worksheets in the same workbook or CSV files in the same location, you can use unioning to bring them together into a single table. Unions can not be created for cross-database data, and can only be created with tables from the same connection. To get the most out of unions, it's best to make sure that the data you are bringing together is stored using an identical or similar table structure. FREE ACCESS
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    3.  Cleaning up data
    3m 51s
    Sometimes the data you intending to work with contains anomalies, inconsistencies, or adjustments and formatting that have been applied to improve readability for users. Before bringing the data into the Tableau Data Engine, you can use the Data Interpreter tool to perform a cleanup operation on it. FREE ACCESS
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    4.  Splitting fields
    4m 25s
    Splitting fields is a great way of preparing or cleaning up data before you start digging into your analysis and creating visualizations. Tableau can analyze the contents of a field and perform automatic splits, but if you need greater control over the data that is calculated, you can use a custom split. FREE ACCESS
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    5.  Pivoting data
    You can use the pivot tool in Tableau to change the data structure in your table and prepare your data for analysis. The pivot tool allows you to convert your cross-tab data into a columnar structure, which Tableau tends to prefer when working with data. The pivot tool in Tableau Desktop works with Excel, Google Sheets, text files, and PDFs, so if you are intending to work with a different source type, you'll have to pivot your data using a custom SQL query. FREE ACCESS
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    6.  Filtering data at the data source level
    6m 24s
    Data source filtering is useful for restricting data that is used in visualizations, for analysis, user permission, or data security purposes. A Tableau user can set filters at the source level, which once published or shared, will then prevent other users from getting access to or querying any data that doesn't match applied criteria. Extract filters and data source filters work in similar way, with both affecting the data that is brought into the Tableau data engine. However, they are treated separately by Tableau and handled in a specific order of operations. FREE ACCESS
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    7.  Managing data sources
    3m 54s
    Once you have connected and added data sources, there are a number of ways of editing them. You can use the Data Source Page to configure your dataset and connection details, rename existing connections and sources, create data source duplicates, and even close sources that you no longer need. FREE ACCESS
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    8.  Replacing data sources
    4m 31s
    Replacing data sources is useful if you need to change the location of a source without affecting the analysis that you have already done. You can replace sources via the Connection area in the Data Source Page, or change the data source being used in your Tableau worksheets. You should also be aware that default formatting that you've applied in your worksheet will be lost, and that you may need to update references if there is a difference in your field names. FREE ACCESS
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    9.  Refreshing data sources
    5m 13s
    If you want to make sure that you are working with up-to-date data, you are going to need to know what sort of connection you have set up and the data source settings that are active in Tableau. See how to refresh live data sources and data extracts, and append data to existing data extracts. FREE ACCESS
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    10.  Appending data to extracts
    2m 46s
    One way of adding data to a data extract is to use the append tool. This will add the data to the extract in your workbook but will not update the original data source. If you then refresh your data extract, the appended data will be lost. You can also use the Extract History to keep track of the changes being applied to your extract, including refreshes and appended data. FREE ACCESS


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