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Prepare Excel Files for Ingestion by Using Data Interpreter

Clean your Excel files to make sure that your data has the correct structure for ingestion. The Data Interpreter cleans and structures Excel data during upload. It resolves formatting issues, such as merged headers or blank fields, and ignores non-essential images and hidden formatting.

Required Editions

View supported editions.
User Permissions Needed
To upload data into Tableau Next: Tableau Unmetered Platform Analyst or Tableau Next Platform Analyst permission set
  1. On the workspace tab, select an existing workspace or create one.
  2. Upload the data.
    • From a new workspace, click Connect to New Data, and then click Upload File.
    • From an existing workspace that includes data, click Add, select New Data, and then click Upload File.
    Note
    Note If the Data Interpreter doesn't identify a field’s data type, it automatically assigns a string type to that data.
  3. Select an .xlsx file and click Open.
  4. To resolve formatting issues or create separate subtables, click Run.
    Running Data Interpreter.
  5. Examine detected formatting issues.
    1. Click Review Results (Beta) on the cleaned sheet.
      Reviewing a subtable after the Data Interpreter
    2. Click View Original to view a snapshot of your source file.
      Reviewing a subtable after the Data Interpreter

Supported Data Interpreter Formats

Data Interpreter can identify and resolve the listed data issues during the Excel ingestion process.

  • Merged Headers
    • Combines merged cells into single, unique names for each column.
    • Table with two columns under a merged header.
    • Merged headers resolved.
  • Multi-row Headers
    • Connects information from the top rows to the main column header to keep the correct context.
    • Table with three columns under a multi-row header.
    • Three columns are now split apart.
  • Blank Headers
    • Gives a temporary name to any column that doesn’t have a header.
    • Table with a missing column header.
    • Missing column header resolved.
  • Duplicate Headers
    • Adds a number to column names that are the same to make them unique.
    • Table with duplicate header names.
  • Stacked Tables (Vertical)
    • Separates tables that are one on top of the other if there are two or more empty rows between them.
    • Two tables with separated by multiple rows
    • Previewing one of the separated tables.
  • Side-by-SideTables (Horizontal)
    • Separates tables that are side by side if there are two or more empty columns between them.
    • Side by side tables separated by a column.
    • Previewing one of the separated tables.
  • Empty Columns
    • Removes single empty columns that don’t have any titles.
    • Table with a missing column.
    • Table with with missing column removed.
  • Hidden Data
    • Reads and processes data even if it is in hidden rows or columns.
    • Table with collapsed data.
    • Table with all rows revealed
  • Grouped Data
    • Reads data inside collapsed or hidden groups as normal.
    • Table with hidden data.
    • Table with all data revealed.
  • Conditional Formatting
    • Processes data that has color rules or special formatting applied.
    • Table with a column with conditional formatting showing values ranging from red to green.
    • Table with all conditional formatting removed.

The Data Interpreter ignores the listed data issues to make sure that your dashboard remains clean and focused only on your data.

  • Page Layout Breaks
  • Object Linking and Embedding (OLE)
  • Charts and Images
  • Rich Text
  • Extra Text
  • Hyperlinks
  • Filters
  • Frozen Panes
  • Comments