Sort columns

To sort the data by a column, select Sort Ascending or Sort Descending from the Data Prep Options dropdown menu.

To sort by several columns at the same time, select Advanced Sort for the first column. Then add additional columns in their sort order.

Sorting columns require that all data columns have the same number of rows. If the column lengths are unequal, you will be prompted to make them equal to proceed.

Change column data type

To change a single column's data type, select Change Type from the Data Prep Options dropdown menu.
  • Change a numeric column to text or date/time.
  • Change a text column to numeric or date/time.
  • Change a date/time column to numeric or text.

Rename column

To rename a data column, select Rename from the Data Prep Options dropdown menu.

Use the following requirements for column names.
  • Use unique names.
  • Use names between 1 and 31 characters.
  • Use names without the following characters: # '
  • Use names that do not start with the following character: *
Note

If you rename a column in the Data Center that connects to an asset in a Dashboard, the asset will not update.

Filter rows

To filter the rows of data to meet a condition, select Filter Rows from the Data Prep Options dropdown menu.

Filter options include the following operators.
  • equals
  • does not equal
  • greater than
  • greater than or equal to
  • less than
  • less than or equal to
  • is missing
  • is not missing

You can also select and right-click an individual value within a cell to exclude or show only that value. In the case of missing values, you can show missing values or show non-missing values.

Filtering rows require that all data columns have the same number of rows. If the column lengths are unequal, you will be prompted to make them equal to proceed.

Note

If you filter rows in the Data Center and sync your data, the Dashboard assets update.

Merge columns

To merge several columns into a single text column, select Merge Columns from the Data Prep Options dropdown menu.

You can merge up to six columns. The new merged text column is added to the end of the columns.

Merging columns require that all data columns have the same number of rows. If the column lengths are unequal, you will be prompted to make them equal to proceed.

Split a text column

To split an existing text column into a series of new text columns, select Split from the Data Prep Options dropdown menu.

To define a split operation, enter a delimiter value as the list separator. By default, the default delimiter value is a comma.

Note

You can create a maximum of 11 new columns from an existing column. If a column contains a list of more than 10 separated values, only the first 10 indexed values are placed into separately created columns. The remaining list items are grouped together into a separate column (the 11th column).

Extract text values from a column

To extract specific text values from an existing text column into a new text column, select Extract from the Data Prep Options dropdown menu.

Extract offers four ways to specify how to extract the information into a new column.
  • Start and end index extracts values that include the first and last index value that you specify and all values in between.

    Suppose you have a date and location code for each invoice identifier and want to extract the month, 20250415PR. In Start Index, enter 5. In End Index, enter 6 for the 2-digit month code, in this case 04.

  • First N characters extracts the first characters from the string.

    Suppose you have a date and location code for each invoice identifier and want to extract the year, 20250415PR. In Number of Characters, enter 4 for the 4-digit year code, in this case 2025.

  • Last N characters extracts the last characters from the string.

    Suppose you have a date and location code for each invoice identifier and want to extract the location code, 20250415PR. In Number of Characters, enter 2 for the 2-digit location code, in this case PR.

  • From list extracts values between the starting and ending index values.

    Suppose you have location information that includes county, city, state, and zip code, and you want to extract the city, Jefferson County, Arvada, CO, 80003. In List Delimiter, enter ,. In Extract at Index, enter 2 for the city, in this case Arvada.

Replace values in a column

To find and replace non-missing and missing text and numeric values that are contained in the specified column, select Replace Values from the Data Prep Options dropdown menu or the column context menu. The validity of the find value is determined by the column's data type and user's regional settings.

For text columns, you can also specify the following options.
  • Require letter casing to match the find value.
  • Require an exact match to the find value. This means that the whole word needs to match in order to replace the value.

Prepend or append values to data values

To add characters to the beginning or end of contents in text columns, select Prepend or Append Values from the Data Prep Options dropdown menu.

In this example, change the column to Text, then prepend the number symbol to the beginning of the claim number.
Note

Append works the same way, but places the text at the end of the data values.

Apply capitalization rules to values in a column

To specify the capitalization format for text values in a column, select Change Case from the Data Prep Options dropdown menu. Select one of the following options.
Uppercase
Capitalize all letters.

For instance, SALES ASSOCIATE.

Lowercase
Do not capitalize any words.

For instance, sales associate.

Proper case
Capitalize the first letter of each word.

For instance, Sales Associate.

Sentence case
Capitalize the first letter of the first word.

For instance, Sales associate.

Delete column

To delete a data column, select Delete Column from the Data Prep Options dropdown menu. You can also select the column and press Delete on the keyboard. To select a column, select the column title cell or the column summary cell.