Encoding: pick data encoding for your file. Encoding determines how characters are stored in text files and picking incorrect encoding can result in incorrectly read data (for example, some accented letters may show incorrectly). The most common encodings are UTF-8 (universal encoding that can handle any characters), windows-1252 (US English encoding commonly used for files created on Windows), or ISO-8859-1 (US ASCII encoding).

Delimiter: allows you to select column delimiter. A column delimiter is a single character that serves as a separator between columns in the file. The most common delimiters are comma (",") and tab. You can also type your delimiter if none of the default delimiters work for you. Setting a correct delimiter ensures that all columns are read from the file as expected.

Quoting: determines whether values in your source file are enclosed in quotes or not. You can select from three options - double quotes, single quotes, or N/A (no quotes).

First line is a header: tell the CSV connector that it should interpret the first line of the data as a header and read the names of columns from it. If this is unchecked, columns in your data set will have sequentially generated names like field1, field2, and so on.

Files of any size. There is no limit to the total number of rows in your file. Note that by default only the first 1000 rows are shown in the preview. To ensure the whole file is processed, run the job once you are finished building the transformation.

Files with any number of columns. While there is no technical limitation to how many columns can your files have, Wrangler implements a soft limit set to 1000 columns by default to help you prevent cases where your browser may not be able to handle displaying too large of a sample. You can change this limit by contacting your CloverDX Server administrators and asking them to increase the value of Wrangler.MAX_NUMBER_OF_COLUMNS property.

Files with varying numbers of columns on different rows. Your files do not have to have the same number of columns on each row. However, this feature works correctly only when the header or one of the sample rows is the longest row in the file. For example, the connector will work fine if your header contains 20 columns but some of the rows in your file contain fewer than 20 columns. By default, the connector will read the first 512 kB of your data or the first 1000 rows whichever comes first to determine how many columns your data has. You can work with your CloverDX Server administrators to increase these limits by setting CSVAnalyzer.BYTES_TO_ANALYZE and CSVAnalyzer.LINES_TO_ANALYZE settings (see more here).

Files in which the longest row (a row with the largest number of columns) does not appear within the analyzed sample. For example, if you have a file that has a header with 20 columns and much later in the file (after the first 1000 rows) you have a record with more than 20 columns. See above for more details about increasing sampling limits.

It does not support files with multiple different types of column delimiters. If you have such a file, you will need to pick one of the delimiters and then split the columns using the other delimiter in your Wrangler job using the Calculate formula step.

Sheet name: defaults to the first sheet name found in the loaded Excel file. If you want to read data from a different sheet, select it from the list or type it in. You can also use sheet numbers - note that the numbering starts with 0 (i.e., the first sheet number is 0, the second sheet number is 1, etc.).

Coordinates of the first data cell: defaults to A1; i.e., the typical first position in Excel files. To change it, type in the desired start cell (e.g., C1).

First line is a header: selected by default. When selected, the data in the first row are used as column names. When unchecked, the header names default to column positions (ColumnA, ColumnB, etc.).

Read numbers as raw decimals: when this option is checked, all numbers are read as decimal numbers even if they are integer. In some cases, this can help you get complete data from your Excel file. For example, if you have a file where you have many integers in a column at first and later decimal places, the file scanner may only see the integer values and decide that the column is integer even though it should have been read as decimal - this would lead to loss of data since non-integer numbers would only have their integer portion read.

Files of any size. There is no limit to the total number of rows in your file. Note that by default only the first 1000 rows are shown in the preview. To ensure the whole file is processed, run the job once you are finished building the transformation.

Files with any number of columns. While there is no technical limitation to how many columns can your files have, Wrangler implements a soft limit set to 1000 columns by default to help you prevent cases where your browser may not be able to handle displaying too large of a sample. You can change this limit by contacting your CloverDX Server administrators and asking them to increase the value of Wrangler.MAX_NUMBER_OF_COLUMNS property.

Files with varying numbers of columns on different rows. Your files do not have to have the same number of columns on each row. However, this feature works correctly only when the header or one of the sample rows is the longest row in the file. For example, the connector will work fine if your header contains 20 columns but some of the rows in your file contain fewer than 20 columns. By default, the connector will read the first 1000 rows to determine how many columns your data has. You can work with your CloverDX Server administrators to increase these limits by setting CSVAnalyzer.BYTES_TO_ANALYZE and CSVAnalyzer.LINES_TO_ANALYZE settings (see more here).

If you are a Data Manager administrator, you will be able to read any data set (since as Administrator you can give yourself access to any of the data sets).

If you are not Data Manager administrator, your permissions are based on permissions on each data set. You will only be able to read reference data sets where you are configured at least as a Read-only user (i.e., you must be Read-only user, Editor, Approver, or Administrator on given data set).

ID (integer): unique identifier of the row, this id is assigned by the Data Manager when the row is inserted into the data set.

Enabled (boolean): whether the row is enabled (true) or not (false).

Created timestamp (date): date and time when the row was inserted into the data set.

Last approved timestamp (date): date and time when the row was last approved.

Approved by (string): name of the user who last approved the row.

If you are a Data Manager administrator, you will be able to read any data set (since as Administrator you can give yourself access to any of the data sets).

If you are not Data Manager administrator, your permissions are based on permissions on each data set. You will only be able to read transactional data sets where you are at least an Editor (i.e., you are Editor, Approver, or Admin on given data set).

Data source name: name of the data source

Read rows with status: only rows with the select status will be read by the data source. Following statuses are available:

Include hidden and system columns: select whether to add hidden and system columns to the data layout of the data set for this connector. By default, these columns are not included. When selected, the following additional columns will be added to the data set:

Include deleted rows: configure whether to include deleted rows or not. Deleted rows can have any status. They can be distinguished from the other rows by the value of the Deleted column (which can be added to the data set with the previous option). By default, deleted rows are not read from the data set.