9. Once you have completed importing data, Pipeline builder page opens and you can start applying transforms. You can also right-click the stage and choose the Prepare data option and prepare your data in the DataPrep Studio page. Click here to know more about the transforms.

10. Once you are done creating your data flow and applying necessary transforms in your stages, you can right-click a stage and add a destination to complete your data flow.

Note:  After adding a destination to the pipeline, you can try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here.

Advanced selection

To import files using Advanced selection,

1. Click the advanced selection link.

Important: Advanced selection is used not only for incremental fetch. You can also use this option for bulk import of files based on the file pattern. 

2. Provide the following details:

• Bucket name : The bucket name you want to import data from.
  

• Folder path : The folder path where you want to search for files. Eg. 2023/ 
  
  If the files are stored in the bucket without any folder, you can leave this field empty.
  

  

  The "Folder Path" is a directory path field and does not support regex patterns.

  Info: Folder path is case-sensitive.

• File pattern : The pattern used to match the file names in the bucket. This supports regex type matching. You can also use the pattern, ".*" to match any file in the path specified.
  

Info: File pattern is case-sensitive.

Note: The file pattern match is a simple regex type match. For example, to fetch files with file names such as Sales_2022.csv , Sales_2023.csv , Sales_2024.csv , you can input the pattern Sales_.* 

Similarly to fetch files such as PublicData1.csv , PublicData2.csv , PublicData3.csv , use Public.*

If you want to import a single file, then specify the pattern using the exact file name.
Eg: leads_jan_2022.*

• Include subfolders : You can also select the Include subfolders checkbox if you want to include subfolders while searching for a file.
  

• File password : Enter the password if the file is password protected.
• Merge files and import - This will merge all the files that match the pattern specified and import them as a single dataset.
  

  
  

  You can use this option to merge files together during the import itself, without having to perform unions post import.

  Info: This option can merge a maximum of only 5 files at a time.
  Note: If this checkbox is unchecked then, only 1 file will be fetched at a time.
  

  
  
  Eg. If your S3 account has 10 files, the first 5 will be merged into one dataset and imported. During the next reload, the remaining 5 files will be merged and imported.
  
  
  
  Similarly, if your S3 account has 8 files, the first 5 will be merged and fetched first, followed by the next 3. 
  

• File type: Choose the required file format. The available formats are CSV, TSV, JSON, XLS, XLSX, XML, and TXT.
• Sheet pattern: This option is available for the XLS and XLSX formats only. The pattern used to match the sheet names in the file. This supports regex-type matching. You can also use the pattern ".*" to match any sheet in the file.

  
  

  

  The sheet pattern match is also a simple regex-based match. For example, to fetch sheets with names such as Sales_2022, Sales_2023, Sales_2024, you can input the pattern Sales_.*
  

  
  

  Similarly, to fetch sheets such as PublicData1, PublicData2, PublicData3, use Public.*

  
  

  If you want to import a single sheet, then specify the pattern using the exact sheet name.

  Eg: Leads_Jan_2022.*

• Info: Sheet pattern is case-sensitive.
  
  
• Sheet password: This option is available for XLS and XLSX formats only. Enter the password if the sheet is password-protected.
  
• Merge sheets and import: This will merge all the sheets that match the pattern specified and import them as a single dataset.

Note: If this checkbox is unchecked, then only 1 sheet will be fetched at a time. 

Note: Supported formats are CSV, TSV, JSON, XML, TXT, XLS, and XLSX. You can also import files in zipped format.

In the case of Zip files, only one file is supported. Make sure you have only one file compressed or zipped within the .Zip file.

File parsing

File Parsing is the process of interpreting and structuring a file during import so that the data is correctly organized into rows and columns for processing.

In File Parsing, there are two options: Auto Parsing and Custom Parsing.

1. Auto Parsing - Automatically detects the file structure (delimiter, headers, encoding, etc.) and formats the data accordingly.
   
2. Custom Parsing - Allows you to manually configure how the file should be read, giving full control over delimiters, headers, encoding, and other settings.
   

Custom Parsing includes the following options:

• File encoding: You can encode the file using character encoding methods like UTF-8 through the File Encoding option.

• Text qualifiers: You can specify the characters that indicate the beginning and end of a text field, such as Single Quote (') or Double Quote (").

• Delimiter: You can separate or split the data using a delimiter such as Comma (,), Semicolon (;), Space, Tab, or Pipe (|). You also have a Custom delimiter option to define your own separator.

• Skip initial rows: Skip parsing a specified number of rows at the beginning of the file.

• Comment character: Specifies the first character of a commented row. Commented rows will be skipped during import.

• Escape character: Specifies the character used to escape delimiters or quotes so they are treated as plain text. Available options include Double Quote ("), Backslash (), Pipe (|), Carat (^), and Tilde (~).

• Trim spaces automatically: Removes leading and trailing whitespaces from all columns during data import.

• Data contains header: Specify the row number that should be used as the column header.

File parsing options