Binary file

Overview

A binary file is a computer file that's not a text file, and whose content is in a binary format consisting of a series of sequential bytes, each of which is eight bits in length.

You can use binary files from a Local upload, Amazon S3, or Azure Blob Storage in your data syncs.

Some benefits of using binary files include:

• Better efficiency via compression

• Better Security through the ability to create custom encoding standards.

• Unmatched Speed, since the data is stored in a raw format, and isn't encoded using any character encoding standards, it's faster to read and store.

Example use case

You have a binary file that contains your Employee information. You want to use a batch sync to pull this info into a Cinchy table and liberate your data.

The Binary File source supports batch syncs.

Info tab

You can find the parameters in the Info tab below (Image 1).

Values

Parameter	Description	Example
Title	Mandatory. Input a name for your data sync	Employee Sync
Variables	Optional. Review our documentation on Variables here for more information about this field. When uploading a local file, set this to filepath.	@Filepath
Permissions	Data syncs are role based access systems where you can give specific groups read, write, execute, and/or all of the above with admin access. Inputting at least an Admin Group is mandatory.

Image 1: The Info Tab

Source tab

The following table outlines the mandatory and optional parameters you will find on the Source tab (Image 2).

Source Details

The following parameters will help to define your data sync source and how it functions.

Parameter	Description	Example
(Sync) Source	Mandatory. Select your source from the drop down menu.	Binary File
Source	The location of the source file. Either a Local upload, Amazon S3, or Azure Blob StorageThe following authentication methods are supported per source:Amazon S3: Access Key ID/Secret Access KeyAzure Blob Storage: Connection String	Local
Header Rows to Ignore	Mandatory. The number of records from the top of the file to ignore before the data starts (includes column header).	1
Footer Rows to Ignore	Mandatory. The number of records from the bottom of the file to ignore	0
Encoding	Optional. The encoding of the file. This default to UTF8, however also supports: UTF8_BOM, UTF16, ASCII.
Path	Mandatory. The path to the source file to load. To upload a local file, you must first insert a Variable in the Info tab of the connection (ex: filepath). Then, you would reference that same value in this location (Ex: @Filepath). This will then trigger a File Upload option to import your file.	@Filepath
AuthType	This field defines the authentication type for your data sync. Cinchy supports "Access Key" and "IAM" role. When selecting Access Key, you must provide the key and key secret. When selecting IAM role, a new field will appear for you to paste in the role's Amazon Resource Name (ARN). You also must ensure that:The role must be configured to have at least read access to the source. The Connections pods' role must have permission to assume the role specified in the data sync config.
Test Connection	You can use the "Test Connection" button to ensure that your credentials are properly configured to access your source. If configured correctly, a "Connection Successful" pop-up will appear. If configured incorrectly, a "Connection Failed" pop-up will appear along with a link to the applicable error logs to help you troubleshoot.

Schema

The Schema section is where you define which source columns you want to sync in your connection. You can repeat the values for multiple columns.

Parameter	Description	Example
Name	Mandatory. The name of your column as it appears in the source.	Name
Alias	Optional. You may choose to use an alias on your column so that it has a different name in the data sync.
Data Type	Mandatory. The data type of the column values.	Text
Description	Optional. You may choose to add a description to your column.
Parse Content By (Only for Standard Columns)	Binary File sources have a unique, mandatory parameter for Standard Columns: Parse Content By - Choose from the following three options to define how you want to parse your content: Byte Length - The content length in number of bytes Trailing Byte Sequence - the trailing sequence in base64 that indicates the end of the field Succeeding Byte Sequence - the trailing sequence in base64 that indicates the start of the next field, and thus the end of this one.	Byte Length

Select Show Advanced for more options for the Schema section.

Parameter	Description	Example
Mandatory	If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected If just Mandatory is checked on a column, then all rows are synced with the execution log status of failed, and the source error of "Mandatory Rule Violation" If just Validated is checked on a column, then all rows are synced.
Validate Data	If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected If just Validated is checked on a column, then all rows are synced.
Trim Whitespace	Optional if data type = text. For Text data types, you can choose whether to trim the whitespace._
Max Length	Optional if data type = text. For Text data types, you can choose whether to trim the whitespace._

You can choose to add in a Transformation > String Replacement by inputting the following:

Parameter	Description	Example
Pattern	Mandatory if using a Transformation. The pattern for your string replacement.
Replacement	What you want to replace your pattern with.

Note that you can have more than one String Replacement

Filter

You have the option to add a source filter to your data sync. Please review the documentation here for more information on source filters.

Image 2: Define your Source

Next steps

• Configure your Destination
• Define your Sync Actions.
• Add in your Post Sync Scripts, if required.
• Click Jobs > Start a Job to begin your sync.