Cinchy Platform Documentation
Cinchy v5.0.0

Data Management

This page goes over the several ways to work with (enter, update, remove, load and extract) data from Cinchy tables.

Table of Contents

1. Data Entry

Users are only able to enter data into Cinchy based on their access. Users can also copy and paste data from external sources.

2. Insert/Delete Data Rows

Users are only able to insert or delete rows based on their access. If you have the ability to insert and/or delete a row of data it will be visible when right-clicking on a row of data (Image 1).
Image 1: Inserting/Deleting Rows

3. Import Data

Importing data allows you to add new rows of data into a table. If you wish to perform a sync instead please refer to the CLI. Importing data acts as a smart copy-and-paste of new data into an existing table.
Importing the first row of your CSV as a header row will match the headers to the column names within your table. Any columns that cannot be matched will be ignored as well as any columns you do not have edit permissions for.
Users can import data from a CSV file to an existing table in Cinchy. Importing data into a Cinchy table only adds records to the table. This type of importing of data does not update or append existing records
To import data into a table, complete the following:
  1. 1.
    From within the table, click the Import button on the top toolbar of the table (Image 2).
Image 2: Step 1, Clicking the import button
2. Click Choose File to locate and import your file.
3. Validate the imported columns and click next (Image 3).
Image 3: Step 3, validate your columns
4. Click the Import button
5. Click the OK button on the Import confirmation window

3.1 Import Errors

If there are import errors, click the download button next to Rejected Rows on the Import Succeeded with Errors window (Image 4).
Image 4: Import Errors
You will get a file back with all the rejected rows, as well as the 2 columns added called ‘Cinchy Import Errors' and 'Cinchy Import Original Row Number’.

3.2 Cinchy Original Row Number

This provides a reference to the row number in the original file you imported in case you need to check it.
You can simply fix any errors in your error log followed by importing the error log since successful rows are omitted.

4. Export Data

Users are only able to export data in CSV or TSV format. In tables with over 1000 records, you will need to export each page of data separately, or you can use the CLI to export your entire table at once.
When data is exported out of the network, it is now just a copy and no longer connected to Cinchy.
To export data from a table, complete the following:
  1. 1.
    From within the table, click the Export button in the table toolbar
  2. 2.
    Select the Export file type (CSV or TSV) (Image 5).
  3. 3.
    Open your file in Excel, or any other CSV software, to view.
Image 5: Exporting Data

5. Approve/Reject Data

Cinchy has the ability to have data change approvals turned on (configured by builders) when data is added or removed from a table view. A change approval process can be put into place for the addition or removal of specific data. If you have been identified as an "Approval" of data you will have the ability to:
  • approve a cell of data
  • approve a row of data
  • reject a row of data
To approve or reject a cell/row of data, complete the following:
  1. 1.
    Right-click on the desired row/cell
  2. 2.
    Select Approve row/cell or Reject row/cell

6. Collaboration Log

The Collaboration log is accessible from each and every table within Cinchy (including metadata). It allows you to see the version history of ALL changes that have been made to an individual row of data.
To access Cinchy’s Collaboration Log:
  1. 1.
    Open the desired table
  2. 2.
    Locate the desired row > Right Click > View Collaboration Log (Image 6).
Image 6: Step 2, Open the Collaboration Log
Once the Collaboration Log is open you have the ability to view ALL changes with a version history for the row selected within the table.
Users have the ability to revert to a prior version of the record. To do so, click the Revert button for the desired version (Image 7).
Image 7: Reverting Data in the Collaboration Log
There is a potential for a record to have a white coloured Revert button. This indicates that version record(s) are identical to the current version of the record in the table. Hovering over the Revert button will provide a tool-tip.

6.1 Data Erasure and Compression Policies

By default, Cinchy does not delete any data or metadata from within the Data Fabric.
Click here for more information on Data Erasure & Compression Policies in Cinchy

6.2 Audit for Data Synchronization

Audit Logging of data loaded into Cinchy via Data Synchronization such as batch or real-time using the Cinchy CLI, or through data changes by any Saved Queries exposed as APIs to external clients, is recorded the same way as if data is inputted into Cinchy by a User. All data synced into Cinchy will have corresponding line items in the Collaboration Log similarly to how it is handled when data is entered / modified in Cinchy by a User.

6.3 Collaboration Log Performance Considerations

The Collaboration Log data is also stored within Cinchy as data, allowing the logs to be available for use through a query or for any downstream consumers. There are no separate performance considerations needed for the logs as it will rely on the Cinchy platform’s performance measures.

7. Recycle Bin

All data records that have been deleted are put into Cinchy’s Recycle Bin. Data that resides in the Recycle Bin can be restored if required.
To restore data from the recycle bin:
  1. 1.
    From the left-hand navigation, click Recycle Bin (Image 8)
Image 8: The Recycle Bin
2. Locate the row for restoring
3. Right-click and select Restore Row.
The restored row will now be visible in your table.
If Change Approvals are turned on, that row will need to be approved.