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This page outlines your user preferences.
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Your Cinchy Profile has three (3) components that can be changed from user preferences:
My Photo
My Profile
My Password
To add a photo to your profile, complete the following (Image 1):
From My Network, click the avatar icon
Select My Profile
From the settings page click on the my photo image
Locate and upload your photo
From the settings page in the My Profile section you are able to update the language, region, and time zone (Image 2).
If you do not see the password option in my profile, you must be logging on to Cinchy using Single Sign-On and will not need to update your password within Cinchy.
To change your password, complete the following:
In the Old Password field, enter in your existing password
In the New Password field, enter a new password
In the Confirm New Password field, re-enter in your new password
Your Cinchy password must conform to whatever minimum requirements are set by your administrator.
This page provides an overview of the role of the End User in Cinchy.
The “End-Users” of the Cinchy platform are those that apply the functionalities created by the “Cinchy Builders” to their business objectives. This can be employees, customers, partners, or systems. There are two types of end-user: direct and indirect.
Direct Users log into Cinchy via the data browser
Indirect Users (also commonly referred to as "external users") view/edit data via a third-party application/page that connects to Cinchy via API
All Builders are also End-Users, but not all End-Users are Builders.
Cinchy End-Users are able to:
Create and save personal queries. Unlike traditional saved queries made by builders, personal saved queries cannot be shared and are not auto-exposed as APIs.
Use Tables, Saved Queries, and Experiences created by “Builders"
Track version history for the full lifecycle of data
Bookmark and manage data
Access data through application experiences
An end-user can be part of the Administrators group
Cinchy’s Dataware platform features a Universal Data Browser that allows users to view, change, analyze, and otherwise interact with all data on the network. The Data Browser even enables non-technical business users to manage and update data, build models, and set controls, all through an easy and intuitive UI.
Data on the network is protected by cellular-level access controls, data-driven entitlements, and superior data governance. This means that users can only view, edit, or operationalize data that has been granted access to from the data owner (Image 1).
All data is automatically version-controlled and can easily be reverted to previous states with the proper permissions. On all data tables, you can see changes made by users, systems, or external applications through Data Synchronization or by using a Collaboration Log (Image 2).
Users can easily access and run saved queries that are available to them through the Data Marketplace. All queries respect Universal Access Controls meaning you will only see the data that you have access to (Image 3).
Users can also access all accessible tables, queries, and applets through the Cinchy Marketplace. Here you can also order tiles and bookmark favourites (Image 4).
Users can also experience their data through custom application experiences that are created by Builders on the platform. All application experiences also respect Universal Access Controls meaning you will only be able to see the data you have been granted access.
Here is an example Experience (Image 5):
This page details information about the Admin Panel on Cinchy.
You can view the admin panel of your Cinchy instance by using the /admin/index endpoint. This is only reachable if you are logged in as a user with admin access. The admin panel includes the following sections:
The Cinchy Healthcheck shows information about your system such as current version, IP Address, the system time, and your database status (Image 1).
This section shows a list of viewable log files from your system, as well as their size, creation time, and last modified time (Image 2).
Log files in the Admin Panel are only visible on Cinchy deployments on IIS, or on a version prior to v5. In those cases, you will need to navigate to Opensearch (or comparable component).
Review the documentation here for information on uploading a logo.
You now have the option to use personal access tokens (PATs) in Cinchy, which are alternatives to using passwords for authentication. Similar to Cinchy Bearer Tokens, you can use a Cinchy PAT to call the Cinchy API as your current user, meaning your associated access controls will be honoured as well. Cinchy PATs, however, have an expiration date of up to 1 year. A single user can have up to 5 PATs active at one time. See Authentication for details on using a PAT in lieu of a Bearer token.
From the Cinchy homepage, navigate to your User Settings > Tokens. Any tokens that you make will appear here. You will also be able to see any expired tokens.
Click “Generate New Token”.
Note: You can have up to 5 active (non-expired) tokens at a time. Once you reach that threshold, the “Generate New Token” button will not work.
3. Input the following information about your PAT and click Generate:
Token Name
Description
Expiration
4. Once generated, make sure to copy down the PAT somewhere secure. You will not be able to view the PAT again once you navigate away from this screen.
From the Cinchy homepage, navigate to your User Settings > Tokens. Any tokens that you make will appear here.
Click the “Delete” button next to the applicable PAT.
Cinchy PATs can be used in much the same way that Bearer tokens are used for in API authentication. I.E. in the Authorization header with the value: "Bearer <token>".
You may also wish to review the information on using PATs in Excel or PowerBI.
There are several table features that can be used to better view, collaborate and analyze the data in Cinchy tables.
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When you first create a table, a default view called All Data will be created for you under Manage Data. Cinchy builders can create different views for users to manage their data in Cinchy where Views can be filtered and/or sorted according to the requirements.
To switch between views simply select the view from the left navigation toolbar under Manage Data (Image 1).
Users can filter data in a view for one or more columns. Filters persist when users navigate from one view to another. The number of filter criteria is identified against the filter icon (Image 2).
Users can add, remove or rearrange the columns in a view based on how they need the data represented in the View (Image 3).
Click Display Columns in the top toolbar
From the ‘Add a Column’ drop down, locate and select the appropriate column.
Ensure you click ‘Apply’ to save.
Click Display Columns in the top toolbar
Click the “X” to the right of the column name to remove.
Ensure you click ‘Apply’ to save.
Click Display Columns in the top toolbar
Drag the column to the appropriate location in the list of visible columns.
Ensure you click ‘Apply’ to save.
Display Columns do not persist. When you move away from the View, any modifications will be lost.
Users can sort data in a view for one or more columns. Sorting can be done by clicking on a column to sort in ascending or descending order (Image 4).
Sorting can also be done by clicking on the Sorting button and selecting the column(s) to be sorted and the order in which the sorting should occur (Image 5).
Sorting Columns do not persist, when you move away from the View any modifications will be lost.
Scrolling “Top” & “Bottom” allows you to jump from the top to the bottom of a view without scrolling (Image 6).
Row height can be either Collapsed or Expanded using the Row Height drop-down (Image 7).
In addition to the row height selection, you can also manually resize a row (or multiple rows if you select more of them). You can also double click on the default row number on the left to auto expand the row height.
Cinchy allows you to freeze and unfreeze a row/column similar to Excel.
Select the row/column for freezing/unfreezing
Right-click on the row and select Freeze/Unfreeze Row/Column from the menu (Image 8).
This page provides an overview of some of the important pieces of the data browser: the homepage, the login page, and the data network.
Cinchy officially supports Google Chrome and Mozilla Firefox browsers for accessing the data browser.
Once you log in to Cinchy, you'll be on the Homepage (Image 1). From here, you can navigate to a variety of tables, queries, and applets you have access to.
You can return to this page at any time by clicking the Cinchy logo in the top left corner.
All objects you have access to in your Marketplace (including bookmarks) are searchable and can be filtered by typing the partial or full name of the object you are searching for in the search bar (Image 2).
You can also search by object type by clicking on either Tables, Queries, or Experiences in the toolbar.
You can bookmark your most often used objects and rearrange them to your liking within your bookmarks.
To bookmark an object, select the star. The star will be yellow when bookmarked, and grey when not (Image 3).
The object will pop into your “Bookmark” section.To rearrange your bookmarks simply drag and drop the object into the desired order.
You "Network Map" shows a visualization of all tables in Cinchy you have access to and how they are all connected (Image 4).
Each of the coloured circles represents an object in Cinchy. The lines between them demonstrate the links between them.
You are able to search and open tables from this view using the search bar on the left (Image 5).
You can see what the network looked like in the past by clicking and dragging the pink circle along the timeline at the bottom.
You can learn more about you Network Map here.
In Cinchy v5.2 we added the ability to include new parameters on the URL path for your network visualizer in order to focus your node view. You can now add Target Node, Depth Level, and Max Depth Level Parameters, if you choose.
Example: <base url>/apps/datanetworkvisualizer?targetNode=&maxDepth=&depthLevel=
Target Node: Using the Target Node parameter defines which of your nodes will be the central node from which all connections branch from.
Target Node uses the TableID number, which you can find in the URL of any table.
Example: <base url>/apps/datanetworkvisualizer?targetNode=8 will show TableID 8 as the central node
Max Depths: This parameter defines how many levels of network hierarchy you want to display.
Example: <base url>/apps/datanetworkvisualizer?maxDepth=2 will only show you two levels of connections.
Depth Level: Depth Level is a UI parameter that will highlight/focus on a certain depth of connections.
Example: <base url>/apps/datanetworkvisualizer?DepthLevel=1 will highlight all first level network connections, while the rest will appear muted.
The below example visualizer uses the following URL (Image 6): <base url>/apps/datanetworkvisualizer?targetNode=8&maxDepth=2&depthLevel=1
It shows Table ID 8 ("Groups") as the central node.
It only displays the Max Depth of 2 connections from the central node.
It highlights the nodes that have a Depth Level of 1 from the central node.
You can upload a custom logo to appear on your platform login screen and homepage. You will need to have adamin access to do so.
Navigate to <base url>/admin/index
Scroll to the bottom of the admin panel and navigate to the “Upload Logo” button (Image 11).
3. Upload your logo
Once uploaded, your logo is stored in the System Properties table.
Navigate to the table and find the row with Name: Logo (Image 12)
3. Delete the Logo row to remove the logo.
Queries are requests for information within Cinchy.
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and Users have the capability to create ad-hoc queries, however only Cinchy Users can create saved queries. For more information on how to create queries, see
Cinchy Users can execute pre-built queries based on their access.
You can find a list of saved queries on your network by navigating to the Saved Queries table (Image 1). You can then search the Cinchy homepage for the saved query in order to execute it.
You will need "Execute Access" for each Saved Query that you want to run. You can find this information in the Saved Queries table.
Once you have executed the query, click the Grid drop down list and select Pivot. Here is where you can take your standard table view and slice and dice your data (Image 2).
From within your pivot view, open the drop down list with the value “table” and select the type of chart you want to use to display the data (Image 3).
Once you have a desired visualization, that visualization can be made available for others as an applet in Cinchy. Grab the Pivot URL and send it to your Cinchy builder to create your mini applet that can be shared and leveraged!
To copy the Pivot URL to build have a visualization created, complete the following:
From within the Pivot, locate the blue Pivot URL
Click Pivot URL button
Click the Copy button
Send the copied URL to your Cinchy builder to create your applet that can be shared and leveraged!
You can also open that visualization by clicking Open in new tab.
Comments are used in Cinchy to provide context to your data along with providing a means of collaborating directly with and on the data.
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Anyone who can view or edit a cell can comment on it. Any data that is read-only does not allow comments to be entered.
To add a comment:
Locate the desired cell
Right-click and select comment (Image 1).
Enter the comment in the comment window
Click "Comment" to finish
Comments can be modified only by only the individual(s) that have created the comment(s).To edit a comment, complete the following:
Hover over the comment
Click the pencil icon (Image 2).
Make the appropriate edit
Click the Submit button to save the change
Comments can be deleted only by the individual(s) who has created the comment(s).To delete a comment, complete the following:
Hover over the comment
Click the garbage bin icon (Image 3).
A User can archive his own comment regardless of approve permissions
A User with the Approve All permission has the ability to archive any cell comments.
A User with the Approve Select Cell permission has the ability to archive comments on that specific cell
To archive all comments in a cell:
Hover over the comment
Click the Archive All button (Image 4).
You can also archive just one comment in a comment string by clicking the archive icon for the specific comment you wish to archive in the thread.
Comments are stored in the [Cinchy].[Comments] table.
This page outlines some best practices for versioning.
This page details a few best practices concerning version history in Cinchy. These recommendations are important because they can help:
Minimize your database bloat/size.
Make it easier to parse through version history when there aren't hundreds of redundant records.
When doing any type of update statement, it is best practice to include an opposite “where” clause to avoid creating unnecessary history for unchanged values.
For example, if your update was “set name to Marc”, you would include a “where name does not already equal Marc”. Doing so prevents a redundant update in your version history.
When writing an update statement, run it more than once. If it results in an update each time, return to your query and troubleshoot.
This is especially relevant anywhere the statement can be run repeatedly, such as in APIs or Post Sync Scripts.
In data syncs, ensure that your data types are matched properly.
For example, if the source is text and the target is data, even if the values are the same, it will update and create unnecessary version history.
When performing a data sync, run it more than once. If it creates an update each time, return to your configuration and troubleshoot.
This page details how Cinchy approaches Version Management within the platform.
Cinchy natively and automatically manages data versioning in the platform through the ‘always-on’ version tracking, collaboration logging, and recycle bin features (data restore).
Cinchy maintains a version history of all changes to every data element stored in Cinchy. The version history is queryable in Cinchy to accelerate analysis, and can also be viewed through the , which tracks changes made by users, systems, or external applications (Image 1). When required, you can easily revert data to previous states using the or the Revert button.
This section refers to data schemas/models, not data values themselves.
Your schema/data model version can also be managed when you are using multiple environments. For example, if you have a DEV environment and make a change to a table design (ex: changing a column name), you can export and deploy your data model to a PROD environment and Cinchy will intelligently consolidate and merge the schema changes to adhere to the latest version.
This functionality is achieved through the use and synchronization of GUIDs. Each data element in Cinchy (table, column, etc.) will have a matching GUID, which stays consistent even across multiple environments. That means that changes made in your source environment will automatically and accurately be applied once promoted to your higher environment.
A GUID (globally unique identifier) is a 128-bit text string that represents an identification (ID).
You can find the GUID for your object by navigating to the applicable System Table. Ex: Column GUIDs can be found in the Columns table (Image 4).
While you are able to manually export/import data models across environments, you may want to package up multiple objects (tables, queries, reference data, etc.) and push that all together between environments. This method still adheres to schema version control and management.
This page goes over the several ways to work with (enter, update, remove, load and extract) data from Cinchy tables.
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Users are only able to enter data into Cinchy based on their access. Users can also copy and paste data from external sources.
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).
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:
From within the table, click the Import button on the top toolbar of the table (Image 2).
2. Click Choose File to locate and import your file.
3. Validate the imported columns and click next (Image 3).
4. Click the Import button
5. Click the OK button on the Import confirmation window
If there are import errors, click the download button next to Rejected Rows on the Import Succeeded with Errors window (Image 4).
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’.
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.
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:
From within the table, click the Export button in the table toolbar
Select the Export file type (CSV or TSV) (Image 5).
Open your file in Excel, or any other CSV software, to view.
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:
Right-click on the desired row/cell
Select Approve row/cell or Reject row/cell
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:
Open the desired table
Locate the desired row > Right Click > View Collaboration Log (Image 6).
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).
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.
By default, Cinchy does not delete any data or metadata from within the Data Fabric.
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.
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:
From the left-hand navigation, click Recycle Bin (Image 8)
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.
To export a table (i.e. your data model), navigate to the Design Table > Export button (Image 2). You can then import your data model into any other environment using the (Image 3).
This can be accomplished using the Cinchy DXD Utility, which you can learn more about by .
Importing data allows you to add new rows of data into a table. If you wish to perform a sync instead please . Importing data acts as a smart copy-and-paste of new data into an existing table.
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
Click here for more information on & Policies in Cinchy
Audit Logging of data loaded into Cinchy via Data Synchronization such as batch or real-time using the , 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.