With CloverDX 6.1 we are continuing to improve CloverDX’s usability for business users. In this release, we focused on data quality and the ability to process large data volumes while still remaining in control of your data.
We’ve added the ability for Wrangler users to validate their data using built-in as well as custom validation rules. This way you can easily validate emails, credit cards, phone numbers or any other values as needed.
Wrangler then collects all information about invalid records at the end of the transformation and allows users to see the reports of validation errors to help them correct the data.
You can also easily share jobs you created in Wrangler by exporting them right from your My jobs table, sending the export via email or even messaging app. The recipient can then easily import the job including data sources and their configuration.
We’ve also implemented additional transformation steps to make it easier for Wrangler users to manipulate their data and made many improvements to overall user experience when editing Wrangler jobs.
With CloverDX 6.1 we’ve finished our transition to Java 11 and Java 8 is no longer supported in any application stack.
Wrangler now allows you to validate your data using new built-in as well as custom rules. You can easily validate emails, phone numbers, credit cards or even custom data using formulas to verify that your transformations work with valid values.
Results of all validations performed by Wrangler – your own rules as well as built-in rules automatically verified by Wrangler – are collected and available for you to inspect. You can see high-level summary reports or even download full details in a “reject file” in CSV or Excel format.
The reject file contains details which allow you to determine why certain row was rejected and follow up on that either by modifying the job to handle the data or by working with source system owners to help them correct their data.
In this release we added several new steps that help you manipulate your data. These steps include date manipulation (Date add/subtract, Date difference and Get part of date) as well as new steps to work with text data (Normalize whitespaces, Propercase and Mask text).
The Mask text step is the first step from our data anonymization collection which we’ll be expanding in the future. It allows you to anonymize sensitive data by masking parts of your data with mask characters (usually star ‘*’ or ‘x’). It allows you to select which characters to anonymize and produces results that are still recognizable but no longer disclose private information:
We’ve also made many improvements to other steps – for example, Delete column(s) step can now delete any number of columns at once.
To share the jobs that you created in Wrangler, you can use our new Export job functionality which is accessible from job’s context menu in My jobs table.
You can then easily send the exported job and the recipient will be able to import everything including data sources and their settings.
OAuth2 connections included in libraries are now shown in library configuration screen in Server Console after the library is installed:
This allows the Server admin to authorize the connection right away in the Server without needing to use the Designer which in turn makes library installation much easier and faster.
This is especially useful when you are publishing data in Data Catalog where you can have quite a lot different connections to variety of cloud APIs.
With CloverDX 6.1 CloverDX Server no longer supports running on Java 8. Following table lists the supported platforms for running CloverDX Server:
To help you install or upgrade to this version, we've prepared a simple checklist:
Before You Upgrade
Designer Upgrade
Server Upgrade
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Error Handling in Wrangler - Rejects
Wrangler Improvements
Libraries Improvements
Miscellaneous
Security
Fixes
Compatibility
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June 27, 2023 | Documentation Download CloverDX 6.1 6.1.0 |