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DataCleaner full changelog

DataCleaner full changelog

DataCleaner 5.2.0 released Jul 14, 2017 (New Release)
Both open source and commercial contain these changes:
IBM's ICU library used for better Unicode standard compatibility.
Hashing component added
Fixed Pentaho plugin
DataCleaner 5.1.5 released Mar 15, 2017 (New Release)
We had a rather bad issue with 5.1.4, so we decided to make a quick release of 5.1.5.
Fixes:
Running DataCleaner on OSX could fail.
DataCleaner 5.1.4 released Nov 10, 2016 (New Release)
BUG FIXES:
Make requirements and scope buttons update properly when job changes
Stability fixes to Union and Coalesce components
Stability fix for Excel writer
DataCleaner 5.1.3 released Sep 19, 2016 (New Release)
5.1.3 is mostly a bugfix release, containing the following fixes:
Remove spurious logging from grouper and UI.
Remove non-functioning view online regex button.
Exported HTML report and monitor graphs should now work properly.
DataCleaner 4.5.3 released Dec 21, 2015 (New Release)
A new filter called Compare has been added. The compare-filter is used to compare two fields, or a field and a fixed value, using a dynamic set of operators such as "Greater than", "Equal" or even "Like" (equivalent to the LIKE operator in SQL).
In the Remove dictionary matches we've added a new output column called "Removed matches". This output column will contain all the dictionary terms that was removed from the inspected string.
A new transformation called Remove substring. This transformation is useful in data standardization scenarios where a substring has been extracted from a larger string, and the larger string needs to be sanitized.
DataCleaner 4.5 released Nov 13, 2015 (New Release)
At the engine and API level we've added the concept of "output data streams", which means that every component can publish streams of data that can be consumed by other components. Users of our API can utilize this feature by implementing the HasOutputDataStreams interface.
If this sounds too technical for you, just appreciate that this capability is underlying the following 4 features/improvements.
DataCleaner 4.0.10 released Sep 24, 2015 (New Release)
So what is new in this release?
We have added support for connecting to Apache Hive via our existing JDBC interface. In addition to the existing Apache HBase connectivity, this is a good first step towards having DataCleaner as a Big Data Profiling engine for your data in Hadoop.
A bug related to version-conflicts in the Apache HBase connector was fixed.
We have made it easier to immediately register new datastores when you need them. For instance when configuring a Table lookup or the Insert into table component.
DataCleaner 4.0.1 released Apr 20, 2015 (New Release)
A new visual way of building jobs instead of navigating though component tabs makes all of the difference for the user and his capabilities. In DataCleaner 4.0 you benefit from a clear picture of how your data is going to be processed.
The canvas not only shows the contents of your job. It also provides hints and guidance while you build it. Modifying the job is a matter of interacting with the nodes in the graph.
DataCleaner 4.0 RC 5 released Mar 9, 2015 (New Release)
The main concern that was addressed in this release was around loading of extensions/plugins. We fixed several issues pertaining to the loading sequence of and visibility of objects within extensions and the main distribution of DataCleaner. If you use extensions, we advise you to upgrade.
Furthermore an improvement to the "Capture Changed Records" filter was introduced - allowing it to work on numerical record version attributes instead of just update timestamp attributes. Lastly the license checking functionality of DataCleaner commercial editions was improved, making it easier to determine what is wrong when a license check is not successful.
DataCleaner 4.0 RC 4 released Feb 27, 2015 (New Release)
The main concern that was addressed in this release was around loading of extensions/plugins. We fixed several issues pertaining to the loading sequence of and visibility of objects within extensions and the main distribution of DataCleaner. If you use extensions, we advise you to upgrade.
Furthermore an improvement to the "Capture Changed Records" filter was introduced - allowing it to work on numerical record version attributes instead of just update timestamp attributes. Lastly the license checking functionality of DataCleaner commercial editions was improved, making it easier to determine what is wrong when a license check is not successful.

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Full DataCleaner 5.2.0 details

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