2011-06-27 : DataCleaner 2.2: Profiling everywhere

DataCleaner 2.2 has been released as of today! This is an exciting new version of our Data Quality Analysis (DQA) and Data Profiling application that is now a lot more extensible, embeddable and compliant with new datastores.

Here's a summary of the news in this release:

Extensibility
  • The main driver for this release has been a story about extensibility. While releasing the application we are simultaniously releasing a a new DataCleaner website which features an important new area: The ExtensionSwap. The idea of the ExtensionSwap is to allow sharing of extensions to DataCleaner and installation simply by clicking a button in the browser!
  • The DataCleaner extension API has been improved a lot in this release, making it possible to create your own transformers, analyzers and filters. If you feel your extensions could be of interest to other users, please share it on the ExtensionSwap and we provide a channel for you to easily distribute it to thousands of users. The Extension API and the ExtensionSwap is further explained in our new videos for developers and other techies with an interest.
  • We are also releasing a set of initial extensions on the ExtensionSwap: The HIquality Contacts for DataCleaner extension which provides advanced Name, Phone and Email cleansing, based on Human Inferences natural language processing DQ web services. We are also shipping a sample extension which will serve as an example for developers wanting to try out extension development themselves. In the coming months we will make sure to post even more extensions originating from our internal portfolio of tools that we use at Human Inference's knowledge gathering teams.
  • In addition to extensibility we are also focusing on embeddability. We want to be able to embed DataCleaner easily into other applications to make profiling and data analysis possible anywhere! We've created a new bootstrapping API which allows applications to bundle DataCleaner and bootstrap it with a dynamic configuration or run it in a "single datastore mode", where the application is tuned towards just inspecting a single datastore (typically defined by the application that embeds DataCleaner). We already have some really interesting cases of embedding DataCleaner in the works - both in other open source applications as well as commercial applications.

Compatibility
  • We've added support for analyzing SAS data sets. This is something we're quite proud of as we are, to our knowledge, the first major open source application to provide such functionality, ultimately liberating a lot of SAS users. The SAS interoperability part was created as a separate project, SassyReader, so we expect to see adoption in DataCleaner's complimentary open source communities soon too!
  • We've also added support for another type of datastore: Fixed width files. Fixed width files are text files where each column has a fixed width. There is no separator or quote character, like CSV files, instead each line are equal in length and each line will be tokenized according to a set of value lengths.
  • An option to "fail on inconsistencies" was added to CSV file and fixed width file datastores. These flags add a format integrity check when using these text file based datastores.
  • A bug was fixed, which caused CSV separator settings not to be retained in the user interface, when editing a CSV datastore.
  • Japanese and other characters are not supported in the user interface. This "bug" was a matter of investigating available fonts on the system and selecting a font that can render the particular characters. On most modern systems there will be capable fonts available, but on some Unix and Linux branches there might still be limitations.

Other improvements
  • The documentation section has been updated! Ever since the initial 2.0 release the documentation have been far behind, but we've finally managed to get it up to date. There are still pieces missing in the docs, but it should definately be useful for basic usage as well as a reference for most topics.
  • Application startup time was improved by parallelizing the configuration loading and by delaying the initialization of those parts of the configuration that are not needed for the initial window display.
  • The phonetic similarity finder analyzer have been removed from the main distribution, as this was quite experimental and serves mostly as a proof of concept and an appetizer to the community to create more advanced matching analyzers. You can now find and install the phonetic similarity finder on the ExtensionSwap.
  • Cancelled or errornous job handling was improved and the user interface responds more correctly by disabling buttons and progress indicators, if a job has stopped.
  • Fixed a few minor UI issues pertaining to table sizing and use of scrollbars.