DataCleaner DataCleaner is a solution for businesses and organizations wishing to measure and increase the quality of their data.
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data data quality component profiling monitor data validation quality component

DataCleaner Description

DataCleaner is a solution for businesses and organizations wishing to measure and increase the quality of their data. DataCleaner is a solution for businesses and organizations wishing to measure and increase the quality of their data. DataCleaner includes functionality to profile and compare data, to validate data against business rules, and to monitor the progression of these measurements over time. It includes both a standalone desktop application for exploring and defining the data quality effort and a Web application for continuous data quality deployments.The field of data quality has been overseen in the IT-business for a long time. Organizations are beginning to feel the pain from inconsistent and flawed systems and interest is being built to support the employment of more ambitious goals as to the quality of our data. To illustrate the concept, let's imagine an information chain typically centered around the process of building a data warehouse. Even though you can employ data quality principles in lots of other scenarios, the data warehouse is the archetypical situation since the data warehouse seeks to create a single version of the truth - and obviously this truth has to be of high quality!The DataCleaner project is a project aimed for working seriously and ambitiously to create a framework for data quality. The goal of DataCleaner in the example above is to help the data warehouse professional to understand the source systems he is working with better and apply the logic of this understanding to both the input and output of his process. This way we ensure our data's quality. Some might even say that we test the data warehouse, just as we test our products for flaws and our software for bugs.So in short...DataCleaner is a data quality component, application and monitor for profiling, validating and comparing data.Known issues:DataCleaner cannot read CSV files with missing values or blank lines. Comma's should be represented on every line, consistently with the CSV-format. What's New in This Release: · Improved Excel spreadsheet support. · Improved SQL Server support. · Improved performance for CSV files. · A fix for a bug that caused certain database connection errors to be ignored in terms of user feedback. · A fix for a bug that caused re-opening of database dictionaries to throw an NPE. · A fix for a bug related to dictionary lookups of null values. · Support for Teradata databases. Connection templates for SQL Server connections. · Selection of file encoding when reading CSV files. · A fix for a minor bug relating to reading files on the classpath when running in Java WebStart mode.

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