Sudan Finance

Jun 13 2017

The Premier Open Source Data Quality Solution #data #quality #checks, #data #quality #business #intelligence #dataquality #datacleaner #data #cleaner #open #source #opensource #datawarehouse #warehouse #business #intelligence #corporate #performance #management #master #data #profiling #java


Data Quality Analysis Profiling

The heart of DataCleaner is a strong data profiling engine for discovering and analyzing the quality of your data. Find the patterns, missing values, character sets and other characteristics of your data values.

Profiling is an essential activity of any Data Quality, Master Data Management or Data Governance program. If you don’t know what you’re up against, you have poor chances of fixing it.

Duplicate Detection

Avoid operational issues and bad customer experiences by identifying if you have the same persons, companies and products registered multiple times in your databases.

We introduce the latest generation Duplicate detection feature, building on Machine Learning principles for ease of configuration and improved inferential matching.

Duplicate Detection (video)

Data Standardization Cleansing

DataCleaner is built to handle data both big and small. Give everything from CSV files, Excel spreadsheets to Relational Databases (RDBMs) and NoSQL databases a spin!

Use reference data, external and internal, in order to verify that the data values you have correspond to the real world. DataCleaner allows you to build your own cleansing rules and compose them into several use scenarios or target databases. Whether it is simple search/replace rules, regular expressions, pattern matching or completely custom transformations, we support it.

Data Health Monitoring

To manage your data’s quality, you need to monitor it. Monitoring is a central aspect with DataCleaner – to establish the starting point and goals, and to ensure a process of following up on data quality issues.

The monitoring server of DataCleaner enables you to not just make point-in-time profiles of your data, but to schedule periodic data quality checks and receive notifications if quality KPIs get out of control.

A Data Quality Eco-System

Pluggability and Connectivity are keywords for the design philosophy of DataCleaner. The application delivers not only out-of-the-box functionality, but also hosts an eco-system of community driven application extensions, integrations, shared content and more.

Head over to the Discussion Forum to interact with fellow users and developers of DataCleaner. Or check out the ExtensionSwap where you can find plug-in functionality that immediately adds to the value of DataCleaner.

Datalytics is a leading business consulting firm in the South American region. We’re specialized in Data Integration, Data Cleansing, Business Intelligence and Data Mining solutions. We’ve been following your products for some time now, since my belief is that it’s an excellent software and the perfect match for our offering.

– Andrés Eyherabide, Professional Services Manager, Datalytics.

With a tool like DataCleaner you avoid a lot of the common mistakes in doing Data Integration and ETL. You also sometimes able unlock new business value or cost savings because you’re able to identify strange behaviour in your database and improve or utilize this in upstream processes.

– Emilio Arias, Stratebi Business Solutions.

At Platon we use DataCleaner in our Information Management projects as a handy and powerful “swiss army knife” for activities related to Data Quality Analysis, Data Profiling and exploring customer data in general. We have found that the tool provides us with a lot of important analysis features in this process.

– Asbjørn Leeth, Senior Consultant, Platon.

Using DataCleaner and its Duplicate Detection function we identified around 10% redundant contact entries. Furthermore addresses were validated and standardized, so the data quality was lifted making it possible for BestBrains to improve our communication and relations with our large network.

– Jesper Thaning, Partner, BestBrains.

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