How To Select The Best Data Quality Tools?
If the right information is available at the right time, the ability of the organization to perform analysis, take best business decisions and create strategies get enhanced. If the organization aims at enhancing all these capabilities, maintaining a data quality standard is a must for it. Getting a quick access to data and fetching a quality of information is possible when the data quality methods are properly defined and implemented in the organization. Standard data quality management capabilities and best data quality tools for enterprises help the organizations to meet their goals.
There is a good number of data quality tools available in the market now and it is honestly a challenge to select the best data quality tools for your organizational data quality needs. There are various dimensions of a data quality management strategy which are accuracy, consistency, integrity, validity, completeness, cleanliness, accessibility, profiling and relevancy. These all dimensions of data quality management should be properly addressed by data management efforts done by data quality tools. Let us go over the capabilities which should be present in the best data quality tools you are going to select.
Data governance capabilities should be there in the quality tools you select. It includes reference data, content definition, databases, calculation engines and reporting techniques. Different individual business units generally implement their own data quality solutions but a common enterprise data quality solution should create a uniform platform for data management and a source for complete reporting across the groups.
Users should be engaged throughout the complete development cycle and a trust in the architecture and its implementers should be built across the organization. In the context of data architecture, some key features to look in a data quality tool are-
- A good support for the enterprise framework as selected by the organization
- Representing models in a way that helps non technology stakeholders to relate well
- Meta models support
- Requirement traceability support
- Multi user collaboration support and other enterprise support features.
Most Important Qualities of Best Data Quality Tools
The data quality management features to look out in data quality tools are-
- Defining data profiling rules
- Evaluation of the profiling rules
- Defining data cleansing rules
- Auditing of cleansed rules
- Creating and implementing data standards which are specific to the organization
- Maintaining these rules to correct data source systems through the lifecycle of data management process
Master Data Management
MDM system in data quality tools should maintain the data hierarchies, auditing, versioning, single and multiple copies and continuous merge. The selected data quality tool must accommodate all the requirements for master data management needed in the organization.
- Extracting data from various layers and report it wherever required
- The key features to look in the best data quality tools are the abilities which include-
- Specification for the mappings and reports which are impacted due to change in database structures
- Providing specific reports assisting data architects to maintain complex data warehouse systems.