What are the benefits of data quality software?
The earlier data quality issues are identified, the easier it is to resolve them. This is because once data is inserted into systems;
- relationships between different data points become formed. Therefore removing a data point can break existing relationships and lead to unforeseen data quality issues.
- strategic and operational decisions are made based on available data. Issues in data quality impact quality of business decisions and ultimately impact a company's success
Data quality systems allow companies to detect and resolve data quality issues before those changes in data are implemented, reducing cost of data quality issues
What are the use cases for data quality software?
Data quality is important for any business process, function or industry that relies on automated decision making systems. Nearly all modern businesses rely on automated decision making systems and data quality software is therefore relevant for almost all modern businesses.
For example, credit scoring and trading systems in finance and recommendation engines in e-commerce are automated decision making systems that are as good as the underlying data.
How does data quality software work?
Data quality issues arise due to improperly formatted, incomplete, incorrect or obsolete data. Data issues arise at the point of observation (e.g. due to faulty hardware), during data communication (e.g. due to issues in the communication channel) or during storage (e.g.overwriting correct data)
Data quality issues can be identified by data quality software as it analyzes existing data, compares data across different tables, databases and systems and compares private data against publicly available data.
Data quality software aims to resolve data quality issues by deleting, modifying or appending records. These can either be done automatically or issues can be highlighted to technical or business personnel.
What is data quality software?
Data quality software supports companies to measure and improve quality of their data. By acting as a single source of information regarding data quality, these software focus the organization on resolving critical data quality issues