Automate Data Validation and Cleansing to Leverage High Quality Data
Improve the Quality of Your Data to Make Better Business Decisions
Whether you’re trying to gain an edge over your competition, customize your marketing strategies, or improve your customer relationships, high-quality data is at the heart of every effective business decision.
But data received from disparate sources may need to be checked for consistency and accuracy before it can be used to draw insights. This data is not always in a structured format and therefore it has to pass through a data quality improvement process to achieve better data quality.
Astera Centerprise data quality management software can help you build an end-to-end pipeline to clean, validate, and standardize your data as it arrives from different sources across the enterprise, fixing data quality issues and leaving you with high quality data that can steer your business decisions in the right direction.
Standardize Data Quality for Effective Reporting
Ensure data quality, completeness, and accuracy using regular expressions and the Data Cleanse transformation for effective analysis.
Identify Redundant Records before Processing
Improve data quality and process efficiency by weeding out duplicate entries from the source.
Get a Statistical Overview of Your Data
View crucial details including the number of records processed, minimum and maximum values, and the number of errors identified in any source.
Facilitate Collaboration between Teams
Allow cross-functional teams to make informed decisions by delivering complete and accurate data in real-time.
Improve Data Quality Across Your Systems with Astera Centerprise
Leverage bi-directional connectivity to cloud sources and databases to extract and load high quality data.
Create custom better data quality rules by choosing from dozens of pre-defined expressions.
Remove whitespaces, nulls, and specified characters from fields with various data transformation functions.
Filter and reroute data based on the metrics of your choice for informative reporting.
Automate data validation with job-scheduling capabilities throughout the data quality improvement process
Clean and integrate data from multiple sources including Email, JSON files, and database tables.
