Data quality is an essential but tricky task. CloverDX's data quality features discover and deal with bad data fast. With our platform, automate:
CloverDX helps you make better decisions with more trustworthy data.
Replicate similar data quality procedures with ease using CloverDX. Define them once in a custom CloverDX component and share them across your teams.
Automatic error detection can pick up problematic data, avoiding future manual corrections.
With CloverDX's native and custom components, you can define data validation rules and build them into your workflows. The process is easy - simply drag and drop the components.
CloverDX's capabilities allow you to integrate with other sources (e.g. master data databases) for better data quality.
Insert error-handling processes into your workflows and reduce instances of bad data disrupting your data flow.
Identify it, fix it, or remove it from the pipeline altogether. Once the data owner checks it, you're good to go. And once you fix the errors, you can feed the corrected data back in.
With CloverDX's error reporting, even non-technical users can resolve problems efficiently. They can see which records contain errors and what the error is pull them into an Excel file, and send them to an expert to fix.
CloverDX has data quality functionality built in, so you can implement data quality steps into your workflows easily.
Data filtering components check for invalid records as they come in and filter out any that don't meet your defined rules. This ensures better data quality further down your pipeline.
CloverDX's Validator component contains pre-built and customizable rules. These repeatable and shareable rules ensure your data meets your quality standards.
Instantly analyze your data as it flows through the CloverDX ProfilerProbe component. These measures make profiling accessible throughout even the most complex data workflows.
An expanding logistics company struggled with its address data. Different languages, alphabets and address structures were hard to work with. So much so, a dedicated team needed to manually verify the addresses to meet the company's delivery deadlines. But as the volume grew, the team couldn't keep up.
A data validation and cleansing framework, built on CloverDX, resolved their issue. The framework interfaces with third-party systems (e.g. Google Maps) to verify and repair 90% of addresses automatically. The team can now modify rules to support additional countries without the need for more coding.
This marketing company's customer contact details were inconsistent, duplicated and dispersed. With CloverDX, they underwent a data quality audit. Email addresses and phone numbers were automatically verified, deduplicated and enriched with external sources. The end result was a clean database, reduced in size but increased in quality. This change led to more efficient targeting, resulting in more orders and huge cost savings.