Data Quality Management

Data Quality Management

Data is the new currency of business, but inconsistent, incomplete and scattered information leads to wrong decisions. Many companies still rely on Excel as their main repository, which increases the risk of errors, hinders analysis and limits scalability.
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Our no-code/low-code platform allows companies to automate data quality management (DQM), centralize it in one place and eliminate manual operations - all without coding.

Your data, your control - no Excel, no errors.
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With our technology, you can:

• Automatically collect and clean up data - eliminate duplicates, fill in gaps, standardize formats.
• Centralize data in one system - no more scattered Excel files and manual merging.
• Manage data quality in real time - AI detects anomalies and irregularities, ensuring correctness.
  
  * Automate information flow - data goes where it's needed, without manual work.

How it works

• Combine data from different sources - CRM, ERP, Excel, APIs, databases.
• Clean and standardize information - AI detects missing values, incorrect formats, duplicates.
• Define quality rules - no-code allows you to set validation, automatic corrections and data completion.
• Centralize and distribute data - the system directs information to the right departments and applications.
• Monitor quality in real time - alerts in case of anomalies and integration with BI.

Applications for B2C and B2B

• Finance and banking - centralize customer data, eliminate erroneous records, improve reporting.
• E-commerce and retail - unified customer, order and product data across systems.
• Manufacturing and logistics - automation of data exchange in the supply chain.
• Sales and marketing - better segmentation, precise reports, no duplicates in CRM.

Technology that improves data quality

• No-code/low-code - simple data quality rules without programming.
• AI and Machine Learning - detection of errors, anomalies and missing information.
• API integrations - connect to CRM, ERP, data warehouses and other systems.
• Automatic updates and validations - eliminate manual work and increase data integrity.

Data you can trust - no Excel, no errors, no chaos.
Automate data quality management and make better decisions.