DQC for Sales Data
No more forgone revenue due to bad sales data
Stop manually checking and correcting customer master and sales transactional data in one-off projects. Fix and maintain your data with the DQC AI and human control.
DQC IMPACT
High-quality sales data is a must-have.
Daily challenge
Customer master data is generated by sales experts who prefer selling over maintaining data - but the customer data is important for many stakeholders.
Risks and losses
Unreliable customer master data hurts the business.
Success with DQC Platform
- 100% data quality fit for purpose
- 35x+ faster issue remediation
- \>1M€ cost saving in year 1
- \>5M€ additional revenue potential
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Calculate the [**cost of bad Sales Data**](/roi)
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Built on 3 pillars
DQC Platform for 100% fit-for-purpose sales data
1) Find data issues with AI.
- Set up data quality rules with the help of DQC AI agent
- Import any rules, requirements, or issue descriptions in natural language or as code in seconds
- Find issues in the data and let the AI agent document everything for you
2) Fix data at source with AI + human experts.
- Generate AI suggestions for data corrections and enhancements
- Fix issues at source with subject matter experts in full control
- Track the change history for complete visibility
- Observe data quality improve over time
3) Prevent issues at source.
- Use all DQC data quality rules via API or SDKs
- Embed the DQC data quality rules directly in your product management system
- Prevent data issues in real-time in source systems
Stop bad data from flowing through your data pipelines / ETL processes
Companies Can Generate Value by Improving Their Data
Dealing with data quality issues at the source lets businesses start with a strong foundation and make the most of GenAI, DQC’s Dr. Michael Spira explains.