Data Quality Assurance
Maintain control over your data quality to ensure the accuracy and validity of analytics, insights, and decision-making delivered by your ML models and AI solutions.
Let's talkQuality data means accurate ML models, robust AI solutions
Data is a critical asset for any enterprise looking to take advantage of complex analytics, AI, and machine learning. To tap into the insights stored in data, companies need to ensure that their data is clean, valid, and accurate, which poses a major challenge from a business and technology perspective. Provectus' Data QA team can help your organization get a clearer understanding of data needed for your AI solutions and ML models, and ensure that your data is ready to power your AI initiatives across your organization.
What Is Data QA?
Data quality assurance is the process of data profiling, to discover inconsistencies and other anomalies within data, as well as data cleansing activities to improve the data quality.
High-Quality Data Is…
Benefits of Data QA
The most advanced algorithms compete for improved accuracy within a fraction of a percent, while data cleansing contributes 20x more to the quality of the final AI/ML solution.
- Better informed decision-making due to more accurate ML models
- Easier implementation of data across different departments for business insights
- Better data quality means faster discovery of business opportunities and a tighter grasp on the market
- High-quality data can lead to increased profitability due to more efficient allocation of company resources
- The earlier the errors in data are detected, the better the accuracy for ML models
- Even small unmanaged errors made in the early stages of workflow can lead to significant degradation of a model's performance in production
- Metrics computed during model testing measure not only the models and algorithms in isolation, but the entire system, including data and its processing
Why Provectus?
Provectus is an AWS Premier Consulting Partner with Data & Analytics Competency
Our Data QA team has a proven track record of success in providing data quality consulting services. We fully own the data quality assurance lifecycle, to ensure that your data is not at risk of being distorted or compromised through data profiling, removal of obsolete information, and data cleansing.
Data Quality Consulting Services
Our data quality consulting services help clients to keep data accurate, unique, valid, complete, timely, and consistent. With our 4-step Data QA methodology, you can rest assured that your data is ready for developing robust AI solutions, training accurate ML models, and running analytics that bring value to your business.
Assessment of your existing data infrastructure and business requirements
Designing data quality infrastructure and processes that fit your constraints and organizational structure
Utilizing the Provectus prebuilt solution and blueprints to create a foundation for data quality monitoring and observability
Defining SLAs and iteratively automating data quality assurance end-to-end, to meet business requirements
Provectus Data QA Solution
By implementing an auditable, AI-ready Data QA system, Provectus enables organizations to ensure robust data governance, strict data management, accurate data collection, and careful design of data control tools.
Thought Leadership
Developer Resources
Check out our collection of Data QA tools on GitHub
