Data Quality Assurance

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Quality 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…

Accurate

Valid

Complete

Timely

Relevant

Consistent

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.

Business

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

Technology

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

Check if your organization or project need Data QA

Download The checklist

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.

Discovery Workshop

Assessment of your existing data infrastructure and business requirements

Strategy Formation

Designing data quality infrastructure and processes that fit your constraints and organizational structure

Data QA Infrastructure Bootstrap

Utilizing the Provectus prebuilt solution and blueprints to create a foundation for data quality monitoring and observability

Managed Data QA

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.