Data Quality Assurance Services: Powering Confident Decisions
Bad data leads to bad decisions — and it’s costing you more than you think. We help you detect, fix, and prevent data issues so you can operate with confidence and clarity.
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Top 1%of software development companies on Clutch
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EU GDPRcommitment to security & privacy
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60%of business is based on customer referrals
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ISO 27001data security certification by Bureau Veritas
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EY EoY 2023EY Entrepreneur of the Year in West Sweden
Messy Data, Missed Opportunities? Clean It Up with Confidence
When data drives your decisions, poor data quality can quietly sabotage everything — from customer insights to strategic planning. Many businesses hesitate to invest in data quality assurance or data quality engineering due to concerns about cost, complexity, or skepticism around ROI. But in reality, bad data is far more expensive. Addressing quality early reduces firefighting later, simplifies integration across tools, and turns your data from a liability into a reliable growth driver.
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Confident Decision-Making
High-quality data provides a consistent foundation for analytics and business intelligence. You can make strategic choices faster, with fewer doubts and delays. -
Streamlined Operations
Messy data — like duplicates, missing info, or inconsistent formatting — can really bog things down. With the right quality checks in place, your systems run more smoothly and your team wastes less time fixing avoidable issues. -
Stronger Compliance and Reporting
Regulatory audits and data-driven reporting require accuracy and transparency. Clean data reduces the risk of penalties and ensures smoother review processes. -
Better Customer Experiences
Inaccurate data leads to failed deliveries, irrelevant messaging, and customer frustration. With accurate profiles and interactions, you can meet expectations and build loyalty.
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Our Data Quality Assurance Services
We offer data quality services that flex around your needs — whether you’re cleaning up legacy systems, rolling out new pipelines, or helping your team build the right skills. Whatever the setup, we’ll work with you to make sure your data is consistent, complete, and actually useful.
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Data Quality Audits
We assess the current state of your data across key systems and identify critical issues like duplicates, missing values, or inconsistencies. This gives you a clear picture of where quality gaps are and what’s needed to close them.
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Ongoing Validation & Monitoring
We implement automated checks to detect errors in real time and monitor key quality metrics over time. This helps you prevent data decay and catch issues before they impact operations.
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Rule-Based QA Framework Design
We work with your team to define custom validation rules and metrics that align with your business logic. These frameworks make your QA process repeatable, scalable, and easier to maintain.
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Data Pipeline QA Integration
We integrate quality checks directly into your existing pipelines and tools — whether you’re using custom solutions or platforms like Airflow, dbt, or Snowflake. This keeps your QA process efficient and low-friction.
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Manual QA and Data Operations Support
When automation isn’t enough, we provide trained specialists to handle complex validations and ongoing data handling. This is especially useful for nuanced tasks like enrichment, classification, or categorization.
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Custom Workshops & Team Training
We design tailored workshops to upskill your team in data QA best practices, tooling, and workflows. Your team learns by working with your actual data and systems — no generic content or one-size-fits-all material.
Let’s find the right mix of data quality services to support your team and goals
Flexible Cooperation Models for Your Data Quality Testing
Work with us in a way that fits your team — whether you need long-term support, help with a specific project, or custom training. We’ll shape the collaboration around your goals, workflows, and how your team likes to get things done.
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Dedicated Development Teams
Direct communication and controlGet a QA team that feels like part of your own. We build the team around your tools, workflows, and goals — so they can jump in and start adding value right away. It’s a great option if you’re looking to grow your internal capacity without stretching your core team too thin.
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Project-Based Solutions
End-to-end supportIdeal for tackling specific challenges like data audits, pipeline QA integration, or tool setup. We tailor the scope, timeline, and deliverables to your business context and existing infrastructure. You get focused outcomes with clear timelines and minimal disruption to your operations.
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Custom Tech Workshops
Hands-on team trainingUpskill your internal team with training that reflects your actual data, tools, and challenges. Our data quality consultants design workshops from scratch — no off-the-shelf content or filler. Each session is built to deliver practical skills your team can apply immediately.
Technologies & Tools We Use
We work with a wide range of tools and platforms to fit seamlessly into your existing data infrastructure. From validation frameworks to data pipeline tools, we select technologies that support scalable, maintainable, and high-quality data operations.
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Data Integration & Pipelines
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Apache Airflow -
dbt -
Fivetran -
Apache NiFi
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Data Validation & QA Frameworks
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Great Expectations -
Deequ -
Soda -
dbt tests
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Data Storage & Processing
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PostgreSQL -
BigQuery -
Snowflake -
Redshift -
Spark
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Monitoring & Observability
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Datafold -
Monte Carlo
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Prometheus + Grafana (for custom metrics)
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Data Quality Assurance vs. Data Governance: Complementary, Not Interchangeable
Think of data quality assurance and data governance services as two sides of the same coin. QA is all about making sure your data is accurate and usable, while governance focuses on the bigger picture — who owns the data, how it should be handled, and what the rules are. They do different jobs, but together, they help you get the most value out of your data.
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Data Quality Assurance
- Error detection & correction. Data QA is all about spotting and fixing problems like missing info, duplicates, or messy formatting. It helps keep your data accurate, consistent, and actually useful for everyday work. That usually means a mix of automated checks, hands-on reviews, and regular updates to keep things on track.
- Operational focus. QA activities are typically embedded in the data pipeline, running alongside ingestion, processing, and analytics. The goal is to maintain high data reliability as part of routine workflows. It’s hands-on, practical, and tightly linked to business output.
- Frameworks & tools. QA relies on technical frameworks that define validation rules, anomaly detection logic, and error thresholds. These tools are designed to catch issues in real time or during scheduled audits. They provide immediate feedback and help teams react quickly to problems.
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Data governance
- Policy & ownership. Governance defines who owns which data, who can access it, and how it should be used. It establishes clear roles and responsibilities to prevent chaos and improve accountability. Without governance, data initiatives often struggle with ambiguity and inconsistency.
- Strategic oversight. Unlike QA, governance operates at a higher level, aligning data practices with legal, ethical, and business requirements. It supports compliance, risk management, and long-term planning. This makes it essential for organizations that handle sensitive or regulated data.
- Structure for QA to operate. Good governance creates the foundation on which effective QA can run. It defines the standards and expectations that QA tools and processes aim to uphold. Together, governance and QA form a feedback loop that reinforces both control and quality.
Get Matched with Skilled Data Quality Assurance Specialists
Whether you’re building a team from scratch or filling a specific role, we’ll connect you with vetted data quality consultants who fit your technical and domain needs. From data analysts to QA engineers, each candidate brings hands-on experience in maintaining reliable, production-ready data systems.
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$29/h
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$67
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$34/h
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$66
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$55/h
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$40/h
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$35/h
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$38/h
A Proven Process for Reliable, High-Quality Data
Our approach to data qa is flexible yet methodical, designed to fit your systems while addressing the root causes of data issues. We focus on long-term quality — combining automation, manual validation, and collaboration to make your data trustworthy and actionable.
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Discovery & Scoping
We begin by examining your current data architecture, systems, and sources to understand where quality issues arise. In this stage, we also align with your team on business objectives, compliance requirements, and the data types that matter most. This initial discovery helps us define clear priorities and set expectations for delivery, timelines, and team roles.
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Data Mapping & Quality Assessment
Next, we map out how your data flows through systems — from ingestion to storage to reporting. We document data sources, transformations, and touchpoints to get a full picture of how and where inconsistencies can occur. Based on this map, we run a thorough audit to identify gaps, outdated records, duplicate entries, and structural issues that could compromise downstream use.
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Rule Definition & QA Framework Design
With your business logic and use cases in mind, we co-create a tailored set of validation rules and thresholds. These rules reflect not just general best practices but the specific patterns, tolerances, and needs of your data environment. We also design the overarching framework — deciding where QA will be automated, how exceptions are handled, and how results will be communicated.
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Tooling & Workflow Integration
Once the framework is in place, we bring in the right tools to operationalize it — whether through existing platforms like dbt and Airflow or custom scripts and configurations. The goal here is seamless integration: quality checks that run where your data already lives, without slowing things down. We also provide technical documentation and guidance so your team can easily maintain or scale the solution.
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Testing & Iteration
We test the framework on live or production-like data to validate rule logic, thresholds, and alerts. During this phase, we work closely with your stakeholders to interpret results, adjust for edge cases, and refine workflows. This collaborative feedback loop ensures the system is not only accurate but also practical for day-to-day use.
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Monitoring & Continuous Improvement
After deployment, we help you establish ongoing quality controls, including automated alerts, scheduled audits, and trend dashboards. These tools help catch new issues as they emerge and highlight patterns before they become problems. We remain available for periodic tuning or new rule development as your systems and data volumes evolve.
Data Quality Assurance Solutions, Tailored to Your Industry
Different industries face different data challenges — from strict compliance demands to rapidly scaling datasets. We bring deep domain knowledge and adaptable QA practices to help you manage complexity, reduce risk, and get more value from your data.
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HealthTech
Clean, reliable data is essential for accurate diagnoses, treatment planning, and regulatory compliance. We help healthtech companies maintain high-quality datasets across patient records, medical devices, and analytics platforms. Our QA practices support both clinical accuracy and audit readiness.
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GreenTech
Impact measurement and sustainability reporting depend on trustworthy environmental data. We work with greentech companies to validate sensor outputs, normalize datasets from diverse sources, and reduce errors in climate modeling or energy tracking.
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FinTech
In fintech, data integrity isn’t optional — it’s a core requirement for compliance, fraud prevention, and customer trust. We help clean and validate financial records, transaction logs, and customer data pipelines. Our work supports faster audits, smoother onboarding, and reduced operational risk.
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E-Commerce
Inconsistent product listings, duplicate entries, and messy customer data can undermine both sales and analytics. We help e-commerce platforms structure and maintain clean catalogs, customer records, and behavioral data. Clean data also enables smoother integration with marketing, CRM, and inventory systems.
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Logistics & Mobility
Real-time decisions depend on accurate data from vehicles, warehouses, and tracking systems. We help logistics companies validate incoming data streams, flag inconsistencies early, and improve cross-platform integration. This strengthens supply chain visibility and supports data-driven route and inventory optimization.
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EdTech
Learning platforms rely on clean usage data, content metadata, and performance metrics to personalize experiences and improve outcomes. We work with edtech providers to audit, structure, and validate their data pipelines. The result: better decision-making, stronger product development, and improved learner engagement.
Let’s explore how we can tailor data quality solutions to your industry
Why Choose Beetroot for Data Quality Consulting Services?
We bring more than technical expertise — we bring long-term thinking, local engagement, and a strong commitment to responsible, people-centered tech. With deep experience in data-heavy environments, our team helps you achieve high data integrity while aligning with your business goals.
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Built for long-term impact
We don’t just fix today’s data problems — we help you build sustainable, scalable systems that improve over time. Our teams integrate fully with yours, creating consistency, trust, and shared knowledge.
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Deep expertise in data ecosystems
From ingestion to processing to analytics, we understand the full data pipeline. This makes us uniquely positioned to identify quality gaps and build tailored QA solutions that work within your architecture.
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Human-centered development
We prioritize transparency and collaboration, keeping your team involved throughout the QA process. This helps build internal alignment and promotes better adoption of data practices.
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Embedded teams with strong local roots
Our hubs in Sweden, Ukraine, Bulgaria, Poland, and Vietnam allow us to assemble highly qualified, culturally diverse teams, united by Nordic business values. You get the benefits of nearshoring with strong communication, team retention, and a shared sense of purpose.
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Ethical and future-proof by design
We’re committed to ethical AI and data use, integrating best practices in governance and transparency. Your data systems will be ready not just for tomorrow’s opportunities, but also for tomorrow’s standards.
What Our Clients Say
From long-term partnerships to focused data initiatives, our clients trust us to deliver with care, consistency, and technical expertise. Hear how we’ve helped teams grow, streamline operations, and build solutions that stand the test of time.
Featured Cases
From fixing critical inconsistencies to building automated quality checks, our work has helped companies turn messy data into a trusted asset. Explore how we’ve tackled real-world data challenges across industries.
Custom Workshops to Elevate Your Data Team’s Capabilities
Your data challenges are unique — your training should be too. Custom workshops help your team build practical skills that directly support your business goals, without wasting time on irrelevant content. We tailor every session to fit your context, making the learning immediately actionable and impactful.
- Tailored to your tech stack and data flows. We adapt every workshop to reflect your actual data environment — no generic content or off-the-shelf examples. Your team learns by working with your own systems, tools, and use cases.
- Upskill for lasting quality improvements. Customized training helps your team spot and resolve data issues earlier, reducing long-term maintenance costs. The result: fewer errors, smoother collaboration, and better use of internal data assets.
- Bridge the gap between tools and people. We help teams understand not just how tools work, but how to work with them more effectively. Our workshops align processes with business needs, improving data ownership and accountability across departments.
Let’s solve your data challenges together!
Have a project in mind or just exploring options? Fill out the form and we’ll connect you with someone from our team to discuss how we can support your goals with tailored data quality services.
