Data Quality ROI Calculator
The ultimate tool to estimate how much bad data is costing you — and how much you could save.
Calculate the hidden costs of poor data — and uncover the ROI of fixing it.
Every company suffers from bad data — but very few can measure what it really costs.
From wasted time to customer churn, hidden rework to compliance risk, poor data silently eats into your margins.
Use our free ROI calculator to estimate the financial impact of data issues across your business.
It takes less than 3 minutes.
Tale of Data offers this calculator to estimate the cost of poor data quality within your company or department.
What Is the ROI of Data Quality?
Data Quality ROI refers to the measurable business return you get from improving your data.
It can take the form of reduced costs, increased productivity, better customer retention, well-informed and prompt decisions, or fewer compliance risks.
This page helps you quantify those returns, starting from the hidden costs of poor data.
Use This Calculator to Estimate the Real Cost of Bad Data
Most companies suffer from poor data — duplicate records, manual rework, bad reporting — but struggle to put a number on it.
Our ROI calculator lets you simulate how much this is costing you each year across operations, staff, and customer experience.
Start using it right away above — no email required.
How to Calculate the ROI of Data Quality Improvements
ROI = (Estimated Benefits – Costs of Improvement) / Costs
But quantifying the benefits can be tricky without a structured approach.
That’s why we break it down by category:
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Staff time wasted on corrections
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Revenue lost due to errors
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Compliance and risk exposure
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Operational inefficiencies
Our calculator guides you through each of these dimensions — with inputs you can adjust to fit your business reality.
Justify Your Data Quality Budget With Real Numbers
Data leaders often know the problems, but lack financial metrics to get leadership buy-in.
This tool gives you:
- Hard numbers to present to CFOs, CIOs, or board members
- A credible business case for investing in remediation, governance, or observability
- A way to compare the cost of inaction vs. the cost of improvement
What’s Included in This ROI Simulation?
We’ve structured the calculator around 6 key areas where poor data impacts your business:
- Time and salary costs due to manual corrections
- Productivity losses from missing or inconsistent data
- Customer dissatisfaction and churn
- Repeated operations due to wrong or missing information
- Compliance risks (fines, audits, delays)
- Poor decisions based on inaccurate KPIs or reports
These reflect real use cases from finance, insurance, public sector, and retail.
Turn Insight Into Action - Tale of Data
Now that you’ve estimated the cost of poor data, the next step is solving it — quickly and at scale.
Tale of Data is the all-in-one platform to do just that.
We help organizations move from awareness to execution by offering a comprehensive, AI-powered, no-code platform that turns data chaos into business value.
With Tale of Data, you can:
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Detect issues instantly with automated quality checks and flash audits
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Fix data with remediation workflows and no-code business rules
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Monitor health with monitoring, anomaly detection, and drift analysis
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Understand flows with full data lineage and impact analysis
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Scale control with natural language prompts and self-service rule creation
Built for modern data governance, Tale of Data empowers both business and technical teams to act — without writing a single line of code.
From anomaly detection to regulatory compliance, from fuzzy deduplication to mass discovery, we help you maintain, monitor, and improve data quality across all systems.
Frequently Asked Questions – Calculating the ROI of Data Quality
Improving data quality delivers ROI through increased operational efficiency, reduced error correction costs, better decision-making, and minimized regulatory risks. It directly reduces waste across departments and unlocks more accurate analytics, AI performance, and compliance readiness.
The cost of poor data quality includes:
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Time lost by employees correcting data
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Customer dissatisfaction incidents
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Rework of failed operations
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Compliance fines
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Strategic missteps from inaccurate reports
This calculator estimates those costs based on your inputs and turns them into a tangible annual financial impact.
This calculator is ideal for:
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Chief Data Officers (CDOs)
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Heads of Data Governance or Data Quality
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CIOs and IT leaders
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Business analysts or operations teams quantifying the impact of poor data
It provides a clear business case to justify investments in data quality tools or initiatives.
Because it affects everything: strategy, operations, compliance, and customer satisfaction. Poor data quality creates invisible losses across teams. Prioritizing data quality improves trust, productivity, and the scalability of your AI and analytics initiatives.
You can assess data quality based on key dimensions such as:
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Completeness
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Accuracy
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Consistency
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Freshness
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Uniqueness
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Validity
Tale of Data enables automated data audits across these dimensions to help you detect anomalies, gaps, and inconsistencies in just a few clicks — no code required.
Improvement strategies include:
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Implementing a modern Data Quality platform
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Automating error detection and remediation
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Standardizing data input processes
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Encouraging cross-team data ownership and collaboration
Tale of Data offers an AI-powered, no-code solution to address all of these.
Yes. Tale of Data includes a Mass Discovery module that performs automated audits at scale. It gives you a comprehensive, visual snapshot of your data quality and lets you drill down into specific issues in seconds.
With Tale of Data, remediation is not just about flagging errors — it's about fixing them:
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Standardize, deduplicate, and enrich data
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Automate remediation workflows with AI
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Deploy changes to production with just 1 click
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Track impact with full lineage and metrics
Tale of Data is a No-Code solution designed for rapid deployment. Most customers are operational in less than one week. There's no complex setup or integration phase.
Only 1 day of training is needed to become operational. The interface is designed for both technical and business users to collaborate seamlessly.
Here’s what our users typically see:
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25x faster than coding data pipelines manually in Python
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80% of Data Quality team time saved through automation
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60% reduction in AI training time
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35% drop in financial losses due to fraud detection
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1 click to deploy data pipelines in production
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1 day to train your teams