Data Quality Software: Validate, Cleanse & Monitor Data
Maintain accurate, complete, and consistent data across every pipeline with built-in AI quality controls.
- Detect and prevent errors with embedded checks
- Automate quality with AI-driven, natural-language rules
- Monitor and improve with scores, trends, and alerts
Definition
A data quality platform validates, cleanses, and monitors data so accuracy, completeness, consistency, and validity are enforced before data reaches dashboards or AI. Infoveave embeds quality rules in the same Unified Data Platform as ingestion and governance — one rule library across pipelines, not bolt-on checks beside the warehouse.
$12.9M
Average annual cost of poor data quality to organisations (Gartner, 2020)
80%
Of data scientists' time spent on preparation and cleaning vs analysis (Forbes-cited survey)
For the full category trade-off across quality, automation, and governance, read Unified Data Platform vs point solutions. Ready to decide whether to consolidate? See UDP vs point tools.
Let Trust Be Your Data Strategy
Data quality isn’t just about fixing errors — it’s about enabling every team member to act with confidence. Infoveave embeds quality checks directly into your data pipelines, helping you connect clean, consistent data with measurable business results.
- When insights are built on verified data, teams can move quickly without second-guessing reports. From performance tracking to forecasting, decisions stay aligned with real conditions.
- Detect and correct data issues before they impact operations. Automated rules and workflows help teams save time spent on rework, reconciliation, and manual cleanups.
- Establish a shared view of data quality across departments. Business and technical teams work from the same definitions, ensuring consistency from source to dashboard.
Australian Utility Provider Boosts Billing Efficiency with a Unified Data Management Platform
An Australian utility provider was facing considerable operational and revenue risks due to accounts that lacked an associated customer name — known internally as “occupant accounts.” These arise when a property has an active supply connection but no registered account holder, often because new occupants move in without updating records. This creates billing ambiguity, revenue leakage, and the possibility of wrongful disconnections.
Key Features
AI-Assisted Rule Authoring
Create draft rules from prompts; accelerate bulk rule creation and mapping to columns/entities.
Reusable Rules Library
Centralize, version, and reuse rules across datasets, teams, and pipelines to ensure consistent standards.
Rich Validation Types
Pattern/regex, range/threshold, referential integrity, reference-data and API checks (e.g., address verification), conditional logic, and timeliness checks.
Monitoring & Reporting
Quality KPIs and scorecards by domain and system; drill-downs to failed rules, columns, and records; trend analysis and SLA tracking.
Pipeline Integration
Plug rules into Infoveave workflows to validate on ingestion and transformation, trigger alerts, and route exceptions.
Governance Alignment
Use common definitions and ownership so business and engineering teams work from the same standards (ties into Infoveave data governance).
How It Works
- Start with AI-generated rule drafts, then refine with business logic—patterns, thresholds, reference lists, or external validation services. Save rules to a central library.
- Run evaluations on demand or on schedule. View quality scores (e.g., accuracy, completeness, validity), issue breakdowns, and lineage-aware impact.
- Embed rules in ELT/ETL pipelines so the same controls guard every flow. Dashboards show trends and SLAs by system, domain, or owner.
- Automate fixes (standardize formats, enrich from reference data, route exceptions) and track improvement over time.
Explore Data Quality Insights
Dive deeper into data quality strategies, best practices, and frameworks to ensure accuracy and trust across your data landscape
UDP vs Point Tools (Decide)
UDP vs Point Solutions (Guide)
Data Quality Primer: Build Your Framework
Data Quality Best Practices
Success Story: System Reconciliation
Data Quality Monitoring Tools Guide
Manufacturing Analytics Solutions
Healthcare Analytics Solutions
Banking Analytics Solutions
Data Lineage & Metadata Management
Frequently Asked Questions
Ready to see Infoveave in action?
