Data Science & Analytics
Data Quality Assessment Engine
Know your data before it knows you
7
VAL
6
FIT
7
EASE
6
ODOO
7
GC
2
RISK
6.6
Score
Why This Workflow Matters
The business case for implementing this workflow.
Garbage in, garbage out remains data science's biggest problem. IBM estimated poor data quality costs organizations $3.1 trillion annually. Yet most data teams assess quality reactively — after a model fails or a report is wrong. Systematic data quality assessment requires methodology that most organizations lack, and manual profiling takes days per dataset.
The Bigger Puzzle
How AI + Odoo creates something greater than the sum of its parts.
AI + Odoo Synergy
Quality assessment reports feed into Quality module for tracking data quality KPIs. Remediation items become Project tasks assigned to data stewards. Knowledge base accumulates data quality patterns and known issues. Dashboards show quality scores across all organizational datasets. When new data sources are onboarded, historical quality patterns inform the assessment automatically.
Odoo Apps Activated
Documents
Quality
Project
Knowledge
Dashboards
Current Alternatives & Why They Fall Short
The existing solutions and their limitations.
Great Expectations / Soda Core
Open-source data quality validation frameworks for automated testing of data pipelines.
Open-source free. Managed: Great Expectations Cloud $5,000-$30,000/year. Soda Cloud $10,000-$50,000/year
Limitations
- Technical tools requiring engineering skills to configure and maintain
- Test-focused — validates rules but does not generate assessment narratives or remediation plans
- No business impact estimation or executive communication
- No connection to project management for tracking remediation efforts
Why RebusAI is Better
RebusAI generates the assessment narratives, business impact estimates, and remediation plans that validation frameworks cannot. We provide the strategic layer on top of technical quality checks, connected to Odoo for tracking and execution.
Informatica Data Quality
Enterprise data quality platform with profiling, cleansing, and monitoring capabilities.
$100,000-$300,000/year — Enterprise licensing with implementation costs
Limitations
- Massive cost and complexity for mid-market organizations
- Implementation takes 3-6 months with consulting support
- Focused on automated cleansing, not assessment reporting and communication
- No integration with business project management or knowledge systems
Why RebusAI is Better
Generates comprehensive quality assessments with business narratives and remediation plans at a fraction of enterprise platform costs. Connected to Odoo for tracking improvement projects and building organizational data quality knowledge.
Manual Data Profiling
Data analysts profile datasets manually using SQL queries, pandas, and custom scripts.
Free tools — But 2-5 days of analyst time per dataset assessment
Limitations
- Time-consuming and inconsistent across analysts
- Results typically stay in notebooks — not shared or tracked
- No standardized methodology or scoring framework
- Remediation tracking is ad hoc at best
Why RebusAI is Better
Standardized, AI-generated assessments with consistent methodology, scoring, and remediation planning. Results live in Odoo with tracking and knowledge retention — not buried in notebooks.
Implementation Approach
How to bring this workflow to life.
Extends the assessment and report generation workflows with data quality-specific dimensions and scoring methodology. 2-3 week implementation with templates based on DAMA data quality dimensions.
Ready to Build This Workflow?
Turn Data Quality Assessment Engine into a competitive advantage with RebusAI + Odoo.
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