Data

Data Quality Framework

Automated Monitoring so Bad Data Never Reaches Production

What we do

Data quality issues discovered by users erode trust and trigger expensive rework. We implement automated data quality frameworks that catch problems at the pipeline level — before they reach analysts, dashboards, or AI models — using dbt tests, Great Expectations, or Soda Core.

Ideal for

Analytics and data engineering teams whose reports are undermined by upstream data quality issues they discover too late

Common applications

Data Quality Rules Engine

Define completeness, uniqueness, validity, and consistency rules for critical data columns and automate their daily execution.

Schema Change Detection

Alert immediately when a source system changes a schema — preventing silent failures from propagating through the pipeline.

Anomaly Detection on Metrics

Detect unusual patterns in row counts, null rates, and value distributions — catching upstream data issues before dashboards are affected.

Data Contracts

Define and enforce data contracts between teams: expected schema, freshness SLAs, and quality thresholds for every data feed.

Quality Dashboards for Data Stewards

Build a data quality dashboard showing rule pass/fail rates, issue trends, and ownership — visible to both engineers and stewards.

dbt Test Suite Expansion

Extend your existing dbt project with comprehensive tests: referential integrity, date range validation, and custom business rule tests.

How we work

01

Critical Data Identification

Identify the most business-critical data domains and the quality dimensions that matter most for each.

02

Rule Design & Tooling

Select the right tooling (dbt tests, Great Expectations, Soda) and design the rule set for each data domain.

03

Implementation & Integration

Implement rules in the pipeline, integrate alerting, and build the data quality dashboard.

04

Escalation Process & Handover

Define the issue escalation process and train data owners on how to investigate and resolve quality failures.

What you receive

  • Data quality rules implemented in your pipeline tooling
  • Automated alerting for quality failures
  • Data quality dashboard for stewards and engineers
  • Data contract templates for inter-team data agreements
  • Quality run history and trend reporting
  • Process documentation and team training

Ready to get started?

Let's discuss your requirements. No commitment, no sales pitch — just a focused conversation about your situation.

Book a free discovery call