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About
Services
Ozessa EngineAutomated ReconcilerCompute Cost ControlData Architecture AssessmentManaged Reliability
Calculator
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FAQ
Resources
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Book a consultation
Ozessa

We build and manage reliable data systems inside your Microsoft Fabric workspace. You own everything.

Corporate Entity

Ozessa is a trading name of OZESSA LTD.
Company No. 17120532 (England & Wales)

Registered Office:
167-169 Great Portland Street
5th Floor
London, W1W 5PF

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Insights
Engineering Insight
The ROI of Data Quality Automation
Owned by you. Built for truth.

The ROI of Data Quality Automation

Why "Cleaning Data" should never be a human job.

Read AnalysisBook a consultation
FABRICENGINE
ERP
CRM
API
SQL
IoT
XLS
DeploymentInside your Microsoft tenant
Data Ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft FabricEnterprise-grade architecture
Operational Depth
TL;DR / Executive Summary

Manual data cleaning is a non-scalable operational bottleneck.

Human error during cleaning often introduces new, silent bugs.

Data quality automation increases the "Trust Index" of the BI stack.

Read Time
12 MIN READ
Authority
Engineering Insight
Tier
Technical Evaluation
KEY FACTS
FACT_01

Automated DQ checks reduce data-related support tickets by 80%.

FACT_02

High DQ increases marketing conversion rates by up to 20%.

FACT_03

Ozessa DQ Engines pay for themselves within 4 reporting cycles.

Definition

What is Data Quality Automation?

The use of technical circuit breakers and logic tests to identify and fix data errors without human intervention.
Problem analysis
A. Symptom

Visible Signal

The CRM is full of duplicates and incomplete addresses.

B. Business Impact

Consequence

Failed marketing campaigns and inaccurate sales forecasts.

C. Hidden Failure

Architecture Flaw

Expecting users to "Type it correctly" every time.

Root cause

Data quality is an engineering problem, not a training problem. If a user can enter bad data, the system should catch it and fix it automatically.

Our solution

The Reliability Engine Response

Our architecture mandates a reliability-first approach, injecting comprehensive markers and circuit breakers into the core transformation logic.

1

Deploying automated "Data Scrubbers" in the Silver layer.

2

Fuzzy-matching for deduplication without human review.

3

Automated "Missing Data" enrichment via external APIs.

Business impact
30 hrs/mo
Time Recovered
$15k/yr (Direct Labor)
Cost Mitigation
Operational Error
Risk Exposure
99.9%
Metric Accuracy
Technical Analysis

Ozessa automates the "Manual Cleaning" of data via a Automated Data Check. We ensure your estate remains clean, structured, and ready for growth using Data Quality Automation.

KEY TAKEAWAYS
  • ●Automation is the only way to scale quality.
  • ●Clean data is the primary driver of marketing ROI.
KEY DATA POINTS
Metric: 80% Ticket Reduction
ROI: 400%
On this page
  • Executive Summary
  • Key Facts
  • Definition
  • Problem analysis
  • Root Cause
  • Our Solution
  • Business Impact
  • Technical Analysis
  • Key Takeaways
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DATA ASSESSMENT

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Stop relying on manual spreadsheets. Establish a reliable baseline and automate your reporting.

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Ready to fix your data?

Stop spending weekends reconciling spreadsheets. Let us build a reliable data system you own - inside your own Microsoft workspace.

DeploymentInside your Microsoft tenant
Data ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft Fabric
Enterprise-grade architecture
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