Varnix Technologies
Banking · Data platform

Next-Generation Data Warehouse (DWH) Implementation

A legacy warehouse that could no longer keep up, replaced in a phased 9-month programme with real-time pipelines, governed analytics and an architecture ready for AI and ML.

One of Asia's largest financial institutions · under NDA

query times
−70%query times
dashboard latency, for the first time
< 1 sdashboard latency, for the first time
manual data preparation
−60%manual data preparation
months, phased programme
9months, phased programme
Client
One of Asia's largest financial institutions (NDA)
Scope
Next-generation data warehouse, pipelines, BI and analytics
Duration
9 months, five phases
Compliance
GDPR and local financial regulation
The starting point

Where the bank was

  1. 1The legacy data warehouse could no longer handle growing transaction volumes or complex analytics.
  2. 2High-latency data pipelines delayed reporting.
  3. 3Banking systems, CRM and digital channels were disconnected from each other.
  4. 4Compliance gaps existed against GDPR and local data protection laws.
  5. 5There was no way to support real-time dashboards or predictive analytics.
What we built

The target architecture

Sources
  • Transactions
  • CRM
  • Mobile channels
Ingestion
  • Real-time ingestion
  • Optimized batch processing
  • Informatica · Talend · Azure Data Factory
Platform
  • High-performance analytical database
  • Data lake integration layer
Consumers
  • Power BI and Tableau dashboards
  • Predictive models for credit scoring
Governance across every layerGDPR alignmentData maskingEncryption
TechnologyInformaticaTalendAzure Data FactoryData lakePower BITableau
How the programme ran

5 phases, 9 months

1

Discovery & Planning

Full audit of the existing environment and a target architecture blueprint covering both hybrid cloud and on-premises options.

2

Architecture Selection

A high-performance analytical database paired with modern ETL tooling (Informatica, Talend, Azure Data Factory) and a data lake integration layer.

3

Data Pipelines

Real-time ingestion from transactions, CRM, and mobile channels, plus optimized batch processing for the rest.

4

BI & Analytics

Power BI and Tableau integration, with predictive models built for credit scoring.

5

Compliance & Deployment

GDPR alignment, data masking, encryption, and a zero-downtime cutover to production.

Results

What changed

  • Query times reduced by 70%.
  • Sub-second latency dashboards enabled for the first time.
  • Manual data preparation reduced by 60%.
  • Full GDPR and local financial regulation compliance achieved.
  • A scalable architecture now in place, ready for future AI/ML integration.

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Want a result like this?

Most engagements start with a fixed-scope sprint from €10k — a measured answer in weeks, then the programme only if it pays off.

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