Try it now

See exactly what we'd build for you.

Pick your industry, narrow to the segment you actually operate in, then select every data source you use. We'll generate the specific pipeline, dashboards, and reports Madison would deliver — metrics included.

01 · Your industry

02 · Your data sources

Pick an industry first.

Choose your industry, pick a segment, select one or more data sources, then generate your preview.

Pipeline

Service offering

A comprehensive suite,
three ways in.

Read each pillar top-down for the business outcome, or follow the tags for the exact stack and the roles that deliver it. Every pillar maps to a layer of the refinery above.

01 · Foundations

Data Engineering & Infrastructure

Reliable, trusted data — ready the moment a decision needs it.

Delivered by Data Engineer · Platform Engineer · Analytics Engineer

  • Modern Data StackOne cloud platform your whole company runs on.Snowflake · Databricks · BigQuery
  • Automated PipelinesData refreshes itself — no manual exports, no 2am breakages.dbt · Apache Airflow · ELT
  • Data LakehouseLake economics with warehouse speed and governance.Delta Lake · Iceberg · S3
  • Governance & Quality as a ServiceBad data is caught before it reaches a dashboard.observability · lineage · automated tests
02 · Intelligence

Advanced Analytics & ML

Predict and shape what happens next, not just report what already did.

Delivered by Data Scientist · ML Engineer · Data Analyst

  • Predictive AnalyticsKnow who'll churn and what they're worth, before they leave.churn · LTV · cohort · retention models
  • Customer 360 & PersonalizationOne view of each customer across every source.CRM + web + social unified · marketing automation
  • Generative AI IntegrationGenAI that does the work, not just chats about it.doc summaries · review sentiment · knowledge bases
  • MLOpsModels stay as accurate in month nine as on day one.monitoring · drift detection · retraining · MLflow
03 · Productized

Specialized “Productized” Offerings

Fixed scope, fast proof — value you can see before you commit.

Delivered by Data Engineer · Data Analyst · Data Scientist

  • 15-Day Proof of ConceptOne real problem solved and ROI proven in two weeks.scoped sprint · churn / fraud / segmentation
  • Industry DashboardsReady-to-run BI tuned to your sector.e-commerce · fintech · logistics
  • Data Lakehouse ArchitectureThe full blueprint, delivered as a package.reference architecture · migration plan
  • Data-as-a-Service (DaaS)Curated datasets, ready to query on day one.market research · enrichment feeds

How we engage

Principles first, and the
stack that backs them.

  • 01

    Start small, prove ROI

    A 15-day proof of concept on one real problem beats a six-month roadmap built on assumptions. We earn the next phase.

  • 02

    Automate the pipes

    Manual ETL breaks quietly. We move you to automated ELT so reliability is the default, not the heroics.

  • 03

    Catch it before the dashboard

    Observability sits in the pipeline, not the post-mortem. Bad data should never reach a decision-maker.

  • 04

    Ship models that act

    From "what happened" to "how to win" — and we stay on for MLOps so the model is as good in month nine as on day one.

The stack, by layer
IngestFivetran · Apache Kafka · custom extractors
LakehouseSnowflake · Databricks · BigQuery · S3 · Oracle
Transformdbt · Apache Airflow · Spark
SciencePython · scikit-learn · XGBoost · MLflow
ServePower BI · Tableau · reverse-ETL · model APIs
Governcatalog · lineage · quality & access reviews

Case studies

Shipped, measured,
still running.

Case 01Well-being / Fitness

Data warehouse architecture

Design and run a scalable data warehouse for a fitness platform with 300,000+ monthly active users, feeding marketing and finance with trustworthy reports.

OutputMarketing & finance reports
Input
MongoDB, HubSpot, Stripe, Google Analytics, Intercom, Salesforce
Stack
AWS EC2, Fivetran, Airflow, Databricks, MongoDB
Team
5 people
Duration
1 year
60%↓time-to-insight across recurring finance, marketing & product reports
5–10%↓weekly and monthly churn via lifecycle automation
+10%YoY retention from a 14-day churn early-warning system
100%stability at 300K+ MAU
BronzeSilverGoldBITIME-TO-INSIGHTbeforeafter · −60%300,000+ MAU · 100% uptime
medallion → BImasked · client metrics
Case 02Logistics

Data lake platform management

A global technology-and-services supplier whose departments each needed data for reports, dashboards, and AI/DS work — from one governed, regional-to-global platform.

OutputProcessed, governed data
Input
ERP, MS Office, IoT data, other platforms
Stack
Oracle DB, Apache Kafka, Solace, AWS, Power BI, Tableau
Team
4 people
Duration
1 year
1unified lakehouse managing the end-to-end lifecycle of global data
Highavailability and security across regional sources
Autoingestion from enterprise, user-generated, IoT & content sources
ERPMS OfficeIoTOtherDATA LAKEReportingDashboardsExplorationAI / DSCentralized · global · governedETL · SAP BODS/SLT · Event hub · Apache Kafka
sources → lake → appsdata management & governance
Case 03Fintech

Credit fraud detection

Credit-default prediction is core to consumer-lending risk. Accurate, real-time scoring means better lending decisions, smoother customer experience, and sustainable profit.

OutputReal-time fraud classification
Input
Customer data from multiple sources
Stack
DB, Fivetran, Databricks, Airflow, scikit-learn, XGBoost
Team
4 people
Duration
4 months
38%↓fraud on average vs businesses without the system
<100msend-to-end scoring latency
20%↓false positives
100%stability at 300K+ MAU
RISK 0–100low · approvemedium · MFAhigh · blockXGBoost · Isolation Forest · feedback loop
real-time risk scoring−38% fraud
Case 04Fitness · PoC

User segmentation by demographic

A four-week proof of concept: turn raw fitness-app data into clean demographic segments — coaches and clients by country, lead source, and spend — so growth and marketing can target with evidence.

OutputDemographic user segments
Input
Fitness-app customer data
Stack
MongoDB, GitHub, Fivetran, Databricks, Airflow
Team
3 people
Duration
4 weeks
4,780coaches and 21.84K clients segmented
119Min coach spend mapped by source & country
4 wkfrom raw data to a working segmentation dashboard
REGISTRATIONS BY COUNTRY2,6241,628336VietnamUSAUnknwnU.K.SGOther4,780 coaches · 21.84K clients
segments by demographic* confidential data masked

Work with us

Have an idea we can
turn into reality?

Bring us the decision you're trying to make. We'll scope a 15-day proof of concept on one real problem — and prove the ROI before anyone signs up for a roadmap.

Visit madison-technologies.com
Contact us[email protected]Tell us the decision you're trying to make — we reply within a business day.
CallMalaysia+60 12 619 8412Singapore+65 8201 4068Vietnam+84 934 988 681
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