DATA & ANALYTICS

Data & Analytics

Turning Raw Data into Business Intelligence

Modulinks helps organisations move from fragmented data silos to unified, governed, and analytics-ready data platforms. Our data engineers, architects, and analysts work together to build the infrastructure, pipelines, and dashboards that make data a genuine organisational asset.

We have deep experience with regulated data in Healthcare (HL7/FHIR, HIPAA), Insurance (actuarial data, claims), Banking (Basel, transaction data), and Telecom (CDRs, network data) — meaning we handle your data with the care and compliance rigour it demands.

Modern Data Platform

Lakehouse architectures on Snowflake, Databricks, or BigQuery — combining the flexibility of data lakes with the governance of data warehouses.

Real-Time Analytics

Streaming data pipelines with Apache Kafka and Spark Streaming for operational analytics, fraud detection, and live dashboards.

Self-Service BI

Power BI, Tableau, and Looker implementations with semantic layers, row-level security, and embedded analytics.

Data Governance & Quality

Lineage tracking, data cataloguing (Collibra, Alation), quality rules, and master data management frameworks.

Our Capabilities
01

Data Warehouse & Lakehouse

Design and build of cloud data warehouses (Snowflake, Redshift, BigQuery) and lakehouse architectures (Delta Lake, Apache Iceberg) for petabyte-scale analytics.

02

ETL / ELT Pipelines

Batch and streaming data pipelines using dbt, Apache Airflow, Fivetran, and custom Python/Spark jobs — with automated testing and alerting.

03

Business Intelligence

Dashboard and report development in Power BI, Tableau, or Looker — from executive scorecards to operational drill-downs and embedded analytics.

04

Advanced Analytics & Modelling

Statistical modelling, cohort analysis, customer segmentation, and propensity scoring that go beyond standard BI to answer the "why" and "what next".

05

Data Mesh & Governance

Domain-oriented data ownership models, data contracts, and governance tooling that scale data operations without creating bottlenecks.

06

Data Migration

Structured migration of legacy data warehouses (Teradata, Oracle, on-prem SQL Server) to modern cloud platforms with zero data loss and minimal downtime.

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