Bad data infrastructure is invisible until it's expensive. Executives make decisions on stale reports. A/B tests run without proper controls. Revenue attribution is wrong and nobody knows it yet.
We audit your existing stack, identify the integrity gaps, rebuild what needs rebuilding and add the monitoring layer that tells you when something breaks before your MD does.
Snowflake, BigQuery, Databricks or Redshift architecture, schema design, cost optimisation and incremental load strategies for petabyte-scale data.
dbt models, Fivetran/Airbyte connectors, Airflow orchestration, real-time Kafka ingestion and automated data quality checks at every layer.
Looker, Tableau, Power BI and Metabase. Self-serve analytics for ops teams, real-time KPI boards for leadership and scheduled report automation.
Statistical experiment design, power analysis, sequential testing and causal inference. Trustworthy results, faster decisions.
Multi-touch attribution, customer journey mapping, cohort analysis, LTV modelling and marketing mix optimisation for growth teams.
Data contracts, ownership catalogues, PII tagging, lineage tracking, freshness SLAs and automated quality monitoring with alerting.
We migrated the strongest old-site analytics taxonomy into the new service model: financial analytics, customer analytics, sales and product insights, asset management analytics, HR analytics, supply-chain insights, transportation and logistics, manufacturing intelligence and healthcare data insights.
The goal is the same across each domain: refine raw data into real-time insight, expose hidden patterns, improve operational efficiency and give leaders a decision system they can trust.