Data & BI
Warehousing, pipelines & real-time dashboards
We design and build modern data platforms — from warehouse architecture and ETL pipelines to self-service BI dashboards — turning scattered data into decisions your leadership team trusts.
Insights that drive, not reports that gather dust.
Data & BI is delivered by data engineers and analysts who build pipelines that run — not slide decks that stall.
Built for teams
who can't trust their data.
CFOs, analytics leads and CDOs who know their reports don't match, their dashboards are stale, and their analysts spend 80% of their time wrangling spreadsheets instead of finding insights.
Whether you're building a modern data warehouse, automating regulatory reporting, or empowering self-service analytics — we make your data work for you.
How a Data & BI
engagement runs.
A senior data engineering team, a shared workspace, and four disciplined phases from data audit to self-service analytics.
Audit & catalogue
We map every data source, quality issue, governance gap and reporting need. The output is a prioritised data roadmap.
Design data architecture
Warehouse schema design, pipeline architecture, data modelling (dimensional/vault), security and access controls — documented before build.
Build & validate
Iterative pipeline development with data quality checks at every stage. Every sprint delivers tested, documented, production-ready data flows.
Dashboard & govern
Self-service BI rollout, user training, data catalog launch and ongoing governance reviews keep insights fresh and trustworthy.
The stack we build &
run with.
Production-grade tools and platforms — chosen for reliability, not hype.
Pipelines, quality
& dashboards — one
view.
Every pipeline, data quality check and dashboard metric tracked in a shared control room your team logs into.
Pipeline · Revenue data mart
Snowflake + dbt · 14 models
Pipeline · Customer 360
Identity resolution · testing
Quality · Product dim nulls
2.1% null rate on SKU column
Dashboard · Executive KPIs
Power BI · 12 visuals · signed off
What clients say after delivery.
"Monthly reporting went from 5 days to 5 minutes. Our CFO now has real-time dashboards instead of stale spreadsheets."
"Spotless built our entire data platform in 10 weeks. Clean architecture, full docs, zero vendor lock-in."
"Data quality went from 72% to 99%. Our analysts finally trust the numbers."
How long does it take to build a data warehouse?
A production-ready warehouse with core data models typically ships in 6–10 weeks. Larger implementations with dozens of sources run 3–5 months.
Which warehouse platform do you recommend?
It depends on your existing stack. We most commonly deploy Snowflake, BigQuery or Azure Synapse. We help you choose based on cost, performance and team familiarity.
Can you work with our existing BI tool?
Yes. We build the data layer underneath and connect it to whatever BI tool you use — Power BI, Looker, Tableau or Metabase.
How do you ensure data quality?
We implement automated testing (Great Expectations, dbt tests), monitoring (Monte Carlo), alerting and data contracts at every stage of the pipeline.
Do you handle real-time analytics?
Yes. We build streaming pipelines using Kafka, Spark Streaming or cloud-native services for use cases that need sub-second latency.
Ready to scope
Data & BI?
30-minute walkthrough with a product specialist. No slides
— just your workflow.
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