Managed Service 07 / 12
Data & Data Analytics
Without one source of truth, everything above it is guesswork.
A unified data warehouse consolidates fragmented data into one clean, governed layer. It is not an IT project — it is the foundation every other investment compounds on.
Single source of truth
CRM, ads, web, email, support, finance and product joined into one trusted, governed layer.
Trusted BI
Measure what matters, decide on evidence not opinion, and spot drift early — because the numbers finally agree.
Fuel for AI
Agents can only reason as well as the data beneath them — depth and quality turn AI from demo into value.
Representative stack
BigQuery 
Snowflake 
Databricks 
Power BI 
Tableau KPIs we move — measured, owned, reported
Every KPI is tied to a named owner and a target agreed up front — so this service is accountable to outcomes, not activity, for every stakeholder who consumes the value.
Why a data warehouse?
Without one source of truth, everything above it is guesswork.
Most businesses run on fragmented data — five tools, five versions of the truth, none trusted. A unified data warehouse consolidates it into one clean, governed layer. It is not an IT project; it is the foundation every other investment compounds on.
Improvement
Trusted BI and analytics. Measure what matters, decide on evidence not opinion, and spot drift early — because the numbers finally agree.
Growth
Connected RevOps and marketing. Segmentation, lifetime value, attribution and churn signals across the full funnel — one joined-up view of the customer.
Agentic AI & Automation
The fuel for autonomous AI. Agents can only reason and act as well as the data beneath them — depth and quality turn AI from demo into value.
Data Quality & KPIs
Quality and depth decide the ceiling.
Incomplete data produces unreliable output at speed and scale; deep historical data drives dramatically better decisions. We assess and remediate quality first, then wire every metric to a business outcome and a named owner.
One data layer · measured & owned
Every service creates data — captured, measured, owned.
Data & Data Analytics doesn’t just run — it generates signal. We land that data in one warehouse and turn it into live KPIs tied to a named owner, so performance is attributable and acted on, never trapped inside a single tool.
Data warehouse
Supabase Snowflake
Keboola BigQuery KPIs, dashboards & apps
Plotly
Retool
Apache Superset Platform-agnostic — we connect what you already use and add a warehouse only where it earns its place.
How we deliver · DMAIC
Every Data & Data Analytics engagement runs on DMAIC.
Define the goal and its value, measure the baseline, analyse the real constraint, improve with a proven build, then control the gains — so results are predictable, repeatable and defensible, not down to luck.
Agree the goal, value, budget & timescale up front.
Baseline the KPIs above — current state, not guesswork.
Diagnose the real constraint and the solution needed.
Build the chosen solution; prove the uplift.
Lock in the gains; monitor and sustain them.
Start here · the free first step
Data & Data Analytics starts the same way every engagement does: with Discovery.
Two distinct moves — a free, no-obligation Discovery Session to find your value at stake, then the Discovery & Blueprint: 14 structured outputs — value model, roadmap and business case — before a pound of delivery is committed.
Engaged alone or as one engine