Your Data Is There.
Let's Make It
Actually Useful.
We clean up your data, build pipelines that don't break, and create dashboards your team actually opens, not just impressive screenshots that no one uses after week two.
Analytics Overview
Q3 Performance Report
Revenue
$2.4M
▲ +12% YTD
Accuracy
94.2%
▲ +2.1% vs avg
Growth
+31%
▲ vs last Q
Monthly Revenue
Core Services
End-to-end data solutions, from raw pipelines to executive dashboards.
What Your Data Can Look Like
Sample dashboards built with Power BI, Tableau, and Databricks SQL. Designed to inform decisions, not just display numbers.
Total Revenue
$4.2M
Revenue Growth
+28%
Active Clients
1,284
Avg Deal Size
$3.3K
Monthly Revenue (USD)
Jan – Dec 2024
Revenue by Segment
Pipeline Trend
Top Accounts
By revenue · Q4 2024
Acme Corporation
Retail
$420K
+15%
Healthy
GlobalTech Partners
Technology
$385K
+8%
Healthy
NextGen Logistics
Logistics
$290K
-2%
At Risk
PrecisionMfg Ltd
Manufacturing
$265K
+22%
Healthy
All data shown is illustrative. Real dashboards are built around your data model, KPIs, and reporting requirements.
Modern Data Stack Patterns
The data stack patterns we work with most. Pick the tab that matches where you are headed.
dbt on top of Snowflake — how most mature analytics teams structure their stack
These are reference architectures. Every engagement is scoped and designed based on your specific source systems, data volumes, and business requirements.
Standards, Not Shortcuts
The patterns used by data teams at Airbnb, Spotify, and GitLab. Applied at the scale that fits your business.
Industry-Standard Architecture
We use the architecture patterns that data teams have converged on for good reasons: medallion layers (Bronze/Silver/Gold), Kimball dimensional modeling, and data vault where the complexity warrants it. The pattern fits the problem, not the other way around.
Engineering Best Practices
Every project follows the same engineering discipline we would apply to production software: version control, peer review, modular design, and documented deployment processes. Data work should not live in someone's laptop.
Data Quality Management
Quality is built into the pipeline, not checked at the end. We implement automated tests at every layer (null checks, uniqueness constraints, referential integrity, freshness SLAs) so issues surface before they reach a dashboard.
Data Quality Management
Quality is not a final check. It is part of the build.
Most data quality problems are discovered by business users who notice a wrong number in a dashboard. We move that discovery upstream, into the pipeline, where it can be fixed before it causes a bad decision.
Automated Testing
Every dbt model ships with tests: null checks, uniqueness, accepted values, referential integrity. They run on every pipeline execution.
Version-Controlled Everything
SQL, models, pipeline configs, dashboard definitions: all in Git. Full change history, rollback capability, and no mystery changes.
Freshness SLAs
Every table has a documented freshness expectation. Alerts fire before your team notices stale data in a report.
Auto-Generated Documentation
dbt generates a data dictionary from your models: column descriptions, lineage graphs, test results. Always in sync with the actual code.
Low Risk · Fixed Scope
See Results Before
You Commit
Every engagement starts with a Proof of Concept: a timeboxed, fixed-scope project that delivers something real. No long contracts, no open-ended retainers. You see the quality of the work first, then decide whether to continue.
Data Audit
We map out what data you have, how it moves, and where things are breaking or missing. One week, fixed scope.
What You Get
- Full data landscape map
- Quality and freshness assessment
- Identified gaps and quick wins
- Prioritised analytics roadmap
✓ A clear picture of where you are and exactly what to fix first.
Dashboard Quick-Start
One production-ready dashboard built from your actual data. Designed, built, and handed over with full documentation.
What You Get
- Up to 5 KPIs / visualisations
- Connected to your live data source
- dbt model for the underlying data
- User guide + technical handover
✓ A working dashboard your team uses on day one.
Pipeline Proof
A fully working ELT pipeline from source to warehouse, with dbt transformations and automated quality checks.
What You Get
- One source connected and loaded
- dbt models with tests and docs
- Scheduled orchestration
- Data quality report
✓ A reliable pipeline running in production, not just a demo.
Every POC includes a full project proposal
At the end of every POC, you receive a detailed proposal for the full engagement: scope, timeline, and fixed fee. You make the call with no pressure.
Our Delivery Process
A structured, repeatable methodology that ensures every engagement delivers lasting value.
Discovery
We start with your data landscape and your business goals. One focused conversation is usually enough to understand what needs to be built.
Planning
We lay out the architecture, define what gets built in what order, and agree on a timeline before anything starts.
Development
The actual build: pipelines, models, dashboards. You see work in progress, not just a finished product six weeks later.
Validation
Every number gets traced back to source. We run quality checks and fix edge cases before calling anything done.
Deployment
We push to production and hand over documentation that explains how things work, not just what they are.
Ongoing Support
Data changes. Business requirements change. We stay available to handle both.
Discovery
We start with your data landscape and your business goals. One focused conversation is usually enough to understand what needs to be built.
Planning
We lay out the architecture, define what gets built in what order, and agree on a timeline before anything starts.
Development
The actual build: pipelines, models, dashboards. You see work in progress, not just a finished product six weeks later.
Validation
Every number gets traced back to source. We run quality checks and fix edge cases before calling anything done.
Deployment
We push to production and hand over documentation that explains how things work, not just what they are.
Ongoing Support
Data changes. Business requirements change. We stay available to handle both.
Frequently Asked Questions
If Your Reporting Is Broken,
Let's Fix It.
Slow reports, unreliable numbers, dashboards no one opens. That is the problem we solve. Start with a Proof of Concept and see the difference before committing to anything.