POWER BI & DATA ANALYTICS CONSULTANCY
Turn data into
business decisions
that drive growth
Analytics is where we lead. Stack Homme is a data analytics consultancy for teams in the US, UK and Europe, turning scattered spreadsheets and systems into a single source of truth — with Power BI dashboards and KPI tracking your leadership team can act on.
Data engineering
Build. Integrate. Store.
Data analytics
Transform. Analyze. Uncover insights.
Executive dashboards
Visualize. Track. Decide.
Business growth
Smarter decisions. Better outcomes.
DRIVE IMPACT WITH ANALYTICS
Actionable insights.
Measurable impact.
A well-built analytics layer does more than draw charts. It shortens the time between something changing in your business and someone noticing, and it gives every team the same numbers to work from.
- Real-time visibility across your business
- KPIs that align with your goals
- Insights that lead to confident decisions
- Dashboards your team will love to use
SHIPPED FOR A CLIENT
OUR CORE EXPERTISE
Data analytics is our core strength
Everything we build starts with a question your team is trying to answer. Engineering and data science are how we get you a good answer. Analytics is where we deliver it.
Data Engineering
Clean, connected data pipelines so your reports are never built on a shaky spreadsheet someone patched together last quarter.
- ETL / ELT Pipelines
- Cloud Pipelines
- Data Warehousing
- Data Migration
- Data Integration
- Data Governance
- Data Modeling
- Data Quality
- SQL Development
- API & Integration
Data Analytics
Power BI dashboards, executive KPI tracking and self-service reporting that replace guesswork with a number everyone in the room agrees on.
- KPI Development
- Business Intelligence
- Executive Dashboards
- Data Visualization
- Power BI Development
- Ad-hoc Reporting
- Report Automation
- Self-Service Analytics
- Dashboard Design
- Performance Tracking
Data Science
Forecasting and machine learning models that push your analytics past reporting on last quarter and into predicting the next one.
- Predictive Analytics
- AI Automation
- Machine Learning
- NLP
- Forecasting
- Time Series Analysis
- Customer Segmentation
- Model Deployment
- Recommendation Systems
- Statistical Analysis
OUR PROCESS
From data to decisions in seven steps
01
Discover
Understand your goals and key decisions
02
Collect
Gather data from CRM, ERP & spreadsheets
03
Engineer
Build reliable data pipelines
04
Transform
Clean, validate & structure data
05
Analyze
Build KPIs and uncover insights
06
Visualize
Create dashboards that drive action
07
Optimize
Continuously improve and measure impact
Industries we serve
Every industry generates data differently, and a KPI that matters in retail can be noise in healthcare. We shape reporting around how yours actually measures success.
Healthcare
Patient records, scheduling and billing usually live in separate systems. We bring them together into KPIs a team can track, from bed utilization to appointment no-show rates.
Finance
Financial data comes with tight accuracy and audit requirements. We build pipelines with validation and reconciliation in them, then reporting on top, so the numbers match before they reach a board pack.
Retail
Sales, inventory and foot traffic rarely sit in one place. We connect them into dashboards for margin, stock and store performance, and forecasting once you are planning ahead rather than reacting.
Manufacturing
Sensor data, production logs and ERP records move at different speeds on a factory floor. We land them in one warehouse so downtime and yield reporting reflect what is happening on the line.
E-commerce
Customer behavior data piles up fast and mostly goes unused past a basic sales dashboard. We report on margin, repeat rate and fulfilment, and model churn and demand on what you already collect.
Logistics
Route data, delivery times and fleet costs are usually tracked well enough to report on, but not well enough to predict. We consolidate them and forecast demand and delivery windows against capacity.
Real Estate
Portfolio performance, occupancy and pricing often live in spreadsheets rebuilt every cycle. We automate that reporting, so a portfolio review does not start with a week of manual reconciliation.
Education
Enrollment, attendance and outcomes data sit across systems that were never meant to talk. We bring them into one view so administrators can track trends without comparing three exports.
SaaS
Usage data is the asset most SaaS companies underuse. We build retention and expansion reporting on your product analytics, plus churn and usage models when the reporting layer is solid.
Energy
Metering and sensor data arrive in high volume and in formats never built for analytics. We normalize them into pipelines, then forecast demand once consumption reporting can be trusted.
Construction
Costs, timelines and change orders are tracked per project in separate tools, which makes portfolio reporting slow. We consolidate them so overruns and schedule risk show up before a job closes out.
ABOUT STACK HOMME
A consultancy built around one idea
Stack Homme helps teams that are tired of making calls off gut feel, a patchwork of spreadsheets, or a dashboard nobody quite trusts anymore.
We work remotely with teams across the US, UK and Europe, and we stay on after launch when you want ongoing support.
More about how we workStart with the decision, not the dashboard
We ask what call you're trying to make before we open a design tool. A chart nobody needs is wasted work, however good it looks.
A dashboard nobody trusts is worse than no dashboard
If the numbers don't match reality, people go back to gut feel and blame the tool. We'd rather ship it right than ship it fast.
Engineering and data science exist to make analytics better
We don't sell pipelines or models for their own sake. They're there to make the dashboard you actually use more accurate.
INSIGHTS
Notes from building data platforms
Practical writing on data engineering, Power BI and data science, drawn from client work — what we fix, why it was broken, and what we would do differently.
NOI, Net Income and Cash
Net operating income up 41%, net income at minus $5.3M, cash down $294K — all three correct, all describing one portfolio. Here is why they diverge.
Why Your Power BI Report Is Slow
Slow Power BI reports are rarely about data volume. It's the model, the DAX or the page — here's how to tell which one you have, and what to fix first.
COMMON QUESTIONS
Questions we are asked before the first call
- What does a data analytics consultancy do?
- A data analytics consultancy helps a business turn the data it already has into reporting and insight people act on. At Stack Homme that means defining the KPIs that matter, building Power BI dashboards around them and, where needed, fixing the data pipelines underneath or adding forecasting on top.
- What is the difference between data engineering, data analytics and data science?
- Data engineering moves and cleans your data so it can be trusted. Data analytics turns that data into dashboards and KPIs that explain what happened and why. Data science uses statistics and machine learning to predict what is likely to happen next. Each one builds on the one before it.
- Do you work with companies in the US, UK and Europe?
- Yes. We work remotely with teams across the United States, the United Kingdom and Europe, and schedule working sessions around your time zone. Data handling and access are set up with GDPR and your internal policies in mind.
- Which tools and platforms do you use?
- Power BI is our primary analytics platform. For data engineering and data science we build on Microsoft Azure, Microsoft Fabric and Databricks, using SQL and Python. We always start from the tools you already have rather than asking you to replace them.
- Where should we start if our data is a mess?
- Usually with a free consultation. We look at the decisions you need to make and the data behind them, then recommend whether to start with data engineering, go straight to dashboards, or do both. Most engagements start with one service and grow into the next as the questions get harder.
- How does a typical engagement work?
- Every project follows the same seven steps: discover, collect, engineer, transform, analyze, visualize and optimize. Each step has a clear output, and everything we build is documented so your team can own it.
- Do you offer ongoing support after launch?
- Yes. After launch we can monitor pipelines and data refreshes, add new reports and data sources, retrain forecasting models and help new users get started. Support is optional — the documentation is written so your team can run everything in-house if you prefer.
- Is the consultation really free?
- Yes. The first consultation is free and comes with no obligation. You get an assessment of where your reporting stands today and a suggested roadmap, whether or not we end up working together.
Still have a question? Ask us directly.
Ready to build a smarter data strategy?
Book a free consultation and let our experts help you turn your data into a growth engine.
- Free consultation
- Business assessment
- Custom solution roadmap
- No obligation