Data Analysis & Insights
Data is only worth what you do with it. I build the pipelines, dashboards and reports that turn your numbers into decisions somebody actually makes.
A dashboard that nobody opens is a project that failed quietly. So this work starts from the decisions you need to make — weekly, monthly, or in the next board meeting — and builds backwards to the numbers that inform them.
What you get
- KPI dashboards built around a decisionSales, marketing or operations. We start from what you will do differently depending on the number, and metrics that change nothing get left out however easy they are to plot.
- Reports that send themselvesDaily, weekly or monthly, generated and delivered to inbox or Slack. No more rebuilding the same spreadsheet every Monday morning.
- Forecasting where the data supports itSales, demand, churn and seasonality — with an honest read on whether you have enough history to forecast at all.
- One source of truthETL that pulls from your database, spreadsheets, ads platforms and payment processor into one place, so two people stop quoting two different revenue figures.
- Analysis, not just visualisationCohorts, segmentation, A/B test readouts and statistical significance — so a 12% lift is confirmed as real before you spend against it.
My Data Analysis & Insights process
Agree the questions
Which decisions is this meant to inform? Everything downstream is judged against that list.
Audit the sources
What exists, what is trustworthy, and what is missing. Gaps found now are cheaper than gaps found in a board meeting.
Build the pipeline
Extract, transform and load into one clean, queryable, scheduled place.
Build the views
Dashboards for what you watch continuously, scheduled reports for what you review periodically.
Write the read-out
What the data says, what I would do about it, and what I am not confident enough to conclude.
Tools I use for this
Chosen per project against your constraints and budget — never one stack forced onto every problem.
Questions I get asked about this
Can you work with the data where it already is?
Usually, yes, and it is normally the better option. I connect to Postgres, MySQL, BigQuery, Google Sheets, Shopify, Stripe, Meta and Google Ads, and most tools with an export or an API. Moving everything into a warehouse first is sometimes right, but it is a real project with real cost, and plenty of businesses get what they need from a read-only connection and a scheduled sync. I will tell you which situation you are in.
What is the difference between a dashboard and a report, and which do I need?
A dashboard is for a number you watch continuously and act on quickly — today's orders, live stock, current spend. A report is for a periodic review where the useful thing is comparison and commentary. Most businesses ask for a dashboard and are better served by a weekly report, because a dashboard nobody has a habit of opening decays into a broken link. Often the right answer is a small dashboard plus a report that lands where you already read things.
How is my data kept confidential?
I will sign your NDA, or provide one. Access is least-privilege and read-only wherever the work allows it, scoped to the specific tables or properties in question, and revoked when the engagement ends. Your data is not used to train anything and is not shared with any third party beyond the tools we explicitly agree on. If a dataset contains personal data, I would rather work with it pseudonymised, and will suggest that where it does not damage the analysis.
Can you do forecasting, or only analysis of what already happened?
Both, with a caveat worth stating early. Forecasting needs enough history to learn a pattern from — as a rough rule, two full seasonal cycles, so about two years for anything with an annual rhythm. With eight months of data I can show you trend and seasonality but I cannot honestly give you a confident twelve-month forecast, and I would rather say that than hand over a chart that looks authoritative and is not.
Turn your numbers into decisions
Bring one question you cannot currently answer from your own data. That is usually enough to scope the whole engagement.
Start with a free discovery call