Data Analytics & Dashboards
Dashboards people actually open, and models that explain themselves.
SQL, Power BI and forecasting work: refreshable dashboards built on a proper data model, plus predictive and recommendation prototypes where the numbers justify one. Every model ships with its assumptions and error bounds written down.
Typical timeline: 2–6 weeks for a dashboard, longer where modelling is involved
When this is the right call
Problems this solves
In the words people actually use when they get in touch, rather than in the words the technology uses.
- “Reporting is a monthly Excel ritual nobody trusts”
- “A dashboard exists and no one has opened it since the launch demo”
- “You have data and no idea which questions it can answer”
- “Someone promised a forecast and delivered a straight line”
Deliverables
What you get
- A refreshable dashboard on a documented data model
- The SQL behind it, readable and commented
- A written analysis of what the data does and does not support
- Where relevant: a forecasting or recommendation model with stated accuracy and limits
- Handover so your team can extend it
Approach
How it is built
- The data model before the visuals, always
- Chart choices the data justifies, not the ones that look impressive
- Forecasting with stated horizons and error bounds — a confident long-range number is fiction
- Explainable recommendations, so a user can see why something was suggested
Process
How it runs
- 1
Question first
Which decisions this should change. Dashboards without decisions go unopened.
- 2
Data audit
What exists, how clean it is, what is missing.
- 3
Model the data
The step most dashboards skip and later pay for.
- 4
Build and validate
Numbers reconciled against a source your team already trusts.
- 5
Handover
Documented, refreshable, extendable.
What it costs
Scope and price agreed on a short call — no obligation, and you get a written figure before anything starts.
Get a figureWhat I need from you
- Read access to the data
- The decisions this reporting should support
- One person who can confirm a number looks right
- Existing reports to reconcile against
Not included
- Building a data warehouse from nothing (a separate, larger piece of work)
- Power BI Pro or Fabric licensing
- Ongoing report maintenance, unless retained
- Forecasts on data that does not support them — I will say so rather than produce one
Related work
Something similar, already built
Motorcycle Match
A recommender that tells you why
A working recommender where each suggestion states the constraints it satisfied and the attributes it matched on.
Read the case study →Air Quality Forecaster
Deep learning on a problem Delhi feels personally
A deployed forecaster with an interactive dashboard, visualising predicted against observed values over the input series.
Read the case study →Data Analytics & Dashboards — questions people ask
Power BI, or something else?
Power BI where your organisation already lives in Microsoft, which is most of the time. Otherwise I will recommend what fits your stack and your team.
Our data is messy. Is that a problem?
It is normal, and cleaning is part of the work. What I will not do is build a polished dashboard on numbers that cannot be reconciled, because that produces confident wrong decisions.
Can you forecast our sales?
Sometimes. It depends on history length, seasonality and how much of the variance is external. I will tell you before quoting whether the data supports a forecast worth having.
Who refreshes it?
Scheduled refresh where the sources allow it; otherwise your team, using the documented process.
Will our team be able to change it?
That is the point of the handover. The model is documented and the SQL is written to be read.
Can you also train our team on it?
Yes — that is corporate training, and it is often the highest-return part of the engagement.
Related services
Start here
Tell me what you are trying to do
You get a written figure and a scope before anything begins. If this is not the right service for the problem, I will say which one is — or that none of them are.
+91 99991 03353
Opens the chat with your message already written. Usually answered the same day.
[email protected]
Opens your mail app with the subject filled in. Better for anything long.
Roughly what you have already, what a good outcome looks like, and any budget or deadline you are working to — that is enough for a first reply with a real figure in it.