Data Analytics
Data analytics services
Answer one specific business question from data you already have, with the definition written down.
The problem
Two people walk into the same weekly review with two different sales figures. One pulled from the CRM, one from the accounts sheet, and nobody can explain why they differ. The meeting ends without a decision because nobody is sure which number to trust. This is not a technology problem. It is a definition problem: nobody has written down what "sales this month" means. Does it include returns? Proforma invoices? Orders placed but not dispatched? Until that definition is agreed and encoded somewhere, any analysis you run will produce a different answer from the one your colleague runs.
Everyone finally quotes the same number.
Built for: Teams where two people bring two different answers to the same meeting.
What we deliver
One question, written down. We start by writing the question and the definition on paper before touching any data. If two people in the room cannot agree on the definition, we surface that first — no point in building an answer to a question nobody agrees on.
Data audit before analysis. We check whether the data you have is actually good enough to answer the question reliably. If it is not, we tell you what is missing rather than producing an answer that looks confident but rests on gaps.
A repeatable answer. The result is not a one-time spreadsheet someone made once. It is a documented query or process that anyone can rerun next month and get a consistent result.
One owner per number. Every metric we deliver gets assigned to one person and one source. When the number looks wrong, there is one place to look and one person to call.
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Not sure which of these fits? See the whole data engineering practice, or read what we build for your industry.
Tell us what’s slow.
Describe the job eating your team’s day. We’ll tell you straight whether an agent is the right fix — and if it isn’t, we’ll say so.
Frequently asked questions
- We have years of data. Can you analyse all of it at once?
- You can, but you usually should not. A large historical analysis with no specific question is expensive to run and rarely actionable. We start with one question that would actually change a decision if the answer surprised you. Once that is answered, the next question is clearer.
- What tools do you use for the analysis?
- Whatever fits the data and the team who will read it. Sometimes that is a SQL query against your database. Sometimes it is a structured Google Sheet with named ranges. We do not default to expensive platforms when a well-built sheet will do the same job.
- Can you do this if our data is spread across Zoho, Tally, and a bunch of exports?
- Yes, but we will be honest about the effort. Joining data across three disconnected systems takes more work than querying one. We scope the analysis against what your data actually looks like before quoting, so there are no surprises mid-project.