Data Analysis with Python & SQL
Business data analysed in Python and SQL to answer specific commercial questions, with charts, a written report and the code.
Custom quote after a short consultation · Timeline agreed in your quote
Scope: We do not write or complete graded academic work (assignments, theses or exams) for submission.
Overview
Data analysis answers practical business questions from the data you already hold: which products or customers drive revenue, how demand changes over time, where costs are rising or which groups behave differently. The focus is commercial decisions, not academic hypothesis testing; for formal statistical tests and methods write-ups, see our Statistical & Research Data Analysis service.
RF ETS uses SQL to query and join data, and Python to analyse it and produce charts. We start by agreeing the questions, check the data is fit for them and then work through the analysis in a notebook so every figure can be traced back to its source.
The Advanced package covers up to five datasets and up to thirty charts, with segmentation, regression or forecasting where the questions call for it. You receive a written report, a short presentation of the findings and the notebook. Data collection is not included, and we do not complete graded academic work.
Who it’s for
- Business owners who want clear answers from sales, customer or operational data
- Marketing teams looking to segment customers or measure what changed
- Managers preparing a decision who need evidence in charts and plain language
- Teams with data in a SQL database but no analyst available
Problems it solves
- Understand what is driving sales, costs or customer behaviour
- Turn raw tables into charts and findings that non-specialists can follow
- Group customers or products into meaningful segments
- Get a forecast or trend view to plan the next period
What RF ETS delivers
- Agreed list of business questions and analysis plan
- Charts covering the key findings
- Written report (Professional) or report and presentation (Advanced)
- Python notebook and SQL queries (Professional and Advanced)
- Segmentation, regression or forecasting outputs where in scope (Advanced)
How we work
Agree the questions
We confirm the business questions, the datasets involved and the format of the findings.
Check and prepare data
We query and join the data with SQL, check quality and prepare it for analysis.
Analyse and chart
We work through the analysis in Python and build charts that answer each question.
Report and walkthrough
We deliver the report, notebook and charts, and walk you through the main findings.
What we need from you
- The datasets or database access needed for the analysis
- The business questions or decisions the analysis should support
- Field definitions and any known data issues
- A contact to clarify business context during the work
How pricing works
This work varies too much for fixed packages. We scope it with you, then send a written quote with price, timeline and deliverables before any work starts.
Tell us what you need
Use the quote form or book a consultation and describe your goal, constraints and deadline.
We scope it with you
We review your material and agree deliverables, assumptions and what is out of scope.
Written quote
You receive a fixed price or milestone plan, timeline and revision terms before any work starts.
Not included
- Data collection (see Web Scraping / Web Research)
- Third-party costs: domains, hosting, paid plugins and themes, software licences, API or AI-model usage fees, data-provider credits
- Work outside the written scope agreed before work starts (handled as an add-on or a custom quote)
- Ongoing support after the delivery and launch-support window unless a support package is bought
Need something different?
Tell us what you need, and we’ll prepare a solution and pricing based on your requirements.
Data Analysis with Python & SQL: common questions
How does pricing work for data analysis?
This service uses fixed packages you can book, based on the number of datasets, charts and the depth of analysis. Extra datasets can be added as add-ons. See the packages above.
How is this different from Statistical & Research Data Analysis?
This service focuses on business questions, using SQL and Python to find patterns, segments and forecasts. The statistical service is built around formal hypothesis tests and methods write-ups for researchers and evidence-based reports.
Can you help with university assignments or theses?
No. We do not write or complete graded academic work, such as assignments, theses or exams, for submission. We support businesses and researchers with analysis and reporting.
Do you collect the data as well?
Data collection is not part of this service. If you need data gathered from public websites or research sources, our Web Scraping or Web Research services can supply it first.
What if we want to explore new questions after the report?
Revisions within the agreed questions are included as listed for your package. New questions or extra datasets are added as add-ons or confirmed in a short quote.
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