AI data analysis and reporting training: from spreadsheet to decision
Full day (about 7 hours) Up to 10 people On site in Istanbul or online 49.900 TL + VAT
Data analysis and reporting
What is this program?
AI data analysis and reporting training is a full-day, hands-on program in which teams from different departments learn on their own data to analyse Excel, CSV and system exports with ChatGPT and Claude, generate charts, interpret variances and automatically draft the management report. Data privacy and figure verification rules form the backbone of the program.
Every department produces data, but very few have the time and the tools to interpret it. Preparing a report is done by copy and paste, the commentary section stays empty and management looks at the table and asks "so what does this mean". AI fills this gap: it reads the table, finds the variance, explains it in plain language and draws the chart.
The program is designed for teams who are not data scientists. No code is written, but AI is made to write code. The team brings its own real data and leaves at the end of the day with a flow that produces its recurring monthly report with AI.
Who is it for?
Whoever prepares reports in each department
Sales, marketing, operations, HR, finance: anyone who prepares a monthly report.
Managers and analysts
Those who need to draw decisions from data but have no data team.
Small and medium-sized companies
Those who want to process data without setting up a separate analysis team.
Program flow: six modules
Talking takes at most a fifth of the day. The rest is hands-on production on your own files, each module ending with a piece of real work.
Data privacy and the verification rule
Which data goes into which tool, anonymisation, corporate accounts. A source check for every figure. The first module of the program.
Feeding data to the tool and cleaning it
Uploading Excel and CSV files, cleaning messy data, merging, finding missing and faulty rows.
Analysis and variance detection
Trends, comparisons, segment analysis, the difference from the previous period. Having AI analyse by writing code, and explaining the result in plain language.
Charts and visualisation
Choosing the right chart type, generating charts with AI, making them presentation-ready.
Report draft and management summary
From analysis to the summary management will read, variance explanations, a recommendation list. A template that repeats in the same format every month.
The automation step
Tying the recurring report to project context, regenerating it with a single command, preparing for handover to an agent later.
Real work scenarios
The kind of tasks the day is built around. Yours replace these after the discovery call.
Monthly sales report
Analysis by region, product and representative from a CRM export, plus a management summary.
Ad performance report
Campaign comparison and a budget recommendation from Google Ads and Meta data.
Customer satisfaction survey
Grouping open-ended answers into themes and interpreting the score distribution.
Stock and order analysis
Which product turns at what speed, where stock is piling up, explained in plain language.
Staff turnover analysis
Extracting reasons for leaving and seasonal patterns from HR data.
Board presentation
A one-page summary and 5 charts from all departments' data.
Tools used
Skills come before tools. The current model comparison with prices is on the AI models page.
What the team leaves with
- A written rule for data privacy and figure verification
- A method for cleaning and merging messy data
- A flow for variance detection and plain-language interpretation
- Presentation-ready chart generation
- A ready template and flow for the report that repeats every month
Format and what is included
- Discovery call: your industry, the team's daily work and the three targets of the day
- Content built on your own files, not a generic slide deck
- Full day (about 7 hours) hands-on, on site in Istanbul or online
- Team playbook with everything built during the day
- 30 days of Q&A support after the training
- Certificate of participation
Scopes beyond the standard package (more than 10 people, several locations, half-day or multi-day formats, integration work) are quoted separately.
The same standard package for every program.
How it works
15-minute call
We talk about the team, the work and whether this program fits. No commitment.
Discovery and preparation
A short session with the team lead. The day is built on your real tasks.
Training day
Everyone on their own laptop, on their own work, the whole day.
30 days of support
Questions that come up while actually using AI at work get answered.
Your trainer
Sefa Aydın
AI trainer and consultant. Years of producing design, advertising and software for the Türkiye projects of world-renowned luxury brands, founder of the agency Rebel Co. Group. I use these tools on real client work every day, and I teach what I use.
About me →Frequently asked questions
Do I need to know how to code for data analysis?
No. In the program no code is written by hand. AI writes it and the result is explained in plain language. The participant describes what they want, the tool produces the analysis and the chart, and the participant verifies the result.
Does AI make mistakes in analysis?
It can, which is why a verification step for every output is the rule. In the program AI is made to do the calculation with code, not by guessing. Figures are compared against the source table.
How much does data analysis training cost?
The standard package is a full day for up to 10 people at 49,900 TL plus VAT. The discovery call, content preparation based on the team's data, report templates and 30 days of Q&A support are included. Data from multiple departments is scoped by proposal.
Is it safe to upload company data to AI?
Yes, with a corporate account and anonymisation. The first module of the program puts which data may be uploaded under which conditions into a written rule. There is a separate rule for tables containing personal data.
We use Power BI or Tableau. Is this training still needed?
It is a different job. Those tools visualise, while AI interprets and writes the report. The two are used together: data is exported from the tool, AI explains the variance and writes the management summary.
Does the report become fully automatic?
The program sets up a flow that can be regenerated with a single command, but every output passes a human check. If fully automatic production and distribution is wanted, that falls under the AI agents program.
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Last updated: 14 September 2026
Request a proposal for your team
Tell me the team size and what you want to solve. I reply the same day.