From beginner to professional Data Analyst
Not just another Power BI course. A complete program that prepares you for real workplace situations: Excel, SQL, Power BI, Python, AI and storytelling to become a junior Data Analyst.
From €490 (regularly €990), one-time payment, lifetime access
Welcome session Saturday, December 19 · launch price until December 18
No technical prerequisites. If you can use a computer, you can become a Data Analyst.
Throughout the bootcamp, you work for a fictional company, just like on the job. Here is a typical mission, followed from start to finish.
“Our sales in the West region have been falling for three months. I want to understand why, and what to do about it.”
You explore the sales export, spot duplicates, inconsistent date formats and missing values, then document every fix.
You write the queries that join sales and regions to measure how revenue changes, region by region.
You model the data, create DAX measures and an interactive dashboard leadership can filter on their own.
You isolate the cause, size the impact and present a clear recommendation to the leadership team.
Kora Market is a fictional company: the data is simulated for the exercise. In the bootcamp, you carry out a mission like this from start to finish.
12 progressive blocks. Every module combines theory, demonstrations and hands-on exercises.
Data fundamentals, roles, the data lifecycle, KPIs and data-driven decisions.
Cleaning, advanced formulas, XLOOKUP, pivot tables, charts and Power Query.
SQL fundamentals for querying and filtering databases.
Joins, subqueries, window functions and performance tuning.
Data import, modeling, table relationships and cleaning in Power Query.
Measures, calculated columns and time intelligence functions for time-based analysis.
KPIs, interactive charts, geographic maps, drill-down and advanced tooltips.
Connecting to data sources, building visualizations, calculations, filters, interactive dashboards and publishing to Tableau Public.
Data manipulation and visualization with the essential Python libraries.
Handling missing values, duplicates, outliers and standardizing formats.
Correlations, distributions, segmentation and generating insights from data.
Which chart for which message? The golden rules of data visualization.
Architecture, visual hierarchy, filters and interactivity of an effective dashboard.
Presentation technique, managing nerves and communicating with decision-makers.
Turning data into concrete action and convincing a leadership team.
Using ChatGPT, Claude, Gemini and NotebookLM to speed up your analysis work.
Code faster with the AI assistant: generating Python, SQL and DAX.
Generate visualizations, DAX measures and insights automatically inside Power BI.
Prompting techniques to generate SQL queries, analyses and reports.
Acquisition cost, customer value, churn, funnel and campaign optimization.
Profitability, cash flow, budget, variance and financial reporting.
Turnover, recruitment, absenteeism and HR metrics.
Inventory management, delivery, turnover and logistics optimization.
Sales analysis, products, customer behavior and average order value.
Hospital activity, performance, quality and health metrics.
Design principles, grids, color, typography and visual hierarchy.
User experience applied to dashboards and interactive reports.
The golden rules of dataviz according to Tufte, Few and Cairo.
The pitfalls of visualization: misleading charts, scales, 3D and clutter.
Data preparation, cleaning and transformation with visual no-code workflows. Blending, macros and pipeline automation.
Automating recurring report generation with Python and Power BI.
Generate automated presentations from your analyses.
Automated professional Excel reports with formatting and charts.
Published, shareable PDF reports for stakeholders.
Publishing your projects, documenting your code and building your technical presence.
Optimizing your profile, publishing data content and growing your network.
Writing a data-focused résumé that showcases your skills and projects.
Building an online portfolio that impresses recruiters.
Work on realistic datasets drawn from 7 industries.
Loan analysis, default detection and branch performance.
Claims, fraud detection and customer portfolio analysis.
Sales, churn, product analysis and recommendations.
Cancellations, customer satisfaction and usage analysis.
Hospital activity, waiting times and quality metrics.
Production, quality, maintenance and inventory management.
Recruitment, turnover, training and performance.
The tools most in demand for Data Analyst roles.
Every participant completes a full Data Analyst assignment, just like at work:
To earn the certification, every learner must:
3 bonus modules to take your preparation further.
Ten weeks. Plan for 10 to 14 hours a week: a demanding but manageable pace.
Four levels of support. The same program, with different guidance.
Limited spots. The launch price is available until December 18, 2026. Prices go up after that.
Have another question? Message us on WhatsApp and we’ll get back to you quickly.
A live welcome session takes place on Saturday, December 19, 2026: introductions, the program and setting up your tools. Classes start on Monday, January 4, 2027, and end on Friday, March 12, 2027. The launch price is available until December 18, 2026.
No. The bootcamp starts from scratch: if you can use a computer, you can follow it. Basic Excel skills help, but they are not required.
Plan for 10 to 14 hours a week over ten weeks: a 2.5-hour live class, a 2.5-hour hands-on workshop, an optional 1-hour Q&A and 5 to 8 hours of independent work (exercises and mini-projects).
Every session is recorded. Unlimited session replays are included in every plan, with lifetime access.
Excel, SQL (PostgreSQL), Power BI, Tableau, Alteryx and Python (Pandas), plus AI applied to data analysis. A computer and a stable internet connection are all you need; in each module we point you to the free versions of the tools whenever they exist.
Every plan covers the same program; only the level of support changes. Essential gives you all 38 modules, with your final project reviewed. Professional adds exercise reviews, the community and the bonuses. Career adds group mentoring, a portfolio, a real-world project and interview prep. Executive adds one-on-one mentoring and career support.
Yes. Prices shown are for a one-time payment, but we can set up installments: just message us on WhatsApp. If you live in the CFA franc zone, you’ll be offered pricing in CFA francs.
You get a full refund at any time until the end of the first week of classes: just email contact@datasai.fr. After that, if something unexpected stops you from continuing, you can transfer your enrollment to the next cohort for free. If we postpone or cancel a cohort, you choose between a full refund and a transfer. Refunds go back to your original payment method within 14 days of your request.
The DataSAI Data Analyst certification is included in every plan. To earn it, you complete each block’s exercises, deliver 8 mini-projects, build a portfolio and pass the final project, presented to a panel of recognized experts.
Not yet: the process with the government is underway. What gives the DataSAI certification its value is what it proves. You earn it by demonstrating your skills on practical cases: validated exercises, mini-projects, a portfolio and a final project presented to a panel of recognized experts. That’s exactly what recruiters look at.
Join the January cohort and launch your career in data.