An online intensive in product analytics covering metrics, SQL, and Tableau. Practical tasks are based on a real dataset.
Language of course:
Ukrainian
Format of the event:
Online
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Course overview
Description generated based on course syllabus and open data.
What the Analytics Bootcamp in product analytics includes
The program focuses on data verification and analysis, defining key product metrics (including the North Star), applying SQL for data extraction, and building visualizations in Tableau. The format combines concise theory with hands-on practice on a real dataset.
Analytics Bootcamp format and schedule
- Online delivery: 2 days, approximately 10 hours.
- Practical exercises immediately after theory blocks.
- Preparation materials provided before the start.
Curriculum: product metrics, SQL, Tableau, North Star
- Data quality checks, events and attributes.
- Product metrics: activation, retention, conversion, North Star metric.
- SQL for analytics: SELECT, JOIN, aggregates, result validation.
- Tableau: dashboards, charts, filters, basic design principles.
- Insight generation and hypothesis framing.
Lecturer and background
Liliya Lutsenko, Senior Product Analyst (Wise). Experience: product analytics at Wise (~37.7M site sessions/month, ~10M app users), analytics for 4 BetterMe apps (100M+ users across 190 countries), Datamonster by Amplitude winner (2020, 2021), former consultant at KPMG (Big Four).
Who the Analytics Bootcamp is suitable for, and who it is not
Best fit
- Junior Product Analysts — to systematize data analytics principles, metrics, and practice SQL and Tableau.
- Data Analysts — to refresh insight generation and visualization tooling.
- Marketers and web analysts — to analyze user behavior and configure correct metrics.
- Product Managers — to choose product metrics and assess changes.
Not the best fit
- Those seeking a pure no‑code path without SQL.
- Those focused on a narrow advanced topic (e.g., ML or experimentation at scale).
- Those expecting theory only without practical tasks.
From need to measurable effect: problem → addressed in the intensive
- Unclear product metrics → framework for metrics and North Star selection.
- Fragmented data → quality checks and event/attribute alignment.
- Ad-hoc SQL usage → structured practice with JOIN and aggregations.
- Hard to spot patterns → Tableau dashboards and chart reading.
- Unstructured hypotheses → insight frameworks and prioritization.
Comparison with alternatives in data/analytics
- Self-paced courses: flexible but limited feedback; here, exercises are reviewed.
- Long programs: deeper but time-consuming; this format is focused and concise.
- Books/videos: theory without application; here, SQL and Tableau on real data.
- Internal onboarding: company-specific; here, general product analytics principles.
Competencies covered by the Analytics Bootcamp
- Building a product metrics system and defining a North Star metric.
- Foundational to intermediate SQL for analytics tasks.
- Structuring insights and framing hypotheses.
- Data visualization in Tableau: creating overview dashboards.
- Data verification practices and calculation validation.
Course Description
Lecturer
Lilia Lutsenko
Senior Product Analyst at fintech company Wise
- collects and analyzes product data in the fintech startup Wise with monthly traffic on the site of 37.7 million sessions and 10 million users of the application- analyzed 4 mobile applications from BetterMe, which are used by more than 100 million users from 190 countries- in 2020 and 2021 became the winner of the international Datamonster award from Amplitude- worked as a consultant in the audit company KPMG, which is a member of the "big four"
Evaluation
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