Key Skills for Business Analysts in Tech
Introduction
- Business Analyst at Spotify since 2019
- Background in Music Business, not Business Analytics
- Learned through mentorship, colleagues, and trial and error
- Three key skills: Technical Skills, Problem-Solving Skills, Strategic Thinking & Business Sense
Technical Skills
Importance
- Crucial for answering business questions using large data sets
- SQL is indispensable for pulling data from databases
- Excel and Google Sheets are vital for organizing and visualizing data
Learning SQL
- Beginners: DataCamp’s free introductory SQL course for basic logics and commands
- Advanced/Interview Prep: Leetcode or Interview Query for real interview questions from companies like Facebook and Google
- Key SQL Functions: pivot tables, sumifs, vlookups, index/match
- Utilize Google for learning and problem-solving
Data Wrangling in Excel/Google Sheets
- Use raw data from SQL for organizing and visualizing
- Practice by playing around with data for internships or seeking data-related tasks in current roles
- Learn by observing experienced analysts and practicing the tasks
Problem-Solving Skills
Approach to Problem-Solving
- Break down ambiguous questions into smaller, structured pieces
- Use data to answer each smaller question, consolidate insights, and provide business recommendations
Example: Root Cause Analysis (Netflix MAU Decline)
- Impact Size: Duration and magnitude of decline
- Geography: Global or specific market
- Seasonality: Recurring pattern?
- Other relevant questions
Communicating Insights
- Use top-down communication: start with key message, then provide details
- Watch mock case interviews and presentations for structure and style
Relevant Experience
- Internships: Consulting, Insights, Analytics, Market Research
- Focus on learning to turn data into actionable insights and storytelling
Strategic Thinking & Business Sense
Turning Data into Insights
- “So What?” exercise: Think about the actionable insights data provides
- Role play as CEO to think strategically about data application
Example: Netflix MAU Decline
- Impact Size: Alarming decline needs large-scale actions
- Trends: If trends are recurring or abrupt, decide on bug fixes or feature adjustments
- Demographics: Target specific age groups with tailored strategies
Learning and Applying Strategic Thinking
- Pause before data analysis to consider the implications and applications of data
- Regularly converse with cross-functional teams (marketing, user research, product) to understand broader business operations
Conclusion
- Focus on honing technical, problem-solving, and strategic thinking skills
- Gain insights from cross-functional conversations
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