How I'd become a data analyst (if i had to start over) in 2024

Agatha
12 Jan 202408:57

Summary

TLDRIn this video, a seasoned data analyst outlines a six-month roadmap for aspiring analysts. The first three months focus on mastering Excel, SQL, and Tableau, emphasizing practical skills. Month four is dedicated to creating impactful projects that demonstrate analytical abilities. Finally, the last two months involve preparing for job applications and interviews, with a strong emphasis on technical SQL assessments. This structured approach, requiring about 3-4 hours of daily study, equips learners with the essential skills and experiences to successfully enter the data analysis field.

Takeaways

  • 😀 Create a 6-month roadmap for becoming a data analyst, focusing on skills, projects, and job applications.
  • 📚 Spend the first three months learning key tools: Excel, SQL, and Tableau in that order.
  • 💡 Excel is essential; aim for an intermediate level, mastering functions like VLOOKUP and pivot tables.
  • 🔍 SQL is fundamental for data analysis; focus on select statements, joins, and group functions.
  • 📊 Tableau is recommended for visualization skills, but knowledge of other BI tools is also beneficial.
  • 📝 Undertake 3-4 projects that showcase a combination of skills and solve real problems.
  • 📈 When working on projects, start with a clear problem statement to guide your analysis.
  • 🌐 Utilize free data sources like Kaggle and data.gov for your projects.
  • 💼 Update your resume and LinkedIn profile as part of your job application process in the last two months.
  • 🎯 Prepare for technical assessments in SQL, using platforms like Leetcode and HackerRank to practice.

Q & A

  • What is the primary focus of the first three months in the data analyst roadmap?

    -The primary focus is on developing skills, specifically learning Excel, SQL, and Tableau.

  • Why is Excel considered the first tool to learn for aspiring data analysts?

    -Excel is the most popular BI tool used across industries and is likely to be used in entry-level data analyst roles.

  • What level of proficiency should one aim for in Excel?

    -An intermediate level is recommended, including knowledge of key functions like VLOOKUP, pivot tables, and data visualizations.

  • How should one practice SQL according to the roadmap?

    -Practice by working with personal datasets, like bank statements, and using online resources for interactive learning.

  • What makes SQL essential for a data analyst?

    -SQL is fundamental for interacting with databases and handling large datasets, which is critical in data analysis roles.

  • What is the recommended approach for learning Tableau?

    -Aim to reach an intermediate user level, focusing on connecting data, adding multiple data sources, and creating visualizations.

  • Why are projects important in the roadmap?

    -Projects showcase practical skills to recruiters and demonstrate the ability to apply tools and solve real problems.

  • What type of projects should aspiring analysts create?

    -Projects should combine different skills, solve specific problems, and tell a story through data analysis.

  • What resources can be used for finding datasets for projects?

    -Free resources include Kaggle, Reddit, data.gov, and guided projects on platforms like Coursera.

  • What should candidates focus on during the job application process?

    -Candidates should update their resume and LinkedIn profiles, practice technical interview questions, especially SQL assessments.

Outlines

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Transcripts

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Связанные теги
Data AnalysisCareer ChangeSkill DevelopmentJob ReadinessExcelSQLTableauPortfolio ProjectsInterview PrepSelf-Study
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