Data Analyst Roadmap
- [Himeji Castle, Japan]
- Overview
Data analysts are professionals who collect, clean, analyze, and communicate insights from data. They work across industries to help organizations make informed, evidence-based decisions.
To become a data analyst, you need to acquire a strong foundation in statistics, learn programming languages like Python or R, master data visualization tools like Tableau, gain experience working with real datasets through projects, develop a portfolio showcasing your work, and ideally, pursue a relevant bachelor's degree or consider a master's in data analytics depending on the role you aim for; strong communication skills to present findings effectively are also crucial.
- 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬 & 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬
Understand statistical concepts like probability theory, hypothesis testing, linear algebra, hypothesis testing, regression analysis, and probability distributions. and more!
- 𝐏𝐲𝐭𝐡𝐨𝐧 & 𝐒𝐐𝐋
Learn Python and/or R for data manipulation and analysis. Gain proficiency in SQL for querying and extracting data from databases.
Master Python libraries such as Pandas and Matplotlib, and SQL operations such as JOIN and window functions for data manipulation
- 𝐃𝐚𝐭𝐚 𝐖𝐫𝐚𝐧𝐠𝐥𝐢𝐧𝐠 & 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧
Clean, transform, and visualize your data using powerful tools like like Tableau, Power BI, or Jupyter Notebook to present findings visually.
- 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠
Dive into supervised and unsupervised learning using algorithms like decision trees, K-means clustering, and model evaluation techniques.
- [Data Analyst Roadmap]
- Practical Experience
Work on personal data analysis projects using real datasets to practice your skills and build a portfolio. Learn how to clean and prepare messy data for analysis. Practice building data models to identify patterns and trends.
- Portfolio Development
Showcase your work: Create a portfolio that demonstrates your data analysis capabilities through projects you've completed, including visualizations and key insights.
- Soft Skills
Develop critical thinking, communication and storytelling skills to transform data into actionable insights!
Develop the ability to interpret data and communicate findings clearly to non-technical audiences through presentations and reports.
- Data Analysis vs Data Analysts
Data analysis is the systematic process of examining, cleaning, transforming, and modeling data to discover valuable insights, which is enriched by the essential data analyst skills.
These skills include statistical analysis capabilities, data processing using tools such as Python or R, and the ability to create compelling data visualizations. Data analysis leverages these capabilities to identify patterns, correlations, and trends in data sets to enable informed decision making across industries.
By employing techniques such as data mining and machine learning, data analysts play a key role in transforming raw data into actionable insights to drive business strategy and operational efficiency
[More to come ...]
