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1. Data Analyst

Description: A Data Analyst focuses on interpreting data and transforming it into meaningful insights. They create reports, dashboards, and visualizations to support decision-making.

Responsibilities:

  • Collect, clean, and analyze data to identify trends and insights.
  • Develop dashboards and reports using tools like Power BI, Tableau, or Excel.
  • Use SQL for querying and retrieving structured data.
  • Work closely with business teams to understand requirements and translate them into data-driven solutions.
  • Perform descriptive and diagnostic analytics to inform business strategies.

Required Skills:

  • SQL, Excel, Power BI, Tableau.
  • Data visualization and storytelling.
  • Statistical analysis and basic machine learning.
  • Data wrangling using Python (Pandas) or R.
  • Strong problem-solving and communication skills.

Essential Topics for Data Analysts

Data Analysts explore, interpret, and visualize data to support decision-making. Their work often feeds into reports, dashboards, and business strategy.

1. Programming and Scripting

  • SQL: Must-know for querying data.
  • Python or R: For deeper analysis and automation.
  • Basic Excel: Formulas, Pivot Tables, Charts

2. Data Exploration

  • Data Cleaning (handling nulls, duplicates)
  • Summarizing data: Aggregations, groupings
  • Understanding distributions

3. Data Visualization

  • Tools: Tableau, Power BI, Looker, Excel
  • Python Libraries: Matplotlib, Seaborn, Plotly
  • Dashboard Creation & Interactivity
  • Design Principles: Clarity, Simplicity, Color Use

4. Business Intelligence (BI)

  • KPIs and Business Metrics
  • Creating Reports and Dashboards
  • Data Storytelling

5. Statistics and Probability

  • Descriptive Statistics
  • Distributions: Normal, Binomial
  • Correlation & Causation
  • Hypothesis Testing, A/B Testing

6. Excel for Data Analysis

  • Formulas: VLOOKUP, INDEX/MATCH
  • Pivot Tables and Slicers
  • Conditional Formatting

7. SQL for Analysts

  • Joins, Aggregations, Filtering
  • Subqueries, CTEs
  • Window Functions

8. Tools and Platforms

  • Google Sheets
  • Jupyter Notebooks
  • Power BI, Tableau, Looker
  • SQL Clients: DBeaver, DataGrip, pgAdmin

9. Communication and Storytelling

  • Translating Data into Business Insights
  • Creating Presentations & Visual Narratives
  • Stakeholder Communication

10. Optional but Useful

  • Basic Machine Learning Awareness
  • Version Control with Git
  • Basics of APIs for pulling data