Next ❯

Data Analytics Fundamentals

  • Learn the basics of data analytics, including key concepts, techniques, and tools.
Note: 👉 Basic knowledge of Python is required before starting the Data analytics course.

  • What is Data Analytics?

    Data Analytics is the process of collecting, cleaning, analyzing, and interpreting data to discover useful insights, patterns, and trends that support better decision-making.

    Data can come from:

    • Databases

    • Excel files

    • Websites and applications

    • Sensors and logs

    Purpose of Data Analytics

    • Convert raw data into meaningful information

    • Identify trends and patterns

    • Improve business performance

    • Support strategic decisions

    Exxample

    A retail company analyzes sales data to:

    • Identify best-selling products

    • Understand customer preferences

    • Plan inventory and discounts

    Data Analytics Flow

    Raw Data → Data Cleaning → Analysis → Insights → Business Decisions


    Types of Data Analytics

    Different types of data analytics answer different business questions.

    Descriptive Analytics

    Question: What happened?

    This type summarizes historical data to understand past performance.

    Examples:

    • Monthly sales reports

    • Website traffic dashboards

    • Yearly revenue charts

    Diagnostic Analytics

    Question: Why did it happen?

    It focuses on identifying the root cause of an event.

    Examples:

    • Analyzing why sales dropped last month

    • Finding reasons for customer churn


    Predictive Analytics

    Question: What is likely to happen?

    Uses historical data and statistical techniques to forecast future outcomes.

    Examples:

    • Sales forecasting

    • Demand prediction

    • Customer behavior prediction

    Prescriptive Analytics

    Question: What should be done?

    Suggests actions based on data insights.

    Examples:

    • Recommending pricing strategies

    • Optimizing delivery routes

    • Suggesting marketing campaigns



    Role of Data Analyst

    A Data Analyst is responsible for transforming data into actionable insights that help businesses make informed decisions.

    Key Responsibilities

    • Collect data from various sources

    • Clean and preprocess data

    • Analyze data using tools and techniques

    • Create reports and dashboards

    • Present insights to stakeholders

    Tools Used by Data Analysts

    • Excel / Google Sheets

    • SQL

    • Power BI / Tableau

    • Python (basic analytics)

    Example Role Scenario

    A Data Analyst in a company:

    • Analyzes customer data

    • Identifies buying patterns

    • Shares insights with marketing team

    • Helps improve sales strategies

    Skills Required

    • Analytical thinking

    • Problem-solving skills

    • Basic statistics

    • Data visualization

    • Communication skills

Next ❯