Data Analyst

Course Overview

This course provides a comprehensive introduction to data analysis, focusing on querying data with SQL and creating impactful visualizations using Power BI, Tableau, and Looker Studio. Through hands-on projects and real-world scenarios, learners will gain proficiency in extracting, transforming, and visualizing data to support data-driven decision-making.

SECTION 1: Introduction to Data Analysis

Duration:1 week

Topics:

Role of a data analyst and career opportunities
Overview of data analysis tools and workflows
Understanding data types: structured vs. unstructured
Introduction to Business Intelligence (BI) and its applications

Learning Outcomes:

Understand the scope and responsibilities of a data analyst
Recognize the role of SQL, Power BI, Tableau, and Looker Studio in data analysis

Activities:

Case study: Analyzing a business problem using data
Tool setup: Installing MySQL, Power BI Desktop, Tableau Desktop/Public, and accessing Looker Studio

SECTION 2: SQL for Data Analysis

Duration:3 weeks

Topics:

– Week 1:SQL Fundamentals

Introduction to relational databases and MySQL
Writing basic SELECT queries
Filtering data with WHERE and sorting with ORDER BY
Working with operators (AND, OR, LIKE, IN)

– Week 2:Intermediate SQL

Aggregating data: COUNT, SUM, AVG, MIN, MAX
Grouping data with GROUP BY and HAVING
Joining tables: INNER JOIN, LEFT JOIN, RIGHT JOIN
Subqueries and nested queries

– Week 3:Advanced SQL

Working with dates, strings, and NULL values
Creating views and temporary tables
Optimizing queries for performance
Case studies: Writing complex queries for business scenarios

Learning Outcomes:

Query and manipulate data from relational databases
Perform advanced data aggregation and joins
Optimize SQL queries for efficiency

Activities:

Hands-on exercises: Querying a sample sales database
Project: Analyze customer and sales data to identify trends

Resources:

MySQL Workbench for query execution
Sample datasets (e.g., retail, e-commerce)

Section 3: Data Visualization with Power BI

Duration:3 weeks

Topics:

– Week 1:Getting Started with Power BI

Introduction to Power BI Desktop and Power BI Service
Connecting to data sources (Excel, SQL databases, CSV)
Data transformation with Power Query Editor
Basic visualizations: Bar charts, line charts, pie charts

– Week 2:Intermediate Power BI

Data modeling: Creating relationships, star, and snowflake schemas
Introduction to DAX (Data Analysis Expressions): Calculated columns and measures
Creating interactive dashboards and reports
Using filters, slicers, and drill-downs

– Week 3:Advanced Power BI

Advanced DAX: Time intelligence, CALCULATE, and FILTER functions
Publishing and sharing reports on Power BI Service
Real-time data updates and scheduled refreshes
Best practices for report design and accessibility

Learning Outcomes:

Build and transform data models in Power BI
Create interactive dashboards and reports
Use DAX for advanced calculations and insights

Activities:

Hands-on: Build a sales performance dashboard
Project: Create an HR analytics report with employee data

Resources:

Power BI Desktop
Sample datasets (e.g., financial, HR)

Section 4: Data Visualization with Tableau

Duration:3 weeks

Topics:

– Week 1:Tableau Basics

Introduction to Tableau Desktop and Tableau Public
Connecting to data sources (Excel, SQL, cloud services)
Creating worksheets: Bar, line, and scatter plots
Using filters, sorting, and hierarchies

– Week 2:Intermediate Tableau

Building calculated fields and parameters
Creating maps, heatmaps, and tree maps
Designing dashboards with interactivity
Storytelling with Tableau: Presenting insights

– Week 2:Advanced Tableau

Advanced calculations: Level of Detail (LOD) expressions
Working with large datasets and performance optimization
Publishing dashboards to Tableau Public/Server
Case studies: Visualizing complex business data

Learning Outcomes:

Create visually compelling and interactive dashboards
Use calculated fields and LOD expressions for advanced analysis
Share and collaborate on Tableau dashboards

Activities:

Hands-on: Build a regional sales dashboard
Project: Create a marketing campaign performance report

Resources:

Tableau Desktop or Tableau Public
Sample datasets (e.g., marketing, logistics)

Section 5: Data Visualization with Looker Studio

Duration:2 weeks

Topics:

– Week 1:Getting Started with Looker Studio

Introduction to Looker Studio and its integration with Google ecosystem
Connecting to data sources (Google Sheets, BigQuery, third-party connectors)
Creating basic visualizations: Bar charts, time series, and pie charts
Using filters and date range controls

– Week 2:Advanced Looker Studio

Data blending: Combining multiple data sources
Creating custom metrics and calculated fields
Designing interactive reports with dynamic controls
Sharing and collaborating on reports

Learning Outcomes:

Build and share reports in Looker Studio
Blend data from multiple sources for comprehensive insights
Leverage Google ecosystem integrations

Activities:

Hands-on: Build a web analytics report using Google Analytics data
Project: Create a cross-channel marketing performance dashboard

Resources:

Looker Studio (web-based)
Sample datasets (e.g., Google Analytics, e-commerce)

Section 6: Statistics for Data Analysis

Duration:1 weeks

Topics:

Descriptive statistics: Mean, median, mode, standard deviation
Data distributions and normality
Correlation and basic regression concepts
Applying statistics in BI tools for trend analysis

Learning Outcomes:

Interpret statistical measures in data analysis
Apply statistical concepts to validate insights

Activities:

Exercises: Calculate and interpret statistics in Excel and BI tools
Case study: Identify trends using statistical measures

Section 7: Capstone Project

Duration:2 weeks

Objective:Apply skills in SQL, Power BI, Tableau, and Looker Studio to solve a real-world business problem

Project Examples:

Retail: Analyze sales and inventory data to optimize stock levels
E-commerce: Visualize customer behavior and campaign performance
HR: Create an employee performance and retention dashboard

Deliverables:

SQL queries to extract and clean data
Dashboards in Power BI, Tableau, and Looker Studio
Presentation of insights and recommendations

Learning Outcomes:

Synthesize skills across tools to deliver actionable insights
Communicate findings effectively to stakeholders

Section 8: Career Preparation

Duration:1 week

Topics:

Building a data analyst portfolio
Resume and LinkedIn profile optimization
Preparing for data analyst interviews
Overview of certifications: Microsoft PL-300 (Power BI), Tableau Desktop Specialist

Learning Outcomes:

Create a professional portfolio showcasing projects
Prepare for job applications and interviews

Activities:

Build a portfolio with capstone project deliverables
Mock interviews and SQL/BI tool challenges

Course Duration

Total: 16 weeks (assuming 5-10 hours per week)
Format: Self-paced with instructor-led sessions (optional)

Prerequisites

Basic computer literacy
No prior experience required; curiosity for data and problem-solving is key
Access to a PC with internet for tool installations (MySQL, Power BI Desktop, Tableau Desktop/Public)

Tools and Software

SQL: MySQL Workbench (free)
Power BI: Power BI Desktop (free)
Tableau: Tableau Desktop (trial) or Tableau Public (free)
Looker Studio: Web-based (free with Google account)
Excel: Microsoft Excel (optional for data cleaning)

Recommended Resources

Online platforms: Udemy, Coursera, DataCamp
Free tutorials: Microsoft Learn (Power BI), Tableau Public, Google Looker Studio documentation
Datasets: Kaggle, Google BigQuery public datasets