Introduction to Data Analytics for Business Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This beginner-friendly course provides a concise introduction to data analytics in business, guiding learners through the journey from raw data to actionable insights. You'll explore how organizations use data to drive decisions, understand key analytical frameworks, and gain hands-on experience with SQL for data extraction. The course spans approximately 7–8 hours total, delivered across four focused modules, making it ideal for beginners seeking foundational knowledge in under a week.
Module 1: Data and Analysis in the Real World
Estimated time: 2 hours
- Think analytically using the Information–Action Value Chain
- Understand how real-world events are captured as data
- Learn how data flows into business actions
- Introduction to relational databases and SQL basics
Module 2: Analytical Tools
Estimated time: 2 hours
- Explore relational databases and their role in analytics
- Introduction to Big Data technologies
- Cloud-based data platforms and storage solutions
- Data virtualization techniques
Module 3: Data Extraction Using SQL
Estimated time: 1 hour
- Write basic SQL queries to retrieve data
- Use commands to filter and sort results
- Combine data using JOINs and subqueries
Module 4: Real-World Analytical Organizations
Estimated time: 2–3 hours
- Identify key roles in data analytics teams
- Understand organizational structures in data-driven companies
- Learn about data governance, quality, and privacy standards
Prerequisites
- Familiarity with basic business concepts
- No prior coding or data experience required
- Access to a web browser for hands-on exercises
What You'll Be Able to Do After
- Explain how data transforms into business actions
- Apply the Information–Action Value Chain to real scenarios
- Query relational databases using SQL
- Recognize core data tools and technologies in business analytics
- Understand the importance of data governance and team roles in analytics