3-days Instructor-led

Course Description 

This 3-module Data Analytics course equips professionals with the skills to interpret, analyze, and present data effectively. The course covers the full analytics workflow: sourcing data, cleaning and transforming it, generating insights, and creating visual reports. Participants will work with tools such as Excel, SQL, Python, and Tableau to apply analytical thinking to real-world scenarios. 

Key Takeaways 

• Learn how to frame business questions and derive insights from data 

• Work with structured datasets using SQL and Excel 

• Apply data transformation and summarization techniques 

• Create dashboards and visual reports using Tableau 

• Use descriptive and diagnostic analytics techniques to uncover trends and patterns 

• Translate raw data into meaningful narratives for decision-makers 

Prerequisites 

• Familiarity with spreadsheets or data tables 

• Basic problem-solving and logical reasoning skills 

• No programming experience required, but a willingness to learn simple code (SQL or Python) is helpful 

Module 1: Introduction to Data Analytics and Data Preparation 

• Overview of Data Analytics and Business Use Cases 

• Types of Analytics: Descriptive, Diagnostic, Predictive, and Prescriptive 

• Introduction to Data Types, Sources, and Formats 

• Using Excel and SQL for Basic Data Handling 

• Data Cleaning and Transformation Techniques 

• Hands-On Lab: Import, clean, and organize raw data in Excel and SQL 

Module 2: Exploratory Data Analysis and Visualization with Tableau 

• Identifying Key Metrics and KPIs 

• Using Summary Statistics to Explore Data 

• Creating Visual Reports with Tableau: Charts, Filters, and Dashboards 

• Enhancing Visuals with Calculated Fields and Parameters 

• Detecting Patterns, Trends, and Anomalies 

• Hands-On Lab: Build a Tableau dashboard to visualize business performance 

Module 3: Diagnostic Analysis and Insight Communication 

• Asking the Right Questions: Root Cause Exploration 

• Segmenting Data for Deeper Insights (e.g., by region, product, or customer group) 

• Comparative and Time-Based Analysis Techniques 

• Communicating Findings with Clarity and Impact 

• Storytelling with Data: Structuring Reports for Stakeholders