Python
Course Description
In today’s data-driven world, businesses are constantly seeking ways to make smarter decisions backed by data. Our Business Analytics course is designed to help you turn raw data into meaningful insights that drive real impact. Whether you’re a student, a working professional, or an aspiring analyst, this course will equip you with the tools and techniques used by top companies to analyse data, identify trends, and make data-backed decisions.
You’ll explore how data can influence strategy, performance, and growth. From Excel-based analysis to real-time dashboards and case studies, this course makes analytics easy to understand—even if you’re just starting out.
What You’ll Learn From This Course
- Fundamentals of Business Analytics – Understand the key concepts, importance, and applications of analytics in real business scenarios.
- Data Handling Using Excel – Learn how to organise, clean, and analyse data using functions, pivot tables, and more.
- Descriptive & Predictive Analytics – Explore how to summarise data and predict future outcomes using simple models.
- Data-Driven Decision Making – Gain practical skills to draw insights from data and turn them into strategic actions.
By the end of this course,
At the end of this course, gain the hands-on experience and analytical skills needed to succeed in the field of Business Analytics. Each module is built around real-world applications, enabling practical understanding of data analysis, dashboards, and decision-making. Be prepared to approach business problems with the mindset and tools of a professional analyst.
Curriculum
- 18 Sections
- 60 Lessons
- 100 Hours
Expand all sectionsCollapse all sections
- EXCELThe Advanced Excel course equips you with essential skills for data management, analysis, and visualization using advanced formulas, PivotTables, and charts. Learn to create interactive dashboards and automate tasks for efficient data-driven decision-making.0
- Module 1: Data Management in Excel4
- Module 2: Data Analysis and Charting4
- 3.1PivotTables and Pivot Charts: Creating and customizing PivotTables and charts.
- 3.2Slicers and Timelines: Dynamic filtering of PivotTables and charts.
- 3.3Advanced Charting: Creating Waterfall, Funnel, and Combo charts.
- 3.4Conditional Formatting: Highlighting data patterns with color scales and icons.
- Module 3: Excel Formulas4
- Module 4: Data Validation and What-If Analysis4
- Module 5: Dashboard Creation and Consolidation4
- POWER BIThis Power BI course covers all essential aspects, from importing and transforming data to creating advanced visualizations and reports. Students will learn to integrate Power BI with other tools, optimize data models, and share and collaborate on reports, with a focus on hands-on case studies and real-world applications.0
- Module 1: Introduction to Power BI4
- Module 2: Data Transformation and Advanced Modeling4
- Module 3: Visualizations and Reports4
- Module 4: Power BI Service and Sharing4
- Module 5: Advanced Power BI Features and Case Studies4
- TABLEAUThis Tableau course provides a comprehensive understanding of data visualization, from basic visualizations to advanced analytics, including data blending and storytelling techniques. Students will also learn to collaborate and manage Tableau workbooks effectively using Tableau Server.0
- Module 1: Introduction to Tableau and Data Visualization Basics4
- Module 2: Intermediate Data Visualization Techniques4
- 15.1Introduction to advanced chart types: Heatmaps, box plots, and treemaps.
- 15.2Customizing visualizations with colors, labels, and annotations.
- 15.3Understanding data blending and joins to combine multiple data sources.
- 15.4Creating interactive dashboards using actions, filters, and design best practices.
- Module 3: Advanced Analytics with Tableau4
- 16.1Working with calculated fields and parameters, including advanced calculations (IF statements, LOD expressions).
- 16.2Implementing forecasting models and analyzing trends in data.
- 16.3Visualizing spatial data through geographic mapping and customizing maps.
- 16.4Exploring advanced analytics such as seasonality and identifying trends in Tableau.
- Module 4: Data Storytelling and Presentation Techniques4
- 17.1Understanding the principles of data storytelling and structuring your narrative.
- 17.2Incorporating storytelling into data visualization with story points and annotations.
- 17.3Effective communication techniques for presenting insights to non-technical stakeholders.
- 17.4Presenting data findings confidently and clearly using Tableau’s visualization features.
- Module 5: Tableau Server and Collaboration4
Pass Percentage