Business Productivity & Data Analytics Bootcamp

Business Productivity & Data Analytics Bootcamp

(MS Office, SQL, Python, and Power BI/Tableau)

Introduction

This course bridges the gap between traditional business productivity skills and modern data analytics expertise. Students will begin by mastering Microsoft Office Suite for workplace productivity and reporting, then advance to Python, SQL, and Power BI/Tableau for data analytics and business intelligence.

By the end, learners will be able to produce professional documents and presentations, analyze and manage data with Excel and SQL, use Python for deeper analysis, and visualize insights with Power BI or Tableau.

Course Objectives

• Master MS Word, Excel, and PowerPoint for professional productivity.
• Understand database concepts and apply SQL queries for structured data.
• Use Excel intermediate and advanced features for data cleaning and reporting.
• Apply Python libraries (Pandas, NumPy, Matplotlib/Seaborn) for data analysis.
• Design interactive dashboards with Power BI or Tableau.
• Integrate productivity tools with analytics tools to support data-driven decision-making.

What You’ll Learn

Business Productivity Tools

• MS Word → reports, formatting, professional docs.
• MS Excel → formulas, functions, pivot tables, charts, and data cleaning.
• MS PowerPoint → designing impactful presentations.

Data Analytics Tools

• SQL → querying databases, joins, aggregations, subqueries.
• Python → data cleaning, analysis, and visualization.
• Power BI/Tableau → dashboards, KPIs, and business reporting.

Integration

• Exporting and analyzing data from Excel to SQL/Python.
• Presenting insights with PowerPoint + BI dashboards.

Prerequisites

• Basic computer literacy.
• No prior coding experience required (Python & SQL taught from basics).

Who This Course is For

• Students & job seekers – who want in-demand skills for today’s job market.
• Professionals – looking to upskill in data analysis & reporting.
• Small business owners – who want to manage and analyze their data effectively.
• Future data analysts – as a strong foundation for more advanced analytics or data science.