Module 13 – Pivot Tables for Business Analysis in Excel - Oxtech Academy
Data Analysis
Module 13 - Pivot Tables for Business Analysis in Excel
Data Analysis
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Week 1 – Introduction to Data Analysis
You will be introduced to the meaning and purpose of data analysis and how it supports better decision-making. This section explains how data is collected, organized, interpreted, and used across industries such as business, finance, marketing, healthcare, education, and technology.
You will build a strong foundation for working with data using Excel and Google Sheets. This section covers how to enter, organize, format, sort, filter, and perform simple calculations so you can begin handling data more confidently.
You will understand how to prepare raw data before analysis so your results are accurate, reliable, and useful. In this module, you will work on identifying and fixing common data issues such as duplicates, missing values, wrong formats, spelling inconsistencies, blank rows, and errors. You will also organize your dataset properly, standardize entries, and structure the data in a way that makes it easier to analyze, visualize, and turn into meaningful insights.
You will discover how to turn raw data into clear visuals that people can quickly understand and act on. In this module, you will explore how to choose the right charts, present patterns and trends, avoid confusing visuals, and use dashboards to communicate important business insights. By the end, you will be able to make data easier to read, explain your findings with confidence, and support better decision-making through simple, purposeful visuals.
You will be introduced to SQL as one of the most important tools for working with data stored in databases. In this module, you will understand what SQL is, why data analysts use it, and how it helps you retrieve, filter, organize, and analyze information from large datasets. You will also begin to see how SQL connects to real business tasks such as finding customer records, checking sales performance, tracking transactions, and generating useful reports from structured data.
This week focuses on transforming data insights into clear, engaging, and decision-driven narratives. It covers how to identify important findings, choose the right visuals, explain trends, highlight key patterns, and present recommendations in a way that makes data easy to understand and act on.
You will learn how to package their data analysis projects into a simple portfolio that shows their skills, tools, and problem-solving ability. This section also introduces different career paths in data analysis, including business analyst, data analyst, reporting analyst, BI analyst, and entry-level analytics roles, helping students understand how to position themselves for opportunities.
You will revisit the key concepts, tools, and practical skills covered in the Data Analytics course to strengthen your understanding before the final stage. This section helps you review important areas such as spreadsheet functions, data cleaning, visualization, reporting, pivot tables, and analytical thinking. It also gives you the opportunity to clarify confusing topics, correct mistakes, and prepare confidently for your final project or assessment.
You will review your data analysis work with your peers, receive constructive feedback, and make final improvements before your capstone project. This section helps you check the quality of your analysis, charts, reports, formulas, and presentation of insights. You will also prepare to bring together everything you have learned in the course and apply it to a complete data project that shows your ability to clean, analyze, visualize, and explain data clearly.
Week 11 – Capstone Project Submission & Final Exam
The final week brings together everything covered in the Data Analysis course through a practical capstone project and final assessment. It focuses on applying key skills such as data cleaning, spreadsheet analysis, visualization, interpretation, and insight presentation, while assessing overall readiness to use data analysis in real-world scenarios.
You will complete the final requirements for the Data Analysis course, including project submission, assessment review, attendance confirmation, and certificate processing. This stage marks the end of your learning journey and prepares you to showcase your new data skills confidently.