Data Analysis is the process of collecting, organizing, processing, and interpreting data to uncover useful information, identify patterns, draw conclusions, and support decision-making. In the IT world, data analysis plays a crucial role in optimizing systems, improving business processes, enhancing user experience, detecting fraud, and driving strategic initiatives.
IT professionals use data analysis tools and programming languages like Excel, SQL, Python, R, Power BI, and Tableau to clean data, perform statistical analysis, build models, and create visualizations.
Key Areas in IT Where Data Analysis is Applied:
- Business Intelligence (BI) – Transforming raw data into actionable insights.
- Cybersecurity – Analyzing logs to detect unusual patterns and threats.
- Web & App Analytics – Tracking user behavior to optimize design and functionality.
- Network Management – Monitoring and analyzing traffic and performance metrics.
- Artificial Intelligence (AI) & Machine Learning (ML) – Feeding clean and structured data into models.
- IT Operations – Predicting failures, improving uptime, and automating support.
Duration: 3 Months
Payment Method
Interested individuals can pay using the following methods:
Pay at the centre of your choice Pay to the bank using the following bank details
Account Number: 1422103977
Account Name: Neyo4africa International Ltd.
Bank: Acess Bank Payment
Full Payment (Attracts 5% discount of Course Fee)
Installmental Payments (First Payment= 60% of Course Fee)
7 lessons in this course
Introduction to Excel (Your First Tool)
Microsoft Excel is a spreadsheet tool used to: Store data Organize data Analyze data Create reports
Introduction to Excel Part 2
Microsoft Excel is a spreadsheet tool used to: Store data Organize data Analyze data Create reports
Introduction to Excel Part 3
Microsoft Excel is a spreadsheet tool used to: Store data Organize data Analyze data Create reports
Excel Introduction Assessment
Data Cleaning in Excel
Why Data Cleaning Matters Real-world data is always messy. If you analyze dirty data: ❌ Your results will be wrong ❌ Your decisions will be wrong Common Data Problems 1. Missing Values Name Sales John 5000 Mary 👉 Problem: Empty cell 2. Duplicates Name Sales John 5000 John 5000 3. Inconsistent Data Product Rice rice RICE
Data Cleaning in Excel Part 2
Common Data Problems 1. Missing Values Name Sales John 5000 Mary 👉 Problem: Empty cell 2. Duplicates Name Sales John 5000 John 5000 3. Inconsistent Data Product Rice rice RICE
Data Cleaning in Excel Part 3
Course Price
Secure payment via Paystack
What's Included
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Video lessons
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Downloadable resources
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Certificate of completion
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Lifetime access
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Mobile and TV access