Big Data and Analytics - SSS 2 plan

LESSON PLAN

BIG DATA & ANALYTICS

Lesson Details	Information
Subject	Digital Technologies
Class	SSS 2
Term	Second Term
Week	8
Topic	Big Data & Analytics
Duration	80 Minutes (Double Period)
Date	________________________

1. Behavioural Objectives

By the end of the lesson, students should be able to:

1. Explain the meaning of Big Data.
2. Identify and explain the Five Vs of Big Data.
3. List common sources of Big Data.
4. Describe applications of Big Data in different sectors.
5. Identify introductory tools used for data analysis.
6. Perform simple analysis on a small dataset.

2. Previous Knowledge

Students have learnt about data collection, data storage and organization, and data cleaning and preparation in the previous lesson on Data Science Basics.

3. Instructional Materials

• Computer or laptop, where available.
• Whiteboard and markers.
• Sample data table or printed dataset.
• Spreadsheet application such as Microsoft Excel or Google Sheets, where available.
• Charts, diagrams or projector, where available.

4. Teaching Methods

Discussion, explanation, demonstration, questioning, guided practice and collaborative learning.

5. Presentation of the Lesson

Time	Teacher's Activities	Students' Activities
10 mins	Introduction: The teacher reviews the previous lesson on data science and asks students to mention places where large amounts of data are generated, such as banks, hospitals, social media platforms and online shops.	Students recall previous knowledge and give examples of data generated by digital activities.
15 mins	Meaning and Characteristics of Big Data: The teacher defines Big Data and explains the Five Vs: Volume, Velocity, Variety, Veracity and Value, using familiar examples.	Students explain Big Data in their own words and identify the Five Vs from the examples provided.
10 mins	Sources of Big Data: The teacher explains sources such as social media, business transactions, mobile applications, sensors, websites, healthcare systems and government records.	Students list sources of Big Data and match each source with an example.
10 mins	Applications of Big Data: The teacher discusses how Big Data supports healthcare, education, banking, transportation, agriculture, retail and environmental monitoring.	Students describe how data analysis can help solve problems in at least two sectors.
15 mins	Introduction to Data-Analysis Tools: The teacher introduces spreadsheets, databases, charts, dashboards and programming tools. The teacher demonstrates simple sorting, counting or summarizing using a sample dataset.	Students identify the tools and observe or practise organizing and summarizing sample data.
10 mins	Practical Activity: The teacher presents sample school-shop sales data and guides students to calculate the total number of items sold, identify the most popular product and suggest a suitable chart.	Students calculate the total, compare product quantities and explain what the results show.
5 mins	Evaluation: The teacher asks questions about the meaning, characteristics, sources, applications and tools of Big Data.	Students answer the questions orally.
5 mins	Conclusion and Assignment: The teacher summarizes the lesson, emphasizes data accuracy and privacy, and gives the assignment.	Students note the main points and copy the assignment.
Total Time: 80 Minutes

6. Evaluation

1. Define Big Data.
2. List and explain the Five Vs of Big Data.
3. Mention four sources of Big Data.
4. State three applications of Big Data.
5. Mention four tools or methods used for data analysis.
6. Why should data be checked for accuracy before analysis?

7. Assignment

1. Explain the meaning and characteristics of Big Data.
2. List six sources of Big Data and give an example of each.
3. Describe four applications of Big Data in everyday life or in Nigeria.
4. Explain the uses of spreadsheets, databases and charts in data analysis.
5. A shop sells 25 exercise books, 40 pens, 30 pencils and 15 rulers in one day. Calculate the total number of items sold and identify the most and least popular products by quantity.

8. Reference

CMPNOTE: SSS 2 Digital Technologies – Second Term, Week 8: Big Data & Analytics.