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Nigeria's free digital learning hub. Videos, lecture notes, practice questions and leaderboards aligned with CCMAS, NBTE, NCCE, WAEC, NECO, IJMB and JAMB curricula.
Cyber Security · 300 Level
This is the complete lecture note for CYB 304 INFORMATION AND BIG DATA SECURITY, prepared for Cyber Security students at 300 Level. You can read it online below, open it in the full viewer, or download the PDF for offline study. It pairs with the course's video lectures, so you can read and watch together.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Course Title: Information and Big Data Security Course Code: CYB 304 Course Units: Unit 2 • Series 1: Foundations of Big Data and Information Security • Series 2: Big Data Characteristics, Technologies, and Handling Techniques • Series 3: Information and Big Data Security Policies, Risk Management, and Lifecycle Security • Series 4: Big Data Platforms, Skills, Adoption, and Governance • Series 5: Organisational Change, Analytical Tools, and Cloud-Based Big Data Solutions Suggested Out line for Series 1: Foundations of Big Data and Information Security Part 1.1: Introduction to Big Data • Definition of big data • Evolution from small data to big data • Importance and relevance of big data Part 1.2: Big Data Characteristics and Features • The 3Vs and 6Vs of big data • Unique features of big data • Sources and formats of data Part 1.3: Applications and Opportunities in Big Data • Everyday applications and industry use cases • Business intelligence vs. big data vs. data mining • Big data as an opportunity for innovation Part 1.4: Foundations of Information Security in the Context of Big Data • Definition of information security • Relationship between information security and big data • Initial challenges and requirements for securing big data
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Introduction Data has become one of the most valuable resources in today’s world. From social media interactions and online purchases to healthcare records and government databases, vast amounts of information are generated every second. This growth has given rise to the concept of big data, which is not only transforming how organisations operate but also creating new challenges for securing information. Understanding the foundations of big data and its relationship with information security is therefore essential for anyone preparing to work in technology, business, or security fields. The aim of this Series is to introduce you to the fundamental concepts of big data and information security. By the end, you will be able to define big data, explain its characteristics, recognise its applications, and describe the basic principles of securing information in the context of big data. We shall commence this Series by exploring what big data is, how it has evolved, and why it matters. Next, we will examine the characteristics and unique features of big data, including the 3Vs and 6Vs, as well as its sources and formats. Following that, we will consider applications and opportunities, looking at how big data is used in everyday life and industry, and how it compares with business intelligence and data mining. Finally, we will round off by introducing the foundations of information security, highlighting its relationship with big data and the initial challenges of securing large-scale information systems. Series Learning Outcomes Upon completing this Series, you should be able to: • SLO 1.1 define big data and explain its evolution from small data to large-scale information systems, • SLO 1.2 describe the importance of big data and its relevance in contemporary contexts, • SLO 1.3 explain the main characteristics of big data, including the 3Vs and 6Vs, • SLO 1.4 identify sources and formats of big data in practical scenarios, • SLO 1.5 analyse everyday applications and industry opportunities of big data, • SLO 1.6 differentiate between business intelligence, big data, and data mining, and • SLO 1.7 outline the foundations of information security and its relationship with big data. 1.1 Introduction To Big Data 1.1.1 Definition of big data Big data refers to extremely large and complex sets of data that cannot be managed, processed, or analysed using traditional data management tools. It is characterised by its scale, diversity, and speed of generation. Big data is not just about size, but also about the ability to derive meaningful insights from vast and varied information sources. Fill in the blank: Extremely large and complex sets of data that cannot be managed with traditional tools are called ______.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Short description: Diagram showing the concept of big data compared to traditional data. Caption: Figure 1.1 Definition of big data 1.1.2 Evolution from small data to big data Data has evolved from small data, which refers to manageable datasets often stored in spreadsheets or simple databases, to big data, which involves massive, unstructured, and continuously growing datasets. This evolution has been driven by technological advancements, increased digital activity, and the rise of interconnected devices. Fill in the blank: Manageable datasets stored in spreadsheets or simple databases are referred to as ______ data.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Short description: Image showing the transition from small data to big data. Caption: Plate 1.1 Evolution from small data to big data 1.1.3 Importance and relevance of big data The importance of big data lies in its ability to generate insights that drive decision-making, innovation, and efficiency. Organisations use big data to predict customer behaviour, improve healthcare outcomes, enhance security, and optimise business operations. Its relevance extends across industries, making it a cornerstone of modern information systems. Fill in the blank: Organisations use big data to predict customer behaviour, improve healthcare outcomes, and enhance ______.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Caption: Box 1.1 Importance and relevance of big data Short description: Box summarising uses of big data in business, healthcare, and security. Pilot questions 1.1 1. What is big data? 2. What is small data? 3. How has data evolved from small data to big data? 4. Mention one reason why big data is important. 5. Give one example of how organisations use big data. 1.2 Big Data Characteristics And Features 1.2.1 The 3Vs of big data The most common way to describe big data is through the 3Vs: volume, velocity, and variety. Volume refers to the sheer size of data generated daily, often measured in terabytes or petabytes. Velocity highlights the speed at which data is produced and processed, such as real-time streams from social media or sensors. Variety points to the different formats of data, including text, images, audio, and video. Fill in the blank: The speed at which data is produced and processed is referred to as ______.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Short description: Diagram illustrating the 3Vs of big data (volume, velocity, variety). Caption: Figure 1.2 The 3Vs of big data 1.2.2 The extended 6Vs of big data Beyond the 3Vs, big data is often explained using the 6Vs: volume, velocity, variety, veracity, value, and variability. Veracity refers to the accuracy and trustworthiness of data. Value highlights the importance of extracting meaningful insights from data. Variability points to the changing meaning or interpretation of data depending on context. Together, these six dimensions provide a more comprehensive understanding of big data. Fill in the blank: The accuracy and trustworthiness of data is referred to as ______.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Caption: Table 1.1 The 6Vs of big data Short description: Table summarising the six dimensions of big data with brief definitions. 1.2.3 Unique features of big data Big data is unique because of its scale, complexity, and continuous growth. Unlike traditional datasets, big data often includes unstructured information such as social media posts, sensor readings, or multimedia files. Its dynamic nature requires advanced tools and technologies to manage, store, and analyse effectively. Fill in the blank: Social media posts and multimedia files are examples of ______ data.
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