Unit 5 Big Data & Visualisation (J/618/6251) Assignment Brief 2026

Unit 5 Big Data & Visualisation Assignment Brief

Introduction

Exploring and analysing big data translates information into insight. The purposeful, systematic exploitation of big data, coupled with analytics, reveals opportunities for improved decision making and better business outcomes. All this data is useful when processed but requires visualisation to bring to life. Data visualisation makes big data easier for the human brain to understand and detect patterns, trends and meaning in complicated data sets. With such rapid advancement in this area, there have been considerable challenges for data specialists to develop the skills, experience and growth required to maintain innovation in the sector. Similarly, the public and private sectors have struggled to keep up with progress, meaning that the introduction of legislation and community norms have been retrospective and, at times, reactive.  As data continues to be the fuel for the digital economy, this area remains a constant topic of conversation for organisations and governments, and the public who share an interest in its growing commercial use, manipulation and presentation.

This unit introduces students to the concepts of big data and visualisation and how this is used for decision making. Students will explore the industry software solutions available for investigating and presenting data, before assessing the role and responsibility of data specialists in the current environment. Students will examine topics including data-driven decision making, manipulating data and automation, and building ethics into a data-driven culture. Students will demonstrate their use of tools and software to manipulate and prepare a visual presentation for a given data set. They will also assess how data specialists are responsible for adhering to legislation and ensuring data compliance.

On successful completion of this unit, students will be able to investigate the value of data for decision making to both end-users and organisations; compare how different industry leading tools and software solutions are used to analyse and visualise data; carry out queries to summarise and group a given data set, and analyse the challenges faced when building ethics into a data-driven culture. Students will have the opportunity to progress to a range of roles in the digital sector and will develop industry-led skills, analysis, and interpretation, which are crucial for developing practical experiences with big data and for gaining employment.

Learning Outcomes

By the end of this unit, students will be able to:

LO1 Examine big data and visualisation for decision making

LO2 Investigate statistical and graphical techniques, tools and industry software solutions for big data and visualisation

LO3 Demonstrate the use of industry software to manipulate data and prepare  visual presentations for a given data set

LO4 Assess the role, responsibilities and challenges for data specialists.

Scenario

BIA Data Solutions*
Company Profile:

BIA Data Solutions is a London-based company that has been providing bespoke data analysis and reporting services to clients from various sectors since 2015. With its expert team and advanced data processing technologies, BIA helps clients optimize their business strategies by turning raw data into actionable insights.

Our Services:

• Data Processing: BIA processes raw datasets provided by clients and transforms them into meaningful information.
• Data Visualization: Raw data is transformed into clear and interactive visuals, including complex graphs, dashboards, and detailed reports.
• Customized Reporting: Tailored reports are prepared based on the specific needs of different industries, enabling clients to leverage their data more effectively.
• Consultancy Services: In addition to data analysis, BIA offers guidance on building business strategies and identifying target markets.
• *BIA Data Solutions is not a real company.

Data Visualisation Requirements

You are required to use Python to create six data visualisations based on the dataset you have selected. Your visualisations should help present important patterns, trends, and relationships in the data in a clear and meaningful way.

Your six visualisations must include the following:

Two simple visualisations showing one piece of information only.
Two comparison visualisations showing differences between two or more groups. One heatmap to show relationships, patterns, or correlation in the data. One advanced visualisation created using the Seaborn library.

You must also:

• Explain each visualisation clearly.
• Analyse what the graph shows.
• Describe what the data is suggesting.
• Comment on any important pattern, trend, difference, or relationship shown in the graph.

In other words, you must not only present the charts, but also show that you understand what they mean.

Task: Writing a Research Paper

Chapters will consist of the following sections.

Introduction

• Define and explain the concept of big data.
• Explore the fundamentals of big data.
  Investigate the value of data for decision-making processes for both end users and organizations.
• Analyse the advantages and challenges of data-driven decision-making within an organization.
• Evaluate the potential impact of using data for decision-making on both users and organizations.

Techniques

• Outline statistical and graphical techniques commonly applied for big data and visualization in the industry.
• Review industry-leading tools and software solutions available for analysing and visualizing data.
• Compare the usage of different industry-leading tools and software solutions for data analysis and visualization, providing examples.

Methodology

• Provide a detailed explanation of the dataset you have selected for analysis.
• Describe the tools and techniques utilized to work with the dataset.
• Present and interpret the findings derived from the dataset.
• Evaluate your data preparation and manipulation process, justifying your choice of statistical techniques and explaining how these meet the needs of stakeholders for the given dataset.

Discussion

• Discuss the various roles, responsibilities, and challenges faced by data specialists.
• Review strategies employed by data specialists to ensure compliance with data regulations and standards.

Conclusion

Examine the roles, responsibilities, and challenges that data specialists encounter when integrating ethical principles into a data-driven culture.

Learning Outcomes and Assessment Criteria

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