BMP4005 Assignment Help: Information Systems and Big Data Analysis Guide

Last updated: November 2026 · Reviewed by the HND Assignment Help tutoring team

Information systems and data analysis modules ask business students to combine theory with practical work on numbers, which many find challenging in their first year. This guide explains how to approach a BMP4005-style assessment: describing and evaluating systems, using big data concepts, analysing data step by step and writing recommendations a manager could act on. Learning outcomes, credits, datasets and formats are set by your institution, so check every detail against your module handbook and brief.

BMP4005 at a glance

Item	What to know
Module	BMP4005 Information Systems and Big Data Analysis (first-year, business programmes)
Learning outcomes and credits	Vary by institution: check your module handbook and brief.
Common assessment types	Business report on a case organisation, data analysis task with dashboard or charts, sometimes a presentation.
Key concepts	Types of information system (TPS, MIS, DSS, ERP, CRM), the 5 Vs of big data, data-driven decision making, CRISP-DM.
Typical tools	Excel (pivot tables, charts), Power BI or Tableau, depending on the module.
Legal and ethical context	UK GDPR and the Data Protection Act 2018, data security and bias.
Where the marks are	Correct analysis, clear visuals, critical evaluation of systems and evidence-based recommendations.

Section-by-section approach

1. Introduce the organisation and the business question

Briefly set out the case organisation (from your brief or one you have chosen) and the business question the data should help answer, such as "Which products and regions drive falling profit?" A focused question keeps the analysis purposeful.

2. Explain and evaluate information systems

Identify which systems the organisation uses or should use and evaluate them, rather than just defining them.

System	What it does	Evaluation angle
Transaction processing system (TPS)	Records day-to-day transactions	Accuracy and speed of data capture
Management information system (MIS)	Summarises data into routine reports	Timeliness and relevance of reports
Decision support system (DSS)	Supports analysis of semi-structured decisions	Quality of insight, user skills
Enterprise resource planning (ERP)	Integrates finance, operations, HR data	Cost, implementation risk, integration benefits
Customer relationship management (CRM)	Manages customer data and interactions	Personalisation versus privacy

3. Apply big data concepts

Use the 5 Vs (volume, velocity, variety, veracity, value) to explain what kind of data the organisation holds and what challenges it creates. Link each V to the case: for example, high-velocity online orders, or low veracity because of duplicate customer records.

4. Analyse the data with a clear method

Follow a recognised process such as CRISP-DM (business understanding, data understanding, data preparation, modelling or analysis, evaluation, deployment) and describe each step you took, including how you cleaned the data.

Worked method example (not an answer, invented dataset): a retailer’s monthly online sales rise from £40,000 in March to £46,000 in April.

Step	What to do	Example working
Clean	Remove duplicates and blanks, fix formats	12 duplicate orders removed from 1,200 rows
Summarise	Pivot table by month, product and region	Totals by region for March and April
Calculate a KPI	Month-on-month growth = (new − old) / old	(46,000 − 40,000) / 40,000 = 15% growth
Visualise	Choose a chart that suits the message	Line chart for trend, bar chart for regions
Interpret	Explain what the numbers mean for the business	Which region drove growth and whether it is sustainable

5. Discuss ethics, security and limitations

Explain how the organisation must handle personal data under UK GDPR and the Data Protection Act 2018 (for example lawful basis, data minimisation and security), and note limits of your analysis such as sample period, missing fields or possible bias.

6. Recommendations

Give two to four recommendations that follow from your analysis, for example investing in a dashboard for regional managers or improving data quality at the point of entry. Link each one to a finding and suggest how success would be measured.

How assessors judge BMP4005

What the marker looks for	Weak work	Strong work
Understanding of IS concepts	Definitions only	Systems applied to and evaluated for the case organisation
Big data concepts	5 Vs listed	Each V linked to the organisation’s data and challenges
Data preparation	Not mentioned	Cleaning steps described and justified
Analysis and visuals	Unlabelled charts, calculation errors	Accurate KPIs, labelled charts suited to the message
Ethics and law	Brief mention of GDPR	Specific UK GDPR principles applied to the case
Recommendations	Generic advice	Actions linked to findings with success measures

Pre-submission checklist

• The business question is stated at the start and answered at the end.
• Information systems are evaluated for the case, not just defined.
• The 5 Vs are applied to the organisation’s data.
• Data cleaning steps are described, with numbers of records affected.
• Every KPI calculation is shown and checked.
• Every chart has a title, labelled axes and a sentence of interpretation.
• UK GDPR and data ethics are applied to the case.
• Recommendations each link to a specific finding.
• Any data files or dashboards required by the brief are attached in the right format.

BMP4005 answer hints and sample structure

There is no answer to copy, because your analysis must use your own dataset and case. This is a typical structure for a 2,500-word business report in an information systems and data module. Follow your brief if it sets a different format.

Section	What goes in it	Suggested share
Introduction	Organisation, business question, report structure	10%
Information systems evaluation	Current and proposed systems, strengths and weaknesses	20%
Big data concepts	5 Vs applied to the case, opportunities and challenges	15%
Data analysis	Method, cleaning, KPIs, charts and interpretation	30%
Ethics, security and limitations	UK GDPR, data quality, bias	10%
Recommendations and conclusion	Evidence-based actions and summary	15%

Frequently asked questions

What is BMP4005 Information Systems and Big Data Analysis?

It is a first-year business module code used on some UK programmes, covering information systems, big data concepts and practical data analysis. Check your module handbook for its exact learning outcomes.

What are the 5 Vs of big data?

Volume, velocity, variety, veracity and value. In an assessment, link each one to the data your case organisation holds.

Do I need to use Power BI for BMP4005?

Only if your brief asks for it. Many first-year tasks can be done in Excel with pivot tables and charts. Use the tool your module teaches.

How do I evaluate an information system?

Look at what it does for the organisation, its benefits, costs, risks and how well users can use it, and support your points with sources and case evidence.

How much should I write about GDPR?

Enough to apply the main UK GDPR principles to your case, such as lawful basis, data minimisation and security. A short, specific section is better than a long general one.

What is CRISP-DM?

It is a widely used six-stage process for data projects: business understanding, data understanding, data preparation, modelling, evaluation and deployment. It gives your method section a clear structure.

Can a tutor help me with BMP4005?

Yes. A tutor can teach the tools, explain concepts and review your draft. The analysis and writing must be your own work.

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