Business Information Systems Final Assessment

This is guidance for your final assessment.

This document sits alongside the final assessment brief, the supporting VLE Big Data Analytics publications and can be used in combination with “Walkthrough of Final BIS assessment” video in Videos: Lecture Recordings tile on the VLE.

Topic: Big Data Analytics

  • Four tasks with marks allocated
  • Three written tasks
  • Fourth task is a mark out of ten for quality of references, citations and writing.
  • Deadline:  Wednesday,
  • 3000 word (+/- 10%)
  • Minimum:  2700 words
  • Maximum:  3300 words
  • Please do not go beyond the maximum or under the minimum.  Exceeding the maximum word count will result in marks being deducted.  No-one wants this.

Please be attentive to the health warning in the assignment brief:

Your briefing report does not need an executive summary, recommendations or appendices. Use the sector and business/organisation chosen for the interim assessment. If you do not, marks will be forfeited.

It is important to understand that the first three written tasks apply at different levels as follows:

  • Task 1: refers to Big Data Analytics at the global level – that is, the world.
  • Task 2: refers to Big Data Analytics at your sector/industry level
  • Task 3: refers to Big Data Analytics at your individual business level (first assessed during the interim)
  • Follow this level approach and your work will be much clearer and will read well.
  • Task 4: is completed automatically as you write the above tasks.  The main KPI here is the quality and believability of your in-text citations and references based on the research you have done.  Please try to write in an academic ‘tone’.  Assume a detached, professional style, free of colloquialisms (slang).

Big Data Analytics

  • Issues to consider:
    • Five Components of Information Systems: with your research, please show you have considered the connected resource categories always needed to be used effectively by business managers.  Resources require competencies to use them effectively and always require investment of time, money and effort to meet the business KPIs over time.  Resources here are:
      • Hardware selection and implementation.  Hardware resources refer to all types of machines, not just computer hardware.  
      • Software selection and implementation.  Software resources refer not only to computer programs and the media on which they are stored, but also describe the procedures used by people.
      • Data and information created, managed, secured and analysed by the business.  Data resources describe all of the data that an organisation has access to, regardless of its form.
      • Networks & telecommunications selected and implemented.  Resources are also required to enable different systems to transfer data.
      • HR resources required to support delivery of the business and information systems strategies.  People can be managers making decisions based on data and information, customers, suppliers, specialist technical support whether employed or outsourced.
    • Five Vs of Big Data: this model suggests five dimensions in which you can consider and evaluate the opportunities and risks of big data, in any of the three required tasks:
      • Volume: huge amounts of data generated every second by IT systems
      • Variety: many data types are generated (e.g. text, sound, video, numeric etc.)
      • Velocity: speed of global transmission
      • Veracity: how reliable, accurate, certain or truthful is the data?
      • Value: the commercial, social, economic, environmental, ethical, medical, scientific, cultural etc. benefits of the data produced, stored, processed and analysed
    • Value Chain & Virtual Value Chain:  choose one or both of these models to structure proposals for value creation and delivery in your business.  These were covered in Weeks 2, 5 and 6.  I also covered the concept of business value in Week 6.  A selective approach can be taken (section below refers).  Please remember you are only considering the models developed by Porter (Value Chain) and Rayport & Sviokla (Virtual Value Chain).

Big Data Analytics research & application of theory

  • Big Data Analytics should not be considered as just one label.  You need to analyse and evaluate with further reading and research.
  • Research can be considered as a process of exploration and discovery.  You will not know what you will find until you try. 
  • You know by now that we manage a general category (e.g. IoT, app, BIS, value, etc.) by detailed examination of the elements or structure of the category.  A process we call analysis
  • Having analysed, via necessary research, we then judge the quality or value of the thing(s) analysed.  A process we call evaluation.
  • Please practise this for best results!
  • Use and application of relevant, available theoretical frameworks (or tools) is an important component of good quality outcomes.  We use tools to generate positive results which may, for examples, clarify our thinking on an issue and to maintain focus and relevance in our writing up of research results.
  • Due to the word count limit, we do not have to write robotically and use every element in a model like the value chain or five forces.  It could be better to design a tailored figure (screenshot) of the applied area and to evaluate 1-3 chosen elements in our own words underneath.  A standard and useful information processing technique is selection.  This can be used with our useful business tools to help demonstrate our critical thinking. 
  • I have already provided you with some initial Big Data Analytics research resources to get you started.  These are in a folder on the VLE under Assessments and Assessment Guidance.
  • However, these resources should be considered a start and not an end.  They are not in any way the “correct” answer.  Your objective is to analyse and evaluate the topic of Big Data Analytics in the light of the world, your sector/industry and your interim group business/organisation in particular.

Benefits and risks

  • Big Data Analytics should be considered in the balance of benefits and risks to individuals, society, economy, the environment and business.
  • Value creation and delivery in line with the business strategy remains an important factor.
  • Benefits and risks can be analysed and evaluated in the light of the models given in the assessment brief – the privacy paradox, current national and international privacy law, regulations and organisational privacy policies and the value chain and the virtual value chain.

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