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You are working for a research company in Belfast called BMC Consulting.
The Managing Director has asked you to investigate “Cyber security risks involved in local and/or cloud-based Big Data storage systems. Evolution of these risks over time and future risks.”
Background
Big data is a term that has become more and more common over the last decade. It was originally defined as data that is generated in incredibly large volumes, such as internet search queries, data from weather sensors or information posted on social media. Today big data has also come to represent large amounts of information generated from multiple sources that cannot be processed in a conventional way and that cannot be processed by humans without some form of computational intervention. Big data can be stored in several ways: Structured, whereby the data is organised into some form of relational format, unstructured, where data is held as raw, unorganised data prior to turning into a structured form, or semi-structured where the data will have some key definitions or structural form, but is still held in a format that does not conform to standard data storage models. Many systems and organisations now generate massive quantities of big data on a daily basis, with some of this data being made publicly available to other systems for analysis and processing. The generation of such large amounts of data has necessitated the development of machine learning systems that can sift through the data to rapidly identify patterns, to answer questions or to solve problems. As these new systems continue to be developed and refined, a new discipline of data science analytics has evolved to help design, build and test these new machine learning and artificial intelligence systems. Utilising Big Data requires a range of knowledge and skills across a broad spectrum of areas and consequently opens opportunities to organisations that were not previously accessible. The ability to store and process large quantities of data from multiple sources has meant that organisations and businesses are able to get a larger overall picture of the pattern of global trends in the data to allow them to make more accurate and up to date decisions. Such data can be used to identify potential business risks earlier and to make sure that costs are minimised without compromising on innovation. However, the rapid application and use of Big Data has raised several concerns. The storage of such large amounts of data means that security concerns need to be addressed in case the data is compromised or altered in such a way to make the interpretation erroneous. In addition, the ethical issues of the storage of personal data from multiple sources have yet to be addressed, as well as any sustainability concerns in the energy requirements of large data warehouses and lakes. The theme will enable students to explore some of the topics concerned with Big Data from the standpoint of a prospective computing professional or data scientist. It will provide the opportunity for students to investigate the applications, benefits and limitations of Big Data while exploring the responsibilities and solutions to the problems it is being used to solve. LO3 Produce project plans based on research of the chosen theme for an identified organisation.
Your Research will provide the opportunity to investigate “Cyber security risks involved in local and/or cloud-based Big Data storage systems. Evolution of these risks over time and future risks.”
Task 1: Produce project plans based on research of the chosen theme for an identified organisation
- Recommend potential solutions to identified business needs, including carrying out a cost/benefit analysis, defining business objectives, scope and purpose of the project.
- Comprehensive project plans, including:-
- defining functional and non-functional requirements of the system, stakeholder requirements and expectations, carrying out impact analysis, prioritising requirements, describing the deliverables to be produced,
- timescales and time management,
- costs
- management planning, risk and challenges analysis.
- change
- Success criteria to be used, e.g. Key Performance Indicators (KPIs), performance metrics, quality metrics, and business targets.
- Use of an identified project management methodology, e.g. Waterfall, Agile, Rapid Application Development (RAD).
Establish your aims and objectives for the project. Outline objectives and timeframes based on the scenario. Produce an appropriate project management plan that includes relevant actions to meet objectives and timeframes in a Work Breakdown Structure and Gantt Chart. Your plan must cover aspects of scope, time, quality, risk, and resources.
Include
- Project Aims and objectives;
- Provide a detailed Project Plan;
- Provide Milestones Schedule for monitoring and controlling the Project.
Tools for effective project planning, resource planning and allocation, and work breakdown structure, including Project Initiation Documents (PID), Gantt charts or Critical Path Analysis (CPA), risk matrix.
Task 2: Present your project recommendations and justifications of decisions made, based on research of the identified theme and sector - Present Results from your research e.g. Facts/Statistics/Charts
Presenting to different technical and non-technical stakeholders, e.g. emphasis on operational or strategic information, technical terminology used, levels of detail given and simplifying concepts.
Consider the methods and mediums to be used, including written or verbal, report, online or presentation.
Show how project research and intended audience will influence method and medium.
Justification of decisions made:
- Justification of recommendations, including use of key points from cost/benefit analysis, deliverables, success criteria, impact analysis.
- Justifications of planning, including chosen development methodology, work and resource allocation, key deadlines and timescales.
- Rationale for decisions made in the recommended solution and project plan, including use of research and data for the identified technology and business sector, analysis of evidence and business requirements, contextual factors specific to the identified organisation.
- Reflection on the quality of research:
- Quality of secondary and primary data used to inform planning and make
- decisions.
- Awareness that some studies may result in generalised findings and how this can impact on the quality of decisions and the accuracy of conclusions made.
- Evaluate the quality of the data and information used to inform project initiation plans, e.g. sample size, sample characteristics, user experience during collection, domain context.
- Reach conclusions as to the likely accuracy and reliability of assertions made.
- Assess the extent to which the project recommendations meet the needs of the identified organisation, including fully- supported rationales for planning decisions made.
Task 3: Overall - Evaluate the project planning recommendations made in relation to the needs of the identified organisation and the accuracy and reliability of the research carried out.
Reflection involves reviewing your project actions to improve the performance/success of future projects.
NB Explain any Assumptions made and make Recommendations based on your Conclusions. These must be specific and actionable.
*Please access HN Global for additional resources support and reading for this unit. For further guidance and support on report writing please refer to the Study Skills Unit on HN Global. Link to www.highernationals.com
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