Level 5 Higher Diploma in Data Analytics 

This position is found in any employer in any sector that uses data to make business decisions. Data analysts may work in various departments within a single employer, (for example finance, sales, HR, manufacturing, or marketing), and in any employment sector, public or private, including retail, distribution, defence, banking, logistics, media, local government, etc.

The broad purpose of the role is to ascertain how data can be used in order to answer questions and solve problems. Data analysis is a process of requirement-gathering, inspecting, cleansing, transforming and modelling data with the goal of discovering useful information, informing conclusions and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names. In today’s world, data analysis plays a crucial role in making decisions more evidence-based and helping organisations operate more effectively.

For example: a data analyst may investigate social media trends and their impact on the organisation. In retail, a data analyst may break down sales figures to make recommendations on product placement and development. In HR, a data analyst may investigate staff retention rates, in order to decide on recruitment strategy. In a hospital, a data analyst may investigate wait times for different departments, in order to provide a better service to its patients.

In their daily work, an employee in this occupation interacts with internal or external clients. Internally, the data analyst may work with many people within their organisation, at different levels. Externally a data analyst may provide data analysis services to other organisations on behalf of their employer. Data analysts would normally be office based and work normal business hours.

An employee in this occupation will be responsible for the creation and delivery of their own work, to meet business objectives. The data analyst will be responsible for working within the data architecture of the company and ensuring that the data is handled in a compliant, safe and appropriately secure manner, understanding and adhering to company data policy and legislation. Data analysis is a fast-moving and changing environment, and data analysts need to continue to stay abreast of, and engaged with, changes and trends in the wider industry; including data languages, tools and software, and lessons learnt elsewhere.

Job Description/Occupation duties

Duty 1: Identify data sources to meet the organisation’s requirement, using evidence-based decision making to establish a rationale for inclusion and exclusion of various data sets and models.

Duty 2: Liaise with the client and colleagues from other areas of the organisation to establish reporting needs and deliver insightful and accurate information.

Duty 3: Collect, compile and, if needed, cleanse data, such as sales figures, Digital Twins etc. solving any problems that arise, to or from a range of internal and external systems.

Duty 4: Produce performance dashboards and reports in the Visualisation and Model Building Phase.

Duty 5: Support the organisation by maintaining and developing reports for analysis to aid with decisions, and adhering to organisational policy/legislation.

Duty 6: Produce a range of standard and non-standard statistical and data analysis reports in the Model Building phase.

Duty 7: Identify, analyse, and interpret trends or patterns in data sets.

Duty 8: Draw conclusions and recommend an appropriate response, offer guidance or interpretation to aid understanding of the data.

Duty 9: Summarise and present the results of data analysis to a range of stakeholders, making recommendations

Duty 10: Provide regular reports and analysis to management or leadership teams, ensuring data is used and represented ethically in line with relevant legislation (e.g. GDPR which incorporates Privacy by Design).

Duty 11: Ensure data is appropriately stored and archived, in line with relevant legislation e.g. GDPR, with technological developments to enhance relevant skills and take responsibility for own professional development.

Duty 12: Practice continuous self-learning to keep up to date with technological developments to enhance relevant skills and take responsibility for own professional development.

EXTERNAL END-POINT ASSESSMENT (EPA)

The HDDA has a total of 120 credits and comprises of 6 modules, each of the modules carrying 20 credits as follows:

• The students will be provided with pre-recorded video lectures for all the modules for learners to access at their convenience.
• Pre-recorded video lectures for modules may be release entirely at the start of the programme or to the students at monthly intervals (one module per month so that the entire set of lectures will be released by the fifth month).
• There will be live interactive on-line sessions with the tutors scheduled where learners are able interact with tutors and to ask questions and receive more help on the module. There will be a maximum of 4 hours of tutor interaction in a month.
• As well as the pre-recorded video lectures, there will be detailed and in depth course material for all the modules.

Assessment Method

• Assessment will be through structured assignments for each module.
• The assignments shall be completed and submitted by the learner.
• Learners must go through the pre-recorded video lectures for each module assigned for that month in that month to be able to undertake assignments. Assignments for a particular module should be completed and submitted before the end of the learning period of the forthcoming module.
• The assignments will be evaluated and the marks scored in the assignments will decide the students’ grading.

The assessment is purely based on the assignments given by LEB for each of the modules which are to be answered and submitted by the students on the due dates. The assignments are designed in such a way that it reflects the students’ understanding of the concepts and their skills in applying the knowledge gained through the course to solve real world Data Analytics problems. The assignments will be a mix of questions requiring descriptive answers and problems requiring solutions.

The type of assignments in each of the modules and the marks assigned are as below:

There are objective type self-assessment questions with answers included in the course material. These are for self-practice by learners to gauge their understanding.  The objective type self-assessment questions do not form part of the formal assessment.