A temporary dispensation has been applied to the ST0118 V1.1 end point assessment plan for this apprenticeship. The dispensation will remain live until redundant apprentices identified in the dispensation request have completed their EPA, including any resits and retakes, when it will then be withdrawn. The end-point assessment organisation (EPAO) delivering the EPA for the apprenticeship will implement the dispensation as required and agreed by IfATE, supported and monitored by the relevant EQA provider (EQAP).
The key changes are:
The Training Provider will step in as the employer for the duration of the EPA period in order to ensure that apprentices that have been made redundant can conduct their work based project and complete their apprenticeship.
The dispensation applies to the agreed apprentices only. EPAOs must contact IfATE for each individual case. If your organisation is planning delivery of this EPA, you should follow the requirements as detailed in the plan as the dispensation is intended to support specific apprentices only.
Please contact the Institute for Apprenticeships and Technical Education via enquiries.ifa@education.gov.uk should you require any further clarity.
Collect, organise and study data to provide business insight.
This occupation 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 occupation 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.
Junior analyst
Marketing data analyst
Problem analyst
| Duty | KSBs |
|---|---|
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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 |
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Duty 2 Liaise with the client and colleagues from other areas of the organisation to establish reporting needs and deliver insightful and accurate information |
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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 |
K1 K2 K3 K4 K5 K6 K8 K10 K11 K12 K13 K15 |
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Duty 4 Produce performance dashboards and reports in the Visualisation and Model Building Phase |
K1 K2 K3 K4 K5 K6 K7 K8 K9 K10 K11 K12 K13 K15 |
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Duty 5 Support the organisation by maintaining and developing reports for analysis to aid with decisions, and adhering to organisational policy/legislation |
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Duty 6 Produce a range of standard and non standard statistical and data analysis reports in the Model Building phase |
K2 K3 K4 K5 K6 K7 K8 K9 K10 K11 K12 K13 K14 |
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Duty 7 Identify, analyse, and interpret trends or patterns in data sets |
K1 K2 K3 K4 K5 K8 K10 K11 K12 K13 K14 K15 |
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Duty 8 Draw conclusions and recommend an appropriate response, offer guidance or interpretation to aid understanding of the data |
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Duty 9 Summarise and present the results of data analysis to a range of stakeholders, making recommendations |
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Duty 10 Provide regular reports and analysis to different management or leadership teams, ensuring data is used and represented ethically in line with relevant legislation (e.g. GDPR which incorporates Privacy by Design). |
K1 K2 K3 K4 K5 K6 K7 K9 K10 K11 K12 K15 |
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Duty 11 Ensure data is appropriately stored and archived, in line with relevant legislation e.g. GDPR |
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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 |
K1: current relevant legislation and its application to the safe use of data
Back to Duty
K2: organisational data and information security standards, policies and procedures relevant to data management activities
Back to Duty
K3: principles of the data life cycle and the steps involved in carrying out routine data analysis tasks
Back to Duty
K4: principles of data, including open and public data, administrative data, and research data
Back to Duty
K5: the differences between structured and unstructured data
Back to Duty
K6: the fundamentals of data structures, database system design, implementation and maintenance
Back to Duty
K7: principles of user experience and domain context for data analytics
Back to Duty
K8: quality risks inherent in data and how to mitigate or resolve these
Back to Duty
K9: principal approaches to defining customer requirements for data analysis
Back to Duty
K10: approaches to combining data from different sources
Back to Duty
K11: approaches to organisational tools and methods for data analysis
Back to Duty
K12: organisational data architecture
Back to Duty
K13: principles of statistics for analysing datasets
Back to Duty
K14: the principles of descriptive, predictive and prescriptive analytics
Back to Duty
K15: the ethical aspects associated with the use and collation of data
Back to Duty
S1: Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
Back to Duty
S2: implement the stages of the data analysis lifecycle
Back to Duty
S3: apply principles of data classification within data analysis activity
Back to Duty
S4: analyse data sets taking account of different data structures and database designs
Back to Duty
S5: assess the impact on user experience and domain context on data analysis activity
Back to Duty
S6: identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
Back to Duty
S7: undertake customer requirements analysis and implement findings in data analytics planning and outputs
Back to Duty
S8: identify data sources and the risks and challenges to combination within data analysis activity
Back to Duty
S9: apply organizational architecture requirements to data analysis activities
Back to Duty
S10: apply statistical methodologies to data analysis tasks
Back to Duty
S11: apply predictive analytics in the collation and use of data
Back to Duty
S12: collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
Back to Duty
S13: use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
Back to Duty
S14: collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
Back to Duty
S15: select and apply the most appropriate data tools to achieve the optimum outcome
Back to Duty
B1: maintain a productive, professional and secure working environment
Back to Duty
B2: show initiative, being resourceful when faced with a problem and taking responsibility for solving problems within their own remit
Back to Duty
B3: work independently and collaboratively
Back to Duty
B4: logical and analytical
Back to Duty
B5: identify issues quickly, investigating and solving complex problems and applying appropriate solutions. Ensures the true root cause of any problem is found and a solution is identified which prevents recurrence.
Back to Duty
B6: resilient - viewing obstacles as challenges and learning from failure.
Back to Duty
B7: adaptable to changing contexts within the scope of a project, direction of the organisation or Data Analyst role.
Back to Duty
Apprentices without level 2 English and maths will need to achieve this level prior to taking the End-Point Assessment. For those with an education, health and care plan or a legacy statement, the apprenticeship’s English and maths minimum requirement is Entry Level 3. A British Sign Language (BSL) qualification is an alternative to the English qualification for those whose primary language is BSL.
4
24
this apprenticeship will be reviewed in accordance with our change request policy.
| Version | Change detail | Earliest start date | Latest start date |
|---|---|---|---|
| 1.1 | Standard, funding band and end-point assessment plan revised. | 01/06/2021 | Not set |
| 1.0 | Retired | 23/03/2016 | 31/05/2021 |
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