Level 4

Data Analyst

Apprenticeship

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Collect, organise and study data to provide business insight.

Key apprenticeship information

Title of embedded diploma/qualification:

Level 4 Apprenticeship Standard

Additional Functional Skills:

Level 2 English and maths - 19 yrs and over this is optional

Awarding Organisation:

Highfield Qualifications

Qualification duration:

18 months and 12 weeks End Point Assessment

Data Analyst, Marketing Data Analyst, Departmental Data Analyst, Energy Data Analyst, Junior Analyst, Problem Analyst

Who is suitable:

Non-levy employer contribution (5%) - £750 & levy paying employer contribution - £15,000

Funding value and cost:

About your course

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.

Data analysts turn raw data into actionable insights. They manage, clean, transform, and analyse data to address questions and solve problems. Their expertise spans the entire data lifecycle, from gathering and understanding requirements to collecting and preparing data, performing detailed analysis, and creating compelling reports.  

As logical thinkers, they solve problems and use their skills to drive decisions and business improvements. By creating clear reports and impactful presentations, Data Analysts empower organisations to make informed decisions and drive success. 

Our apprenticeship is designed to equip individuals with the skills and knowledge to achieve success in a fast moving, data driven world, helping businesses shape their future. 

See full specification

What will you study?

  • Knowledge

    • K1: current relevant legislation and its application to the safe use of data

    • K2: organisational data and information security standards, policies and procedures relevant to data management activities

    • K3: principles of the data life cycle and the steps involved in carrying out routine data analysis tasks

    • K4: principles of data, including open and public data, administrative data, and research data

    • K5: the differences between structured and unstructured data

    • K6: the fundamentals of data structures, database system design, implementation and maintenance

    • K7: principles of user experience and domain context for data analytics

    • K8: quality risks inherent in data and how to mitigate or resolve these

    • K9: principal approaches to defining customer requirements for data analysis

    • K10: approaches to combining data from different sources

    • K11: approaches to organisational tools and methods for data analysis

    • K12: organisational data architecture

    • K13: principles of statistics for analysing datasets

    • K14: the principles of descriptive, predictive and prescriptive analytics

    • K15: the ethical aspects associated with the use and collation of data

  • Skills

    • S1: Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design

    • S2: implement the stages of the data analysis lifecycle

    • S3: apply principles of data classification within data analysis activity

    • S4: analyse data sets taking account of different data structures and database designs

    • S5: assess the impact on user experience and domain context on data analysis activity

    • S6: identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate

    • S7: undertake customer requirements analysis and implement findings in data analytics planning and outputs

    • S8: identify data sources and the risks and challenges to combination within data analysis activity

    • S9: apply organizational architecture requirements to data analysis activities

    • S10: apply statistical methodologies to data analysis tasks

    • S11: apply predictive analytics in the collation and use of data

    • S12: collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience

    • 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

    • S14: collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs

    • S15: select and apply the most appropriate data tools to achieve the optimum outcome

  • Behaviours

    • B1: maintain a productive, professional and secure working environment

    • B2: show initiative, being resourceful when faced with a problem and taking responsibility for solving problems within their own remit

    • B3: work independently and collaboratively

    • B4: logical and analytical

    • 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.

    • B6: resilient - viewing obstacles as challenges and learning from failure.

    • B7: adaptable to changing contexts within the scope of a project, direction of the organisation or Data Analyst role.

How will your qualification be delivered

Our sector expert staff will support you to achieve the apprenticeship. We have highly skilled and knowledgeable staff with significant experience of working in the industry who will be able to share their experiences and support you. All learning is either on a 1-2-1 basis or small group webinars so you have the best experience possible with Phoenix 4 Training. You will have an e-portfolio to gather and store all your evidence to support your apprenticeship.

End Point Assessment

We give learners mock synoptic projects and interviews to ensure they are ready for the End Point Assessment and know precisely what to expect at all points in the process. The End Point Assessment itself includes:

  • Portfolio –Produced towards the end of the apprenticeship, containing evidence from real work projects 

  • Project – A business-related project over a one-week period away from the day-to-day workplace

  • Employer reference

  • A structured interview with an assessor – exploring the portfolio and the project 

What you can do next

  • Completion of this apprenticeship enables learners to apply and become Level 3 SFIA recognised