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info_outline From 29th October all our classroom courses will be delivered via Live Online until further notice. Our centres are open for Computer Based Exams (CBE) only, which are running with safety measures in place.

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DIGITAL

Data Analyst Apprenticeship Level 4

The Data Analyst apprenticeship equips individuals with the ability to ascertain how data can be used in order to answer questions and solve problems. Apprentices will learn the process for requirement-gathering, inspecting, cleansing, transforming and modelling data with the goal of discovering useful information, informing conclusions and supporting decision-making.

This apprenticeship provides the skills and knowledge to apply different facets and approaches of data analysis. A Data Analyst apprentice 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.

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.

Typical job titles include: Data Analyst, Departmental Data Analyst (e.g. HR, Marketing etc.), Problem Analyst, Junior Analyst, Marketing Data Analyst.

 

Level: 4
Qualification gained: Level 4 Data Analyst Apprenticeship

1. Standards to be met
2. Length of apprenticeship
3. Training modules
4. Entry requirements
5. End point assessment
6. Progression
7. Funding

Standards to be met

The Apprenticeship standard details the essential Knowledge, Skills and Behaviours that somebody would need to demonstrate to be successful in this job role, this includes practising continuous self-learning to keep up to date with technological developments. Apprentices will need to show they are competent in all the areas detailed in the standard when they take End Point Assessment.

The Knowledge areas of the apprenticeship will be covered through completion of our dedicated training modules which have been mapped to the standard. The Skills and Behaviours are developed through the practical experience gained in the job role, workplace training and mentoring, and the completion of 2 work-based projects.

Knowledge

  • Legal and Regulatory Requirements keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn current relevant legislation and its application to the safe and ethical use of data.

    Organisational data and information security standards, policies and procedures relevant to data management activities.

    Quality risks inherent in data and how to mitigate/resolve them.

  • Principles and Types of Data keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn principles of data, including open and public data, administrative data, and research data.

    The differences between structured and unstructured data.

  • Data Structures, Database Design and Data Architecture keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn the fundamentals of data structures, database system design, implementation and maintenance.

    Organisational data architecture.

  • User Experience and Customer Requirements keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn principles of user experience and domain context for data analytics.

    Principal approaches to defining customer requirements for data analysis.

  • Data Analysis Approaches keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn principles of the data life cycle and the steps involved in carrying out routine data analysis tasks including combining data from different sources and approaches to organisational tools and methods for data analysis.

  • Statistical, Predictive and Prescriptive Analytics keyboard_arrow_up keyboard_arrow_down

    Apprentices will learn the principles of statistics for analysing datasets and principles of descriptive, predictive and prescriptive analytics.

Skills

  • Analysing Data Sets and Sources keyboard_arrow_up keyboard_arrow_down

    Implement the stages of the data analysis lifecycle including analysing data sets taking account of different data structures and database designs.

    Identify data sources and the risks, challenges to combination within data analysis activity.

  • Data classification, risks and security keyboard_arrow_up keyboard_arrow_down

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

    Apply principles of data classification within data analysis activity.

  • Data Architecture Requirements keyboard_arrow_up keyboard_arrow_down

    Apply organizational architecture requirements to data analysis activities.

  • User Experience and Customer Requirements keyboard_arrow_up keyboard_arrow_down

    Assess the impact on user experience and domain context on the data analysis activity.

    Identify and escalate quality risks in data analysis with suggested mitigation/resolutions as appropriate.

    Undertake customer requirements analysis and implement findings in data analytics planning and outputs.

  • Statistical, Predictive and other Analysis keyboard_arrow_up keyboard_arrow_down

    Apply statistical methodologies to data analysis tasks including predictive analytics in the collation and use of data.

    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.

  • Collaboration and Communication keyboard_arrow_up keyboard_arrow_down

    Collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience.

  • Visualising data keyboard_arrow_up keyboard_arrow_down

    Collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs.

    Select and apply the most appropriate data tools to achieve the best outcome.

Behaviours

  • Productive and Professional keyboard_arrow_up keyboard_arrow_down

    Maintain productive, professional and secure working environment.

  • Initiative keyboard_arrow_up keyboard_arrow_down

    Shows initiative, being resourceful when faced with a problem and taking responsibility for solving problems within their own remit.

  • Independent and Collaborative working keyboard_arrow_up keyboard_arrow_down

    Works independently and collaboratively.

  • Logical and Analytical keyboard_arrow_up keyboard_arrow_down

    Identifies issues quickly, enjoys investigating and solving complex problems and applies appropriate solutions.

    Has a strong desire to push to ensure the true root cause of any problem is found and a solution is identified which prevents recurrence.

  • Resilience and Adaptability keyboard_arrow_up keyboard_arrow_down

    Demonstrates resilience by viewing obstacles as challenges and learning from failure.

    Demonstrates an ability to adapt to changing contexts within the scope of a project, direction of the organisation or Data Analyst role.

Length of Apprenticeship

The End Point Assessment cannot be taken until the apprentice has been on programme for at least 12 months. The Apprenticeship will typically take 18 months in order for them to complete all of the training modules, be able to consistently work at or above the occupational standard, create a portfolio of evidence and complete the independent end point assessment.

Key milestones:

person Ongoing skills and behaviours
av_timer Optional interactive sessions
laptop Knowledge
person_pin Talent coach check in
border_color End point assessment


 
START OF APPRENTICESHIP
 
 
Month 1
person_pin Onboarding and induction

person Analysing data sets

 
Month 2
laptop Microsoft Office Specialist - Excel Associate.

 
Month 3
person Statistical and Predictive analytics.

person_pin Talent coach check in

laptop MOS and DATA literacy certification exams

 
Month 4
av_timer Time management

laptop Data and Visualisation. Using Tableau and Power BI.

person Data Visualisation.

 
Month 5
person Data and Visualisation

 
Month 6
person_pin Talent coach check in

person Requirements analysis

laptop Data Analysis and Statistics

 
Month 7
person Presenting results

av_timer Personal Impact

 
Month 8
laptop SQL and Data Modelling

 
Month 9
person_pin Talent coach check in

person Making recommendations

 
Month 10
laptop Exploring Data Science using Python and R

av_timer Presentation Skills

 
Month 11
person Collaboration and Communication

 
Month 12
person_pin Talent coach check in

person Resilience and adaptability

 
Month 13
laptop Data Challenge

 
Month 14
border_color Submit portfolio

person_pin Talent coach check in

Month 15
border_color Gateway

Month 16
border_color Project with Presentation and Questioning

Month 17
border_color Professional Discussion with Portfolio

Month 18
border_color Completion

Training modules

Apprentices will need to complete all their training modules to cover the knowledge required in the apprenticeship standard and to be fully prepared for the end point assessments.

All modules consist of online self-paced learning and a live training component. These components are linked to work-based projects that the learner completes to support them in building competencies and their portfolio.

Training will be delivered through our flexible live online classes. The following training modules are completed by apprentices on this standard:

Microsoft Office Specialist: Excel Associate

This module allows learners to demonstrate competency in the fundamentals of creating and managing worksheets and workbooks, creating cells and ranges, creating tables, applying formulas and functions, and creating charts and objects.

This will include how to:

  • Manage worksheets and workbooks
  • Manage data cells and ranges
  • Manage tables and table data
  • Perform operations by using formulas and functions
  • Manage charts

Learners will have an opportunity to attempt the official Microsoft Online Certification exam to assess your skills in Excel 2019. Passing the exam will award the learner the Microsoft Office Specialist: Excel Associate (Excel and Excel 2019) certification which is an internationally recognised qualification.

Data and Visualisation using Tableau and Power BI

This module equips learners with these modern analytical skills and the ability to analyse trends in data and generate business intelligence for enhanced business operations and better decision making in day to day business.

It will cover:

  • Importance of data
  • Types of data and data sources
  • The data analytics lifecycle
  • Data Visualisation using Tableau and Power BI

Data Analysis and Statistics

This module builds on the previous module to help learners understand different types of analysis including statistical analysis of data.

It will cover:

  • Data analysis and Pre-processing techniques
  • Statistical techniques
  • Predictive Analytics including data mining
  • Supervised and Unsupervised learning
  • Testing and Evaluation

SQL and Data Modelling

This module will introduce learners to data modelling and SQL databases. It will cover:

  • Types of databases, their importance and applications
  • Using SQL to perform various functions including queries, joins, subqueries, sets and managing tables
  • Data modelling and designing databases
  • Cloud based databases and their applications

Exploring Data Science using Python and R

This module will explore advanced data analysis concepts and working with various tools that will support working with large datasets. It will delve into concepts of big data and the links between a data analysis and data science role.

It will cover:

  • Introductory Data Science Concepts
  • Usage of tools such as Python, R and Hadoop
  • Cloud based tools for data analysis

Data Challenge

This two-day workshop will take the learner through a practical application of a data project.

  • Learners will be provided with a practical project structure which will involve working through various data analysis activities. This will include working with a large data set, processing data, gathering insights from the data and presenting this in an appropriate format.
  • The data challenge will help support the learner in preparing them for their End Point Assessment giving them an opportunity to build their data analysis skills in an immersive exercise getting real time feedback as they hone their skills.

Entry requirements

Apprentices on this standard must be in a full-time data analysis role involved with all aspects of data analysis including requirement-gathering, inspecting, cleansing, transforming and modelling data with the goal of discovering useful information, informing conclusions and supporting decision-making.

Apprentices who have not achieved an A*-C GCSE (or equivalent) in Maths and English GCSE are required to gain Functional Skills Level 2 as part of this Apprenticeship.

Apprentices typically have one of the following:

  • A Level 3 Apprenticeship
  • 2 A Levels or International Baccalaureate or any other Level 3 qualification such as a BTEC Extended Diploma
  • 12 months of work experience in the last 24 months if they do not have any other Level 3 qualifications

Additionally, apprentices must have a grade C (4) or above in Maths at GCSE or equivalent.

End point assessment

Every Apprenticeship includes an End Point Assessment (EPA), assessed by an independent End Point Assessment Organisation (EPAO). The apprentice will take their EPA at the end of their programme where they will demonstrate they are competent in the role that they have developed in.

This apprenticeship end point assessment will include:

1. Project with presentation and questioning

This assessment will have 2 subcomponents:

Component 1: Data Analysis Project

The apprentice will work through a work-based project issued by the Employer. The project will be designed to give the Data Analyst the opportunity to demonstrate the Knowledge, Skills and Behaviours mapped to the assessment method within their day to day work and may cover the following project ideas to enable them to demonstrate competence:

  • Patterns / trends and predictions
  • Presenting statistical analysis results to inform decisions
  • Optimising data models using statistical measures

The employer will ensure it has a real business application.

Component 2: Presentation with Questioning

Apprentices will prepare and deliver a presentation that appropriately covers the Knowledge, Skills and Behaviours assigned to this method of assessment.

The presentation will be based on the project and will cover:

  • a summary of the main aspects of the project
  • context/ implications/recommendations from the project
  • practical application of knowledge, skills and behaviours
  • business recommendations/ outcomes of the project, including visualisations
  • any follow-on outcomes
  • actions and next steps

2. Professional discussion with portfolio

This assessment will take the form of a professional discussion appropriately structured to draw out the best of the apprentice’s competence. It will involve questions that will focus on the knowledge, skills and behaviours mapped to this method of assessment.

A portfolio of evidence containing examples of work sufficient to show the apprentice can apply the knowledge, skills and behaviours mapped to the professional discussion is submitted. The portfolio is not directly assessed, it underpins the professional discussion.

Progression

An apprentice’s journey doesn’t end when their apprenticeship has finished. This is just their first step to becoming a Data professional. The next steps could be to work towards more advanced Data Analysis qualifications, take up higher education studies at a university or start a level 6 technology apprenticeship.

Funding

This apprenticeship standard is currently funded at £15,000. Please note that this standard is currently under review as part of the statutory review of digital standards. Any changes required may need to be reflected in a revised funding band.

For non or marginal Levy payers (where you have overspent your Levy fund), 95% of the cost of the apprenticeship will be funded by the government meaning you will only have to pay 5% of the agreed price. Please contact us for more information on the Levy and funding.

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