Data Technician Apprenticeship Level 3

Standards to be met

The Apprenticeship standard sets out 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 courses 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

• Types and Formats of Data keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn a range of different types of existing data. Data formats and their importance for analysis including presentation tools to visualise. Data architecture - including on premises and cloud. Accessing, extracting, collating and formatting data in line with industry standards.

• Communicating and Presenting Data keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn communication methods, formats and techniques, including written, verbal, non-verbal, presentation, email, conversation, audience and active listening.

  Communicating with a range of roles within an organisation, including customer, manager, client, peer, technical and non-technical. How to filter details, focusing on information relevant to the data project and communicating the results through basic narrative.

• Value and Role of Data keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn the value of data to the organisation. The significance of end user issues, problems, organisation value, brand awareness, cultural awareness/ diversity, accessibility, internal/ external audience, level of technical knowledge and profile in an organisation context.

  The role of data in the context of the digital world including the use of external trusted open data sets, how data underpins every digital interaction and connectedness across the digital landscape including applications, devices, IoT, customer centricity.

• Algorithms keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn about Algorithms, and how they work using a step-by-step solution to a problem, or rules to follow to solve the problem and the potential to use automation.

• Legal and Regulatory Requirements keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn about legal and regulatory requirements e.g. Data Protection, Data Security, Intellectual Property Rights (IPR), Data sharing, marketing consent, personal data definition. The ethical use of data.

• Data Validation and Quality Issues keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn about the range of common data quality issues that can arise e.g. misclassification, duplicate entries, spelling errors, obsolete data, compliance issues and interpretation/ translation of meaning. Different methods of validating data and the importance of taking corrective action.

• Statistical Models and Data Modelling keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn about basic statistical methods and simple data modelling to extract relevant data and normalise unstructured data.

• Learning techniques keyboard_arrow_up keyboard_arrow_down

  Apprentices will learn about different learning techniques and the breadth and sources of knowledge.

Skills

• Source and Migrate Data keyboard_arrow_up keyboard_arrow_down

  Source and migrate data from already identified different sources. Collect, format and save datasets.

• Clean and Process Data keyboard_arrow_up keyboard_arrow_down

  Blend data sets from multiple sources and present in format appropriate to the task.

  Manipulate and link different data sets as required.

  Apply cross checking techniques for identifying faults and data results for data project requirements.

  Clean data i.e. remove duplicates, typos, duplicate entries, out of date data, parse data.

• Identify Trends, Patterns and Insights keyboard_arrow_up keyboard_arrow_down

  Use tools and techniques to identify trends and patterns in data.

  Apply basic statistical methods and algorithms to identify trends and patterns in data.

• Summarise and Explain Data keyboard_arrow_up keyboard_arrow_down

  Summarise and explain gathered data. Demonstrate the different ways of communicating meaning from data in line with audience requirements.

  Explain data and results to different audiences in a way that aids understanding.

• Manage Data keyboard_arrow_up keyboard_arrow_down

  Store, manage and distribute in compliance with data security standards and legislation.

• Technical Documentation and Auditing keyboard_arrow_up keyboard_arrow_down

  Audit data results.

  Produce clear and consistent technical documentation using standard organisational templates.

• Development keyboard_arrow_up keyboard_arrow_down

  Review own development needs.

  Keep up to date with developments in technologies, trends and innovation using a range of sources.

• Work in a team keyboard_arrow_up keyboard_arrow_down

  Operate as part of a multi-functional team.

  Prioritise within the context of a project.

Behaviours

• Time Management keyboard_arrow_up keyboard_arrow_down

  Manage own time to meet deadlines and manage stakeholder expectations.

• Responsibility, Independence and Initiative keyboard_arrow_up keyboard_arrow_down

  Work independently and take responsibility. Use own initiative.

• Thorough and Organised keyboard_arrow_up keyboard_arrow_down

  A thorough and organised approach.

• Working with Others keyboard_arrow_up keyboard_arrow_down

  Work with a range of internal and external customers.

  Value difference and be sensitive to the needs of others.

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:

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 Literacy

As learners start their roles as data technicians, they need to understand how data is used in an organisation, working in a data-driven culture and making data-driven decisions. This module will introduce the learners to the world of data, how it is being used to drive business decisions and how data can be used for storytelling. It will build on their previous knowledge of working with spreadsheets by bringing in concepts on how data can be used for various purposes.

Learners will be introduced to various facets of data, including data protection and governance (GDPR and Data Protection Laws), understanding data, basics of analytics and data informed decision making.

Learners will additionally complete an online assessment to demonstrate their competence in being data literate.

Data Analysis and Visualisation with Excel

This module will enable learners to perform robust and advanced data and statistical analysis using Pivot Tables, use tools such as Power Pivot and the Data Analysis ToolPak to analyse data, and visualise data and insights using advanced visualisations in charts and dashboards.

• Perform data analysis fundamentals
• Visualise data with Excel
• Analyse data with formulas and functions
• Analyse data with PivotTables
• Present visual insights with dashboards in Excel
• Create geospatial visualisation with Excel
• Perform statistical analysis
• Get and transform data
• Model and analyse data with Power Pivot
• Present insights with reports

Databases and Data Modelling

This module delves into the principles and use of databases. It will cover the essential concepts of databases including:

• What is a database
• Designing a database and data modelling
• Managing tables
• Querying and sharing data in the database using SQL

The learners will be able to take this knowledge and practical understanding to use database systems in the workplace including cloud based database systems.

Data Challenge

This three-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 activities that a data technician will typically carry out. This will include picking data from various sources, cleansing data, processing it and visualising data to be presented to various stakeholders.
• The data challenge will help support the learner in preparing them for their End Point Assessment giving them an opportunity to build their data 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 support role where collecting and processing data under the guidance of a senior colleague is the primary focus of their work activities. There are no other formal entry requirements for this Apprenticeship.

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:

• GCSE or other Level 2 qualification
• 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. Professional Discussion underpinned by 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.

2. Scenario demonstrations with questioning

The apprentice is observed completing two scenario demonstrations in which they will conduct data gathering operations and data analysis and validation operations. The observations are supplemented by questioning to establish understanding of underpinning reasoning.

Progression

The next step would be to undertake the Level 4 Data Analyst apprenticeship, providing the apprentice is in a job role that matches the Standard. This level has a focus on using more advanced technical and communication skills to inform conclusions and support business decision-making with data.

Funding

The total cost of this apprenticeship programme is £12,000. If you are a Levy payer this means that the maximum that can be withdrawn from your Levy fund for somebody on this apprenticeship is £12,000.

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.