Data Technician

Source, format and present data securely in a relevant way for analysis using basic methods; to communicate outcomes appropriate to the audience; analyse structured and unstructured data to support business outcomes; blend data from multiple sources as directed and apply legal and ethical principles when manipulating data. In their daily work, an employee in this occupation interacts with a wide range of stakeholders including colleagues, managers, customers and internal and external suppliers.

Typical Job Roles: Data Support Analyst, Data Technician, Junior Data Analyst, Junior Information Analyst.

Typical Programme Duration: 24 months.

Data Technician

Source, format and present data securely in a relevant way for analysis using basic methods; to communicate outcomes appropriate to the audience; analyse structured and unstructured data to support business outcomes; blend data from multiple sources as directed and apply legal and ethical principles when manipulating data. In their daily work, an employee in this occupation interacts with a wide range of stakeholders including colleagues, managers, customers and internal and external suppliers.

Typical Job Roles: Data Support Analyst, Data Technician, Junior Data Analyst, Junior Information Analyst.

Typical Programme Duration: 24 months.

Excellent Work-Based Learning is employer-responsive

TDM coaches guide and drive each individual, employer-responsive learning plan with intent to:

  • fully embed the employee into their new role
  • achieve and exceed the National Apprenticeship Standard.

Occupational duties

By following our Data Technician Apprenticeships learning plan, you will be able to effectively deliver the following duties:

Source data from a collection of already identified trusted sources in a secure manner

Data is collected securely from trusted sources in line with current company requirements informed by relevant regulatory and legal standards and industry best practice.

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Collate and format data to facilitate processing and presentation for review and further advanced analysis by others

Data collated and formatted according to company procedures and recognised industry good practice.

Present data for review and analysis by others, using required medium for example tables, charts and graphs

Data is presented in an appropriate format for review and analysis in line with company procedures and industry best practice.

Blend data by combining data from various sources and formats to explore its relevance for the business needs

Data is blended ensuring that accuracy and consistency is maintained in line with current company requirements informed by relevant regulatory and legal standards and industry best practice.

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Analyse simple and complex structured and unstructured data to support business outcomes using basic statistical methods to analyse the data

Data is structured in a way that meets business outcomes.

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Communicate results verbally, through reports and technical documentation and tailoring the message for the audience

Results from data communicated in line with audience requirements.

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Store, manage and share data securely in a compliant manner

Data is stored, managed and shared in line with organisation, legal and regulatory requirements.

Collaborate with people both internally and externally at all levels with a view to creating value from data

The employee is able to confidently engage with people internally and externally at all levels in a professional manner.

Validate results of analysis using various techniques, e.g cross checking, to identify faults in data results and to ensure data quality

Results are validated in line with organisation and project data quality requirements

Practise continuous self learning to keep up to date with technological developments to enhance relevant skills and take responsibility for own professional development

Articulate the latest technology trends affecting data analysis and can communicate the impacts of latest trends.

Skills, Knowledge and Behaviours

Data Technician Apprenticeships Knowledge

  • K1: Range of different types of existing data. Common sources of data – internal, external, open data sets, public and private. Data formats and their importance for analysis. Data architecture – the framework against which data is stored and structured including on premises and cloud.

  • K2: How to access and extract data from a range of already identified sources

  • K3: How to collate and format data in line with industry standards

  • K4: Data formats and their importance for analysis Management and presentation tools to visualise and review the characteristics of data Communication tools and technologies for collaborative working

  • K5: Communication methods, formats and techniques, including: written, verbal, non-verbal, presentation, email, conversation, audience and active listening Range of roles within an organisation, including: customer, manager, client, peer, technical and non-technical

  • K6: The value of data to the business How to undertake blending of data from multiple sources

  • K7: 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

  • K8: How to filter details, focusing on information relevant to the data project

  • K9: Basic statistical methods and simple data modelling to extract relevant data and normalise unstructured data

  • K10: 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

  • K11: Different methods of validating data and the importance of taking corrective action

  • K12: Communicating the results through basic narrative

  • K13: 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

  • K14: The significance of customer issues, problems, business value, brand awareness, cultural awareness/ diversity, accessibility, internal/ external audience, level of technical knowledge and profile in a business context

  • K15: The role of data in the context of of the digital world including the use of eternal trusted open data sets, how data underpins every digital interaction and connectedness across the digital landscape including applications, devises, IoT, customer centricity

  • K16: Different learning techniques, learning techniques and the breadth and sources of knowledge

Skills

  • S1: Source and migrate data from already identified different sources
  • S2: Collect, format and save datasets
  • S3: Summarise and explain gathered data
  • S4: Blend data sets from multiple sources and present in format appropriate to the task
  • S5: Manipulate and link different data sets as required
  • S6: Use tools and techniques to identify trends and patterns in data
  • S7: Apply basic statistical methods and algorithms to identify trends and patterns in data
  • S8: Apply cross checking techniques for identifying faults and data results for data project requirements
  • S9: Audit data results
  • S10: Demonstrate the different ways of communicating meaning from data in line with audience requirements
  • S11: Produce clear and consistent technical documentation using standard organisational templates
  • S12: Store, manage and distribute in compliance with data security standards and legislation
  • S13: Explain data and results to different audiences in a way that aids understanding.
  • S14: Review own development needs
  • S15: Keep up to date with developments in technologies, trends and innovation using a range of sources
  • S16: Clean data i.e. remove duplicates, typos, duplicate entries, out of date data, parse data (e.g. format telephone numbers according to a national standard) and test and assess confidence in the data and its integrity.
  • S17: Operate as part of a multi-functional team
  • S18: Prioritise within the context of a project

Behaviours

  • B1: Manage own time to meet deadlines and manage stakeholder expectations
  • B2: Work independently and take responsibility
  • B3: Use own initiative
  • B4: A thorough and organised approach
  • B5: Work with a range of internal and external customers
  • B6: Value difference and be sensitive to the needs of others

Typical Certifications

  • Data Tech Basics TDM Apply Course A: Analysing Raw Data
  • Data Tech Basics TDM Apply Course B: Communicating & Presenting Data
  • Data Tech Basics TDM Apply Course C: Contextualising Data & Legals
  • Data Analysis TDM Apply Course A: Extract & Prepare Data
  • Data Analysis TDM Apply Course B: Analysing & Modelling Data
  • Data Analysis TDM Apply Course C: Visualisation of Data
  • Data Analysis TDM Apply Course D: Workspaces & Data Sets
    • Microsoft Data Analyst
  • C&G Level 2 Functional Skills in English
  • C&G Level 2 Functional Skills in Maths

Professional Development: Skills, Attitudes and Behaviours

TDM are acutely aware that the UK faces a productivity gap in our workforce when we are compared against competitor nations.  We are determined to do our bit to improve the performance and quality standards of the UK workforce.

This is why TDM also offer a dedicated Professional Development Coach who, in collaboration with employer mentors, will further develop apprentices’:

  • Logical and creative thinking skills
  • Analytical and problem solving skills
  • Ability to work independently and to take responsibility
  • Readiness to use own initiative
  • Application of a thorough and organised approach
  • Ability to work with a range of internal and external people
  • Ability to communicate effectively in a variety of situations
  • Ability to maintain productive, professional and secure working environment
  • Engagement with Professional Development Activities which go beyond their job role

Level 2 Functional Skills Qualification in both English and Maths will need to be achieved by all TDM learners.

TDM coaches also proudly support other National Educational Priorities, such as:

  • British Values: Democracy, The Rule of Law, Tolerance & Mutual Respect, Individual Liberty.
  • Health & Safety in the Workplace
  • Employee Rights and Responsibilities
  • Equality & Diversity
  • Safeguarding (including prevention against radicalisation)

Individual Learning Plan

To achieve and exceed the National Apprenticeship Standard, 20%+ of salaried hours must be spent in learning away from the workstation.  TDM will deliberately and closely align these learning hours with the 80% of on-the-job learning hours offered by the employer.

Your Individual Learning Plan will be delivered by both “field expert” Tech Coaches and “gently uncompromising” Professional Development Coaches.  According to the particular needs of each employer / learner / topic, TDM coaches will responsively plan and deliver options such as:

  • one-to-one coaching tutorials (online or in the workplace) which guide ePortfolio and employer reference building
  • task-setting and guidance through personally selected learning activities to be completed away from workstation including (eg): eLearning, print materials, journal articles, practice labs and tutorials, etc.
  • “tutored” online group learning events
  • classroom size <=15 learners (in Birmingham or Worcester)
  • classroom size <=8 learners (in Birmingham or Worcester)
  • ad-hoc extra support from a Professional Development Coach who will support the apprentice to develop more employable attitudes and behaviours.

Typical Entry Requirements

Individual employers will set the selection criteria, but this is likely to include:

  • Five GCSEs, (especially English, Mathematics and a Science or Technology subject)
  • OR a relevant Level 2 Apprenticeship
  • OR other relevant qualifications and experience
  • OR an aptitude test with a focus on IT skills

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