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Data technician

Data technician

Digital

Level 3 - Technical Occupation

Source, format and present data securely in a relevant way for analysis.

Reference: OCC0795

Status: assignment_turned_inApproved occupation

Average (median) salary: £31,193 per year

SOC 2020 code: 3544 Data analysts

SOC 2020 sub unit groups:

  • 3544/00 Data analysts
  • 2133/02 Data architects
  • 2133/03 Data engineers
  • 3133/01 Database administrators
  • 4152/00 Data entry administrators

Technical Education Products

ST0795:

Data technician

(Level 3)

Approved for delivery
  • Career Starter Apprenticeship

Employers involved in creating the standard:

Fujitsu, Lloyds Banking, GEO Strategies, Accenture, Accordio Ltd, Stategic Discourse Ltd, Digital Care Consultancy Ltd

Summary

This occupation is found in all sectors where data is generated or processed including but not limited to finance, retail, education, health, media, manufacturing and hospitality. The broad purpose of the occupation is to 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. They would typically work as a member of a team; this may be office based or virtual. An employee in this occupation will be responsible for collecting and processing data under the guidance of a senior colleague or multiple colleagues across the business. This may vary by sector and size of the organisation. An employee would mainly be responsible for their own work but may have the opportunity to mentor others.

Employers involved in creating the standard:

Fujitsu, Lloyds Banking, GEO Strategies, Accenture, Accordio Ltd, Stategic Discourse Ltd, Digital Care Consultancy Ltd

Typical job titles include:

Data support analyst
Data technician
Junior data analyst
Junior information analyst

Keywords:

Analysis
Data
Ict
Pracitioner
Secure
Technician

Knowledge, skills and behaviours (KSBs)

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.

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.

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.

Duties

Duty D1

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

Duty D2

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

Duty D3

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

Duty D4

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

Duty D5

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

Duty D6

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

Duty D7

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

Duty D8

store, manage and share data securely in a compliant manner

Duty D9

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

Duty D10

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

Occupational Progression

This occupational progression map shows technical occupations that have transferable knowledge and skills.

In this map, the focused occupation is highlighted in yellow. The arrows indicate where transferable knowledge and skills exist between two occupations. This map shows some of the strongest progression links between the focused occupation and other occupations.

It is anticipated that individuals would be required to undertake further learning or training to progress to and from occupations. To find out more about an occupation featured in the progression map, including the learning options available, click the occupation.

Progression decisions have been reached by comparing the knowledge and skills statements between occupational standards, combined with individualised learner movement data.

Technical Occupations

Levels 2-3

Higher Technical Occupations

Levels 4-5

Professional Occupations

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Digital