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Overview of the role

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

Data technician

Details of standard

Occupation 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.

Typical job titles include:

Database Technician Data support analyst Junior data analyst Junior information analyst


Occupation duties

Duty

Criteria for measuring performance

KSBs

Duty 1 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

K1 K2 K15

S1

B1 B2 B4

Duty 2 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

K3

S2 S16

B1 B2 B4

Duty 3 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.

K4 K5

S3

B5 B6

Duty 4 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

K6

S4 S5 S6 S16

B1 B2 B4

Duty 5 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

K7 K8 K9

S7

B1 B2 B3 B4 B5 B6

Duty 6 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

K10 K11

S8 S9 S16

B1 B2 B3 B4

Duty 7 Communicate results verbally, through reports and technical documentation and tailoring the message for the audience

Results from data communicated in line with audience requirements

K5 K12

S10 S11

B5 B6

Duty 8 Store, manage and share data securely in a compliant manner

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

K13

S12 S15

B4

Duty 9 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

K14

S13 S15 S16 S17 S18

B2 B5 B6

Duty 10 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

K15 K16

S14 S15 S16 S17 S18

B2 B3 B4


KSBs

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. Back to Duty

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

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

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 Back to Duty

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 Back to Duty

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

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 Back to Duty

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

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

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 Back to Duty

K11: Different methods of validating data and the importance of taking corrective action Back to Duty

K12: Communicating the results through basic narrative Back to Duty

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 Back to Duty

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 Back to Duty

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 Back to Duty

K16: Different learning techniques, learning techniques and the breadth and sources of knowledge Back to Duty

Skills

S1: Source and migrate data from already identified different sources Back to Duty

S2: Collect, format and save datasets Back to Duty

S3: Summarise and explain gathered data Back to Duty

S4: Blend data sets from multiple sources and present in format appropriate to the task Back to Duty

S5: Manipulate and link different data sets as required Back to Duty

S6: Use tools and techniques to identify trends and patterns in data Back to Duty

S7: Apply basic statistical methods and algorithms to identify trends and patterns in data Back to Duty

S8: Apply cross checking techniques for identifying faults and data results for data project requirements Back to Duty

S9: Audit data results Back to Duty

S10: Demonstrate the different ways of communicating meaning from data in line with audience requirements Back to Duty

S11: Produce clear and consistent technical documentation using standard organisational templates Back to Duty

S12: Store, manage and distribute in compliance with data security standards and legislation Back to Duty

S13: Explain data and results to different audiences in a way that aids understanding. Back to Duty

S14: Review own development needs Back to Duty

S15: Keep up to date with developments in technologies, trends and innovation using a range of sources Back to Duty

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. Back to Duty

S17: Operate as part of a multi-functional team Back to Duty

S18: Prioritise within the context of a project Back to Duty

Behaviours

B1: Manage own time to meet deadlines and manage stakeholder expectations Back to Duty

B2: Work independently and take responsibility Back to Duty

B3: Use own initiative Back to Duty

B4: A thorough and organised approach Back to Duty

B5: Work with a range of internal and external customers Back to Duty

B6: Value difference and be sensitive to the needs of others Back to Duty


Qualifications

English & Maths

Apprentices without level 2 English and maths will need to achieve this level prior to taking the End-Point Assessment. For those with an education, health and care plan or a legacy statement, the apprenticeship’s English and maths minimum requirement is Entry Level 3. A British Sign Language (BSL) qualification is an alternative to the English qualification for those whose primary language is BSL.


Additional details

Occupational Level:

3

Duration (months):

24

Review

This apprenticeship standard will be reviewed after three years

Status: Approved for delivery
Level: 3
Reference: ST0795
Version: 1.0
Approved for delivery: 10 July 2020
Route: Digital
Typical duration to gateway: 24 months (this does not include EPA period)
Maximum funding: £12000
Trailblazer contact(s): damian.jacobs@lloydsbanking.com
Employers involved in creating the standard: Fijitsu, Lloyds Banking, GEO Strategies, Accenture, Accordio Ltd, Stategic Discourse Ltd, Digital Care Consultancy Ltd
LARS Code: 576

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