The Data and AI School of London is an NCFE approved centre for this qualification (NCFE Account No. 11001657). Enrol below to begin your learning journey.
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Level 3 · NCFE Self-paced
Enrolling now NCFE Approved Qualification number 603/7882/7

NCFE Level 3 Certificate in Data

Become a data technician: source, collate, clean, blend and analyse data, present it to any audience, and store it securely and lawfully. 195 guided learning hours, UCAS points are allocated to this qualification; see UCAS for the current tariff.

Duration: 195 guided learning hours, 245 total hours, self-paced online

Level
Level 3
Qualification number
603/7882/7
Awarding organisation
NCFE
Regulated status
On the RQF, regulated by Ofqual
Guided learning hours
195 hours
Total qualification time
245 hours
Delivery
100% online
Study pattern
195 guided learning hours, 245 total hours, self-paced online
NCFE This qualification is awarded by NCFE and regulated by Ofqual
NCFE Account No. 11001657

Course overview

This is a regulated Level 3 qualification (NCFE qualification number 603/7882/7). It is designed to equip learners with the knowledge and skills required to enter a job role within the digital workforce area, such as a data technician.

The qualification is mapped against the Level 3 Data Technician Apprenticeship Standard. It is a standalone qualification and does not form part of the apprenticeship standard or its end-point assessment.

This qualification has been allocated UCAS points. Please refer to the UCAS website for the points allocation and the most up-to-date information.

You study six mandatory units totalling 195 guided learning hours. Unit 01 covers where common sources of data are found, including internal, external and open datasets such as those published by DEFRA, local government and the Office for National Statistics, along with data formats and the purpose and function of data architecture and integration.

Unit 02 is the largest unit at 55 guided learning hours and is highly practical. You collect, format, migrate, export and save datasets, select analysis tools and apply data cleansing, test and assess confidence in data including the effect of bias, and blend, manipulate and link datasets from multiple sources.

Unit 03 covers applying statistical methods and algorithms to identify trends and patterns, performing predictive data analytics, justifying and analysing findings, and filtering data to business requirements.

Unit 04 covers the methods, formats and techniques used to communicate data to different roles, understanding audience requirements, and applying both advanced and non-advanced visualisation tools and techniques, then evaluating the decisions behind those choices.

Unit 05 covers the legal and regulatory framework, including the purpose and function of the GDPR, the Data Protection Act 2018 and the differences between them, Intellectual Property Rights, the data sharing code of practice and the role of the Information Commissioner's Office. It also covers ethical and legitimate use of data, consent, and securely storing, managing and distributing data.

Unit 06 covers the role of data in a business context, operating within a multi-functional team, producing technical documentation, and informing your own continuous professional development by evaluating technological developments and learning techniques against a personal development plan.

Assessment is by an internally assessed and externally quality assured portfolio of evidence, with no exams. Grading is achieved or not yet achieved. Evidence could include reports, presentations with notes or audio explanation, and evidence of research.

Learners who achieve this qualification could progress to employment as a data technician, or to further education including the Level 3 Certificate in Digital Support, the Level 4 Diploma: Data Analyst or the Level 4 Diploma: Cyber Security Engineer.

Delivery is 100% online with tutor support.

What you will study

The units below, their unit reference numbers and their guided learning hours are taken directly from the NCFE qualification specification.

Unit Title Unit reference Hours
01 Understand how to source data (mandatory)
3 learning outcomes
  1. Understand where common sources of data can be found
    • 1.1 Explain the role of data in the context of a digital world
    • 1.2 Explain the internal datasets that can be used for analysis
    • 1.3 Explain the external datasets that can be used for analysis
    • 1.4 Describe the open datasets that can be used for analysis
  2. Understand data formats and their importance for analysis for a specific business requirement
    • 2.1 Explain the functions and purpose of data formats
    • 2.2 Explain the importance of selecting the appropriate data format for data analysis
  3. Understand the purpose and function of data architecture for a specific business requirement
    • 3.1 Explain the purpose, principles and functions of data architecture
    • 3.2 Explain the purpose and function of integration
    • 3.3 Evaluate the factors that impact the data architecture based on: • access requirements • security requirements
 L/618/8650 20
02 Collate and format data for processing and analysis (mandatory)
5 learning outcomes
  1. Be able to collect, format and save datasets for a specific business requirement
    • 1.1 Explain the methods of collecting datasets
    • 1.2 Source the appropriate data that contains the required information
    • 1.3 Migrate the appropriate data to the required database
    • 1.4 Apply an appropriate format for the data
    • 1.5 Export and save the data
  2. Be able to prepare data for analysis for a specific business requirement
    • 2.1 Select the appropriate tool for data analysis
    • 2.2 Apply appropriate data cleansing measures
  3. Be able to test and assess confidence in the data and its integrity
    • 3.1 Explain the impact and effect of bias on the integrity and usability of data
    • 3.2 Apply appropriate validation and verification methods
  4. Be able to blend datasets from multiple sources for a specific business requirement
    • 4.1 Explain the importance of blending data from multiple sources
    • 4.2 Apply appropriate blended data techniques from multiple sources
    • 4.3 Provide blended data in an appropriate format
  5. Be able to manipulate and link external datasets
    • 5.1 Explain the importance of manipulating and linking different datasets
    • 5.2 Apply appropriate manipulation and linking techniques
    • 5.3 Provide linked datasets in an appropriate format
 R/618/8651 55
03 Analyse data to support business outcomes (mandatory)
3 learning outcomes
  1. Be able to apply statistical methods to identify trends and patterns in data for a specific business
    • 1.1 Explain the importance of using statistical methods
    • 1.2 Explain the common techniques used in statistical methods
    • 1.3 Apply appropriate statistical methods to interpret and identify trends and patterns in data
    • 1.4 Justify the outcome of data findings
  2. Be able to apply algorithms to identify trends and patterns in data based on a specific business
    • 2.1 Explain the role of algorithms to identify trends and patterns in data
    • 2.2 Perform predictive data analytics based on a dataset using algorithms
    • 2.3 Analyse the outcome of data findings
  3. Be able to filter data according to business requirements
    • 3.1 Identify the elements that need filtering
    • 3.2 Carry out filtering techniques
 Y/618/8652 30
04 Present and communicate data to the appropriate audience (mandatory)
4 learning outcomes
  1. Understand the range of methods, formats and techniques used to communicate data to different
    • 1.1 Explain the range of methods relevant to communicating data
    • 1.2 Explain the range of formats applied to communications
    • 1.3 Explain the range of communication techniques that can be applied
    • 1.4 Explain the audience requirements when communicating to a range of roles within an organisation
  2. Be able to communicate data and results to a specific audience and business requirement
    • 2.1 Apply the appropriate communication methods to present data and results
    • 2.2 Summarise gathered data using a narrative to communicate to a specific audience
  3. Understand the range of visualisation tools and techniques used to present data for specific
    • 3.1 Explain the range of visualisation tools used to present data for business requirements
    • 3.2 Explain the range of visualisation techniques used to present data for specific audiences
  4. Be able to apply a range of visualisation tools and techniques to present data for specific
    • 4.1 Apply advanced and non-advanced visualisation tools to present data
    • 4.2 Apply the appropriate visualisation techniques for specific audiences
    • 4.3 Apply the appropriate visualisation techniques for business requirements
    • 4.4 Evaluate the decision process of selected visualisation techniques for specific audiences and business requirements
 H/618/8654 30
05 Store, manage and distribute data securely (mandatory)
3 learning outcomes
  1. Understand legal and regulatory requirements that apply to data analysis
    • 1.1 Explain the purpose and function of the General Data Protection Regulation (GDPR)
    • 1.2 Explain the purpose of the Data Protection Act 2018 (DPA)
    • 1.3 Distinguish the primary differences between the GDPR and the DPA
    • 1.4 Explain the functions of Intellectual Property Rights (IPR)
    • 1.5 Explain the purpose and applications of the data sharing code of practice
    • 1.6 Describe the role of the Information Commissioner’s Office (ICO)
  2. Understand the legitimate and ethical use of data
    • 2.1 Explain the ethical considerations when analysing data
    • 2.2 Explain the principles of consent in the use of data
    • 2.3 Explain the ethical considerations related to primary and secondary use of data
  3. Be able to securely store, manage and distribute data for a specific business requirement
    • 3.1 Explain the security controls and procedures to ensure data security
    • 3.2 Explain the impacts of common threats to organisations
    • 3.3 Apply data handling methods to manage data in a compliant manner
    • 3.4 Apply storing and distributing methods to data in a compliant manner
    • 3.5 Summarise the appropriate methods, security controls and procedures to meet the required outcome of data analysis
 K/618/8655 30
06 Collaborate with others and practise continuous professional development (mandatory)
3 learning outcomes
  1. Understand the role of data within a business context
    • 1.1 Explain the importance of data in resolving customer issues
    • 1.2 Explain the importance of data to brand awareness
    • 1.3 Explain the importance of data to cultural awareness and diversity
    • 1.4 Explain the importance of data to accessibility
    • 1.5 Explain the importance of data to an internal and external audience
    • 1.6 Explain the importance of data to a business
  2. Be able to operate as part of a multi-functional team for a specific business requirement
    • 2.1 Explain the range of roles within an organisation
    • 2.2 Identify the communication tools for collaborative working
    • 2.3 Produce technical documentation of data and results to meet a specific business requirement
    • 2.4 Discuss the benefits of organisational and priority skills to a collaborative project
    • 2.5 Apply organisational and priority skills to a collaborative project
  3. Be able to inform own continuous professional development (CPD) through identification of
    • 3.1 Evaluate technological developments from a range of possible sources
    • 3.2 Evaluate different learning techniques based on own personal development plan (PDP)
 M/618/8656 30
Total guided learning hours 195

Entry requirements

  • There are no specific prior skills or knowledge a learner must have for this qualification.
  • Learners should be aged 16 and above to undertake this qualification.
  • Learners may find it helpful if they have already achieved a Level 2 qualification in a similar subject area.
  • You will need a laptop or desktop computer with internet access, a web browser, software capable of analysing data and reading .xls and .csv files (for example Python, Microsoft Excel, Google Sheets or OpenOffice), electronic data collection software such as Microsoft Forms or Google Forms, infographic creation software, presentation software and a printer.
  • Registration is at the discretion of the centre, in accordance with equality legislation.
Take it with you

The course guide

Everything on this page as one document you can keep, print, or send to whoever is deciding with you.

  • All 6 units, with the hours behind each one
  • How you are assessed, and who checks the marking
  • How paying works, and what is due when
  • Entry requirements and where the qualification leads
Download the guide (PDF)

Generated from this qualification's record, so the units and hours in it are the ones on this page. The fee is here on the page rather than in the guide, so a saved copy cannot quote you an old one.

How you are assessed

Your work is assessed by our qualified assessors, internally quality assured, and externally quality assured by NCFE. Assessment is against the criteria published in the qualification specification, and your assessor tells you what is needed before you start each unit.

For what happens after you submit: who marks it, who checks the marking, how long feedback takes and what to do if you disagree with a decision, see how assessment works.

If you need an adjustment to how you are assessed, for a disability or any other reason, ask us before you begin. We arrange adjustments under our Reasonable Adjustments policy, and you can request one online.

How we assess and quality assure is set out in DAIS-POL-016 Assessment and Internal Quality Assurance.

How you study, and what you need

You study online through our virtual learning environment, which is where the teaching material, your assessment submissions, your feedback and your progress all live. You work at your own pace, with tutor support throughout. Everyone completes a short online induction before starting an assessed unit.

What you need to take part
Device Laptop or desktop computer
Operating system Windows 10 or macOS 10.15 or later
Browser Google Chrome or Mozilla Firefox, latest version
Internet speed 10 Mbps download and 5 Mbps upload
Webcam Required for live sessions and identity verification
Microphone Required for live sessions

These are the minimum requirements published in DAIS-POL-024 Online Learning and Digital Delivery.

Support, and how quickly we reply

These are the response times we commit to in policy, not an aspiration.

What How Response
General questions Message your tutor in the VLE Within 2 working days
Assessment feedback Returned in the VLE or e-portfolio Within 10 working days of submission
Technical problems Technical support email Within 1 working day
Urgent welfare concerns Email to the Designated Safeguarding Lead Within 1 working day

Published in DAIS-POL-024 and DAIS-POL-009 Learner Support.

Registration and your certificate

We register you with NCFE before you begin any assessed unit, and we collect your Unique Learner Number as part of that. When your assessment decisions are finalised and quality assured, we claim your certificate through the NCFE portal and you are notified digitally. The certificate comes from NCFE, not from us.

Set out in DAIS-POL-008 Learner Registration and Certification.

Progression

Progression: prepares you for our Level 4 Diploma: Data Analyst, and for data analyst roles. This qualification does not carry UCAS Tariff points.

Common questions

Who awards NCFE Level 3 Certificate in Data, and how do I get my certificate?

NCFE Level 3 Certificate in Data is awarded by NCFE, an Ofqual-approved awarding organisation, and sits on the Regulated Qualifications Framework (RQF). The qualification number is 603/7882/7. The Data and AI School of London is an NCFE approved centre (Account No. 11001657). We register you with NCFE before you start any assessed unit and collect your Unique Learner Number. Once your work is assessed and quality assured we claim your certificate through the NCFE portal, and it is issued by NCFE rather than by us.

How long does NCFE Level 3 Certificate in Data take?

This qualification carries 195 guided learning hours and a total qualification time of 245 hours. It is studied online at your own pace, so how long it takes in calendar time depends on how much you can commit each week.

What do I need before I can start?

There are no specific prior skills or knowledge a learner must have for this qualification. We assess every applicant individually and will tell you if a different level would suit you better.

Can I study this entirely online?

Yes. Teaching, materials and assessment are all delivered through our Moodle-based virtual learning environment, so you can study from anywhere in the UK. You need a laptop or desktop computer, a current version of Chrome or Firefox, and a broadband connection of at least 10 Mbps down and 5 Mbps up. Tutor support is available throughout, and we answer questions within 2 working days and return assessment feedback within 10 working days of submission.

Can I enrol now, and when do I pay?

The fee is £495. Enrolment is open, so you can apply online today. Nothing is paid at application: payment is taken only after you accept an offer.

Not sure this is the right qualification?

Ask before you apply. We will say honestly if a different level would suit you better.

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