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 4 · NCFE Self-paced
Enrolling now NCFE Approved Qualification number 603/7751/3

NCFE Level 4 Diploma: Data Analyst - HTQ

An employer-recognised Higher Technical Qualification giving you the skills to launch or advance a career in data analysis.

Duration: 510 guided learning hours; self-paced online study, typically one to two years

Level
Level 4
Qualification number
603/7751/3
Awarding organisation
NCFE
Regulated status
On the RQF, regulated by Ofqual
Guided learning hours
510 hours
Delivery
100% online
Study pattern
510 guided learning hours; self-paced online study, typically one to two years
NCFE This qualification is awarded by NCFE and regulated by Ofqual
NCFE Account No. 11001657

Course overview

This is a Higher Technical Qualification (HTQ), approved by the Institute for Apprenticeships and Technical Education as meeting specific employer needs and industry requirements. It is designed for learners who want to begin or advance their career within data analysis.

Made up of mandatory units, the qualification covers legislation and security standards applied to data analytics, data fundamentals and lifecycle, data structures and databases, stakeholder engagement and user experience, organisational data, and data mining and statistical analysis. Assessment combines an internally assessed portfolio of evidence with task-based controlled assessments, graded pass, merit or distinction.

It prepares learners for a variety of roles in data analysis, such as junior analyst, data analyst, marketing data analyst or problem analyst, as well as progression to related apprenticeships and higher education.

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 Legislation and security standards applied to data analytics
4 learning outcomes
  1. Explore relevant legislation and their influence on the safe use of data
  2. Investigate the impact of relevant security standards, security frameworks and organisational policies and procedures on data management activities
  3. Examine ethical data principles and the role of artificial intelligence (AI) in the collation and utilisation of data
  4. Demonstrate effective use and compliance of data systems when securely collating and utilising data
A/651/0924 30
02 Data fundamentals and lifecycle
4 learning outcomes
  1. Explore the purpose of different data types and their use, characteristics, and applications
  2. Perform analysis of datasets and relevant data structures
  3. Examine the importance of data classification and considerations needed for data management
  4. Implement the fundamental principles of the data lifecycle
D/651/0925 90
03 Data structure and databases
3 learning outcomes
  1. Examine the fundamentals of database system design
  2. Explore the application of data modelling and database design and the implementation and maintenance of database systems and process
  3. Investigate common quality risks in data and implement mitigation techniques
F/651/0926 90
04 Stakeholder engagement and user experience in data analytics
3 learning outcomes
  1. Examine how to plan and deliver an effective analysis for a range of stakeholders
  2. Demonstrate how to collate and display data using the most appropriate visualisation tools and assess the impact on user experience
  3. Explore factors that can impact user experience in relation to data analytics
H/651/0927 90
05 Organisational data
3 learning outcomes
  1. Explore common data combination techniques and identify data sources
  2. Examine common data analytics methods and the functions and features of the tools used to support this
  3. Investigate organisational data architecture and demonstrate how to design data models
J/651/0928 90
06 Data mining and statistical analysis
3 learning outcomes
  1. Examine the purpose of common statistical methodologies and their application to meet requirements
  2. Explore the purpose and application of statistical analysis
  3. Demonstrate the selection and use of appropriate tools for statistical analysis
K/651/0929 120
Total guided learning hours 510

Entry requirements

  • No specific prior skills or knowledge required, though a relevant Level 3 qualification is helpful.
  • Learners must be at least 18 years old.
  • Sound English and maths skills are recommended given the analytical nature of the course.
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 senior data analyst roles and for further specialist study in data engineering. This qualification does not carry UCAS Tariff points.

Common questions

Who awards NCFE Level 4 Diploma: Data Analyst - HTQ, and how do I get my certificate?

NCFE Level 4 Diploma: Data Analyst - HTQ is awarded by NCFE, an Ofqual-approved awarding organisation, and sits on the Regulated Qualifications Framework (RQF). The qualification number is 603/7751/3. 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 4 Diploma: Data Analyst - HTQ take?

This qualification carries 510 guided learning 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?

No specific prior skills or knowledge required, though a relevant Level 3 qualification is helpful. 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 £2,995. 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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