NCFE Diploma: Data Analyst (HTQ)

Unlock the power of data with our Level 4 Data Analyst Higher Technical Qualification (HTQ), available for delivery nationwide. Designed for aspiring data professionals, this comprehensive programme equips you with the essential skills and knowledge to analyse, interpret, and visualise data effectively. Whether you’re looking to start a new career or advance in your current role, our HTQ in Data Analysis provides the expertise needed to thrive in today’s data-driven world.

Course Materials: Data Analyst HTQ Brochure

Duration: 7-8 months Course Cost: £1400 - Payment Options

Course Overview

Our Data Analyst Higher Technical Qualification (HTQ) is designed to launch your career in data science, whether you are new to the field or considering a career shift. You will acquire programming skills and experience using a range of industry-standard software, and develop abilities in data interpretation, statistical analysis, and solving problems based on data.

This qualification will also help you become a skilled communicator, adept at presenting concepts and ideas tailored to various audiences. Additionally, you will obtain valuable transferable skills such as research, evaluation, and teamwork.

Duration:	7-8 months
Timings:	1 day a month, 9am-5pm with scheduled breaks during the session
Study Modes:	Fully remote, 6 x live training sessions, self study assessments
Qualifications and Level:	Level 4 Diploma - nationally recognised qualification
Entry requirements:	Please see below the entry requirements for the Level 4 Diploma:Data Analyst: Learners must be aged 18 or over. Learners must own (or have access to) a laptop or desktop computer with internet access. A Windows device is preferred to access the specialist data software we will use and your computer will need the ability to download free software.
Cost:	£1400 - Payment Options
Who is this aimed at?	The HTQ Level 4 Diploma in Data Analytics is perfect for: Career Starters entering data analytics Career Changers transitioning to data-focused roles Current Employees who use data in their roles to inform decisions This could include Marketing, Sales, Finance, IT, MI or Administration. Employers training staff to leverage data insights. Flexible and hands-on, it’s designed for learners at all stages.

Course Date	Information
Tuesday 22nd April 2025	Tuesdays. Module 1 - 22nd April, Module 2 - 20th May, Module 3 - 24th June, Module 4 - 29th July, Module 5 - 26th August, Module 6 - 30th September.
Wednesday 11th June 2025	Wednesdays. Module 1 - 11th June, Module 2 - 9th July, Module 3 - 6th August, Module 4 - 10th September, Module 5 - 15th October, Module 6 - 10th November.
Monday 21st July 2025	Mondays. Module 1 - 21st July, Module 2 - 18th August, Module 3 - 22nd September, Module 4 - 20th October, Module 5 - 24th November, Module 6 - 12th January 2026.

Module 1 - Data fundamentals and lifecycle This module equips learners with the skills to extract meaningful insights from complex datasets using advanced statistical methodologies. It covers key statistical techniques such as descriptive statistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictive analytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments.
Moduel 2 - Data mining and statistical analysis This module equips learners with the skills to extract meaningful insights from complex datasets using advanced statistical methodologies. It covers key statistical techniques such as descriptive statistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictive analytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments.
Module 3 - Data structure and databases This module introduces learners to fundamental concepts of data organisation and storage. It covers key data structures such as arrays, lists, and trees, as well as database management systems. Learners will explore relational databases, SQL, and how to design, create, and query databases effectively. The unit emphasises how proper data structuring enhances efficiency and accessibility in managing large datasets, preparing learners to handle data in real-world applications.
Module 4 - Organisation data This module equips learners with the skills to extract meaningful insights from complex datasets using advanced statistical methodologies. It covers key statistical techniques such as descriptive statistics, hypothesis testing, and correlation analysis. Learners explore data mining and predictive analytics to identify patterns and trends, applying statistical tools like Python and SQL. This unit focuses on how to use these methods to support informed decision-making in data-driven environments.
Module 5 - Legislation and security standards applied to data analytics This module provides learners with an understanding of the legal and ethical frameworks surrounding data usage. It covers key legislation such as the General Data Protection Regulation (GDPR) and other data protection laws, as well as industry-specific security standards. Learners explore best practices for ensuring data privacy, confidentiality, and security in data analytics, focusing on compliance and risk management in handling sensitive information.
Module 6 - Stakeholder engagement and user experience in data analytics This module teaches learners how to effectively communicate and collaborate with stakeholders throughout the data analytics process. It covers techniques for identifying stakeholder needs, translating data insights into actionable recommendations, and ensuring that data-driven decisions align with business objectives. Additionally, the unit focuses on improving user experience by delivering clear, relevant, and user-friendly data presentations and solutions that meet stakeholder expectations.

The HTQ Level 4 Diploma in Data Analysis will provide students with a comprehensive understanding of data collection, processing, and interpretation, preparing them for a variety of roles within the tech and data-driven sectors.

The qualification is broken down into 6 units:

Data fundamentals and lifecycle
Data mining and statistical analysis
Data structure and databases
Organisation data
Legislation and security standards applied to data analytics
Stakeholder engagement and user experience in data analytics

Why do HTQ’s benefit learners?
HTQs can give learners the confidence to be able to acquire the skills prospective employers are looking for. For a wide range of learners they offer considerable flexibility with the opportunity to study part time, with or without an employer. They’re a great way to continue their educational journey, get a good job or learn new skills and move up the career ladder. They also offer a high-quality alternative to other routes, such as apprenticeships, traineeships or degrees.

How can HTQs benefit Employers
Employees who gain these Higher Technical Qualifications can bring a wide range of benefits to any organisation, from boosting productivity and innovation to enhancing employee satisfaction and retention. By investing in a technically skilled workforce, companies can achieve greater efficiency, maintain high standards of quality and safety, and secure a competitive edge in their industry. HTQs are available to existing staff, identify the future managers and data gurus and take advantage of these great qualifications at even better prices.

Simon Gentile

Trainer

Simon joined Fareport Training in November 2024 as an experienced trainer, coach and mentor. He has been working with level 3 and level 4 Data Analyst apprenticeship learners for around 5 years.

Prior to this, Simon has over 10 years practical experience working in Data Analytics in corporations and SMEs.

Simon is currently studying towards his CAVA assessor qualification.

The training sessions are helping my own professional development because I would like to change my career. Iryna

This session has help to have a good introduction to understanding what Data is all about, it usefulness and application, Glad I enrolled. Eniola

Excellent teaching, Simon makes the class very all inclusive and makes sure we’re all following. Very patient and answers questions quickly and with patience with the students. Anna

Q. What does the NCFE awarding body say about HTQs?

Q. What support is available during the course?

Q. What resource materials will be available?

Q. What is the structure of the Data Analyst HTQ?

Q. What are the entry requirements for the NCFE Level 4 Data Analyst HTQ?

Q. How much does it cost to study the Data Analyst HTQ?

Q. How will I be assessed for the course?

Why choose to learn with Fareport Training?

Fareport Training was established in 1981 in order to offer young people a route into work through work based training. In 2014 the business was purchased with support from entrepreneur Theo Paphitis by Natalie Cahill and Marinos Paphitis. Since then we have been building on Fareport’s excellent reputation for high quality training and delivering training and apprenticeships across England. We are proud to offer:

Expert-Led Instruction: Gain insights from industry leaders and seasoned professionals.
Cutting-Edge Curriculum: Stay ahead with the latest trends, tools, and techniques.
Flexible Learning Options: Balance your education with your professional and personal life.

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Customer Testimonials

Real experiences, real success—hear from our learners and employers about how our training programmes have made a difference.

Level 4 NCFE Diploma: Data Analyst

Really helped with understanding data and how I can use it effectively in my current role.