Course Code: IN00009 Data Analyst - Level 4 Higher Apprenticeship Duration Day/s of weekBy arrangement Time - Next course dates Start dateLocationDuration Anytime University Centre Enquire now Overview Is this course for me? What will I learn? How will I be assessed? Key information Where could this course take me? Course SummaryThe Data Analyst Apprenticeship is a Level 4 programme designed to develop data professionals with the skills and knowledge employers need to make data-driven decisions, enhance business operations, and foster innovation. This comprehensive training programme equips apprentices with practical experience and a strong theoretical foundation in data analysis, enabling them to effectively contribute to their organisations. Benefits to Employers: Talent Development: Cultivate a skilled workforce capable of driving data-driven decisions and innovations. Cost-effective Training: Access to government funding, reducing training costs and maximising ROI. Customisation: Tailor the apprenticeship to address specific organisational needs and skill gaps. Staff Retention: Improve employee satisfaction and loyalty through investment in their professional development. Increased Productivity: Enhance business performance by enabling data-driven decision-making and problem-solving. In summary, the Level 4 Data Analyst Apprenticeship offers a comprehensive and employer-focused training programme, providing apprentices with the skills and knowledge needed to excel in data-driven roles. Employers benefit from cultivating a skilled workforce capable of leveraging data to drive business performance and innovation, while also improving staff retention and satisfaction. Entry Requirements Data analysts will typically work across multiple projects to collect, organise, cleanse and study data. They provide your senior stakeholders and management with insights that support better decision making, enabling your organisation to respond faster to market trends. With the proliferation of real-time data, your analysts can better understand trends which have an effect on your business. In addition, this can help your organisation to predict demand, costs and revenue, while identifying risks and opportunities. English and 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 Qualification ObtainedBSc (Hons) Network Engineering (Cyber Security) Entry Requirements Admission to level 4 would normally be on the basis of the applicant possessing: A minimum of 96 UCAS points in an appropriate discipline Applicants who are able to demonstrate relevant work/life skills or knowledge will also be considered on an individual basis Applicants must also be actively employed within an appropriate setting in a relevant sector Those applicants who do not hold GCSE Maths / English at C, or equivalent qualifications, will be supported to undertake Maths / English qualifications alongside the main programme. Learning and Teaching Methods Apprentices will gain expertise in the following areas: Data Analysis Tools: Proficiency in industry-standard software, such as Excel, SQL, and R or Python. Data Management: Understanding of data architecture, data quality, and data protection principles. Data Visualisation: Ability to create clear and compelling visual representations of data to inform decision-making. Statistical Techniques: Familiarity with descriptive and inferential statistics, hypothesis testing, and predictive modelling. Domain Knowledge: Acquiring sector-specific knowledge to contextualise and interpret data effectively. Problem Solving: Developing analytical and critical thinking skills to address complex business challenges. Communication: Strong written and verbal communication skills to present data insights to non-technical stakeholders. This online course offers flexible learning, with monthly sessions covering essential data analysis skills. Interactive virtual classes, led by industry experts, promote engagement and collaboration. A blend of live sessions, self-paced activities, and practical assignments ensures a comprehensive learning experience, catering to diverse learning styles and busy schedules. Expert Tutors All staff involved in the delivery of adult education courses within the College are approved to teach the subjects and modules they deliver. The approval process ensures that staff delivering a given programme are appropriately qualified and, where appropriate, possess relevant technical and industrial experience and professional practice. Assessment MethodsAssessment in this course involves both formative and summative components. As you progress through the modules, formative assessments will measure your understanding, while you also compile a portfolio based on delivered content. Upon completion, you'll enter the End-Point Assessment (EPA) phase with BCS. Assessment Method 1, Component 1 focuses on a Data Analysis Project, while Assessment Method 2 consists of a Professional Discussion supported by your portfolio, ensuring a comprehensive evaluation. Link to further information :- https://www.instituteforapprenticeships.org/media/5154/st0118_data-analyst-_l4_ap-for-publication_20210602.pdf Other Costs and Equipment NeededThis programme costs £15,000 – all covered through the Apprenticeship Levy. Even if employers don’t pay into the Levy, they will only pay 5% of the full price, with the remaining 95% being paid for by the Government. Key Points Level 4 Data Analyst Apprenticeship: This comprehensive training programme is aimed at developing skilled data professionals, providing them with practical experience and a strong theoretical foundation in data analysis. Online, flexible learning with monthly sessions: The course is delivered through online monthly sessions, offering convenience and flexibility for learners. Virtual classes are led by industry experts and promote engagement and collaboration. Formative assessments and portfolio development: Throughout the course, learners are formatively assessed to track their progress. They also compile a portfolio to showcase their work and learning experiences. End-Point Assessment (EPA) with BCS: Upon completion, learners enter the EPA phase conducted by the British Computer Society (BCS), ensuring a high standard of evaluation. Data Analysis Project and Professional Discussion: The EPA includes two assessment methods: a Data Analysis Project (Component 1) and a Professional Discussion supported by the learner's portfolio (Method 2). Government funding eligibility: The course is eligible for government funding, helping employers to reduce training costs and maximise their return on investment. Employer-focused, tailored programme: The apprenticeship is designed to meet the specific needs of employers, allowing them to address organisational skill gaps and enhance their workforce's capabilities. Enhances data-driven decision-making skills: Learners acquire skills in data analysis tools, data management, data visualisation, statistical techniques, problem-solving, and communication, enabling them to make data-driven decisions that improve business performance and innovation. Career Options and Progression The Data Analyst Apprenticeship equips learners with the skills and knowledge to excel in a variety of data-driven roles. Some potential career options and progression paths include: Data Analyst: Analyse, interpret and visualise data to inform decision-making, identify trends, and solve business problems Business Intelligence Analyst: Transform raw data into actionable insights, helping organisations improve performance and achieve their strategic goals. Data Scientist: Apply advanced statistical techniques and machine learning algorithms to uncover patterns, make predictions, and drive data-based innovations. Progress within the current organisation: Graduates can leverage their newly-acquired skills to advance in their existing roles, take on increased responsibilities, or transition to data-focused positions within their organisation. Explore new opportunities: Armed with relevant skills and experience, learners can seek new challenges and roles in other organisations, sectors, or industries. Further education and certifications: Graduates may choose to pursue higher education or additional qualifications, such as a master's degree in data analytics, a professional certification in data science, or specialised training in big data, machine learning, or artificial intelligence. Overall, the Data Analyst Apprenticeship lays a solid foundation for a successful career in the rapidly evolving world of data, providing learners with ample opportunities for growth and development.