The Level 4 Data Analyst Apprenticeship has been developed to play a significant role in business growth. The primary role of a Data Analyst is to collect, organise and study data to provide business insight. The analysis helps ensure your business stays competitive notwithstanding operational and environmental change. They can predict what the market demands before it happens to provide you with strategic advantages.
Investing in a Data Analyst apprentice will benefit you immediately, but more importantly, it will prepare you for the future. Apprentify sources remarkable data analyst talent for your organisation. Every one of our candidates is assessed on their cultural fit as well as essential skills set, and none are put forward to you without first passing our digital, behavioural and technical tests.
of an apprentice’s hours are all dedicated to the business, with only 20% minimum being set aside for apprenticeship related learning and tasks.
of employers were aware of the Apprenticeship Levy, which leaves 63% unaware that any business (that earns less than £3m) can have most apprenticeship costs offset.
of apprentices chose to or were kept on at the end of an apprenticeship and remained in full-time employment.
of your apprenticeship cost could be covered through the apprenticeship levy.
Throughout the Data Analyst apprenticeship, your apprentice will learn a variety of technical skills and abilities which will greatly benefit them and the business they work for. We teach these mostly through online sessions, where the fresh recruit will find themselves amongst similar apprentices who are learning at the same time.
Not only are the technical abilities learnt an important aspect of any apprenticeship, but also the general skill development of an employee’s recruit. The apprentice’s very own Development Coach is a helpful aspect of our apprenticeship offering. They are available to track progress and provide support, including with Maths and English skills or punctuality.
A Data Analyst apprentice has quite the journey from when they first start with possibly very little skill, all the way to passing their endpoint assessment and having an index of knowledge.
During Unit 1, learners will discover the importance of the business domain context, the principles of user experience and how to use organisational tools, like Trello, OneNote, Gantt charts, STAR technique, Infographics, Version control. They will learn about the principles of what makes a good report and what are the stages of writing it.
During Unit 2, learners will explore the stages of the Data Analytics lifecycle as well as the Data lifecycle and the differences between them. They will recognise the factors of good quality data, learn about types of requirements and how to gather them, Big data and why it is important to understand. Finally, they will be able to identify the functions of data architecture, giving them access to identify their own data architecture used in the workplace.
This unit is spread over 2 months. During Unit 3, learners will begin their journey into data analysis. They will follow the ETL process starting with collecting, integrating, validating and verifying data from multiple sources and in different formats.
During the second month of Unit 3, learners will continue exploring different data structures. They will learn how to filter, clean, transform, manipulate or deal with missing data. The learning will be hands-on, applying all these in many projects, using quantitative and qualitative data.
This unit is spread over 2 months. In the first month of Unit 4, the learners will be introduced to relational databases and NoSQL. They will understand how databases work, will learn about database types, relational models, RDBMS and NoSQL characteristics. They will design databases and then will use SQL Server Management Studio to implement and interrogate databases, using SQL language.
In the second month of this unit, learners will learn about Data visualisation, using Power BI for desktop. Here they will learn how to integrate and transform data and how to generate interactive dashboards for different audiences.
This unit is spread over 2 months. During the first month of Unit 5, learners will explore statistical analysis methods. They will identify different types of analysis, apply Statistics & Hypothesis testing of different scenarios and identify and predict trends and patterns using Machine Learning algorithms like Clustering, Text mining.
In the second month of this unit, learners will continue with Machine Learning algorithms. They will identify and predict trends using the Linear & Logistic Regression algorithms. They will apply these algorithms in many projects using R language. Finally, they will use data sets and job-related scenarios to apply their new skills in the work environment.
This unit is spread over 2 months. In the first month of Unit 6, learners will continue with Machine Learning algorithms - Time Series analysis and forecasting. The goal of these methods is to understand the past trends and to make a forecast for the future. They will learn about other aspects necessary when dealing with Time Series: stationary data, seasonality, autocorrelation.
In the second month of Unit 6, learners will learn about another useful algorithm in Machine Learning - Classification. Finally, for communicating the results of all these data analysis methods, the learners will learn how to share them with internal or external clients. They will be presented methods for summarising and presenting results like dashboards, tailored reports and recommendations.
During this unit, learners will apply everything they have learnt about manipulating and analysing data using another language – Python. They will learn about data types and data structures, data pre-processing with NumPy, data cleaning & pre-processing with Pandas and how to apply Machine Learning algorithms and data visualisation in Python.
Learners will have approximately 4 months to prepare for Gateway. They will consolidate the portfolio that they have built throughout the course.
What I really love about the apprenticeship model with Apprentify is that they have the opportunity to complete that core learning and that it is specialised where needed. If there’s people that have different requirements, then Apprentify will support with that. But also there’s opportunities for that additional learning, which is fantastic.
Karen Rankin
Emerging Talent and Careers Manager at Jet2
Since working with Apprentify we have put a lot of time and investment into existing colleagues who share their aspirations and what they want to do, and if there is anything that we can support them with for their professional development. We utilise apprenticeships in the business massively for existing colleagues.
Gemma Palmer
Head of Early Careers and Apprenticeships at JD Group
The working relationship with Apprentify is fantastic. Very natural, open, and honest. Apprentify took the time to really understand the needs of our business and what is important to us and how we measure success.
Pete Monks
Future Careers Scheme Manager at VMo2
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