Data Technician

Course details

Level

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Level 3

Duration

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13 months

One-to-one support

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Every 4 weeks

You will achieve

Level 3 Data Technician
BCS

Common job roles

  • Data technician
  • Data support analyst
  • Junior data analyst
  • Junior information analyst

Roles you may progress into

  • Data manager
  • Data scientist
  • Data engineer

Delivery of programme

Phase one

Pre-Induction

Before your induction we’ll take you and your employer through the apprenticeship standard and discuss your job role. You’ll also begin your personalised Vocational Scorecard, which assesses your current skill level so that we can develop an individual learning plan tailored to your needs.

Induction

Your induction will take place within the first two weeks of starting your employment. You’ll be taken through the dedicated support available to you throughout your learning journey and will be introduced to our Virtual Learning Environment and online portfolio platform.

Functional skills

We use BKSB tests to determine your current level of knowledge in English and/or Maths. If you require Functional Skills training you’ll undertake 3 remote sessions and workshops before sitting an exam.

Phase two

Core modules

The first 7 months of the level 3 Data Technician programme is made up of core modules. Once the core modules are complete you can then specialise on one of our three specialist pathways.

Essential mathematics skills to reach a minimum required standard for data analysis.

In this preparatory module, learners will learn fundamental professional skills, for example working in a team, communication skills and how to deal with customer issues. These skills will then be applied throughout the apprenticeship in ‘real-life’ scenarios. Learners will be presented with different learning techniques, assessing their own learning style and explore ways to improve it.

In this module, learners will learn about different data sources of data in the digital world and how to recognise types of data, for example structured and unstructured, numerical and categorical data. They will learn about data legislation and regulation, including creation and the use of open, public and proprietary data and GDPR rules. After this module learners will be ready to recognise and use different types of files like json, xml, bak etc.

In this module, learners will discuss different features of quality data. This is necessary when identifying sources of data and establishing whether is it reliable or fit for the purpose. They will learn how to integrate data from different formats, as well as transform, prepare and work with data. Finally, they will learn how to present data using Exploratory Data Analysis methods.

This module will include the use of advanced formulae in Excel and the creating and analysis of pivot tables. Learners will learn how to clean data, handle missing data, perform descriptive analysis and effectively report the results. Along with these technical skill, they will acquire soft skills like communication, time management and working in a team.

In this module, learners will recognise and use quality data from different sources and integrate them together, applying Extract-Transform-Load methods in Power BI. They will follow the data analytics life cycle to prepare the data, transform it to be fit for purpose and to create reports and interactive dashboards. They will also model the data using drilling down /up, filters, slicers and DAX language.

In this module, learners will create new databases, integrate data from different formats, transform, and prepare data using a SQL server. They learn how to design, normalise and interrogate a database, as well as how how to normalise it and how to interrogate it.

In this module, learners will continue to work in SQL Server, using some advanced features like aggregate functions, views, and stored procedures. They will apply the communication and presentation skills they’ve developed using the results from the projects

Specialist pathways

Pathway 1: Excel

In this unit, more advanced topics are presented data structures, sub setting, imputing and normalising data using Excel (VBA & macros).

In this module, we discuss about basic statistics and descriptive methods, applied in Excel.

Using Excel, in this module, learners will use all the knowledge, skills and behaviours acquired in the previous months in projects created especially for them. They can combine using Power BI, Excel or even SQL Server to prepare the data and then can use a language like R or Python for performing some data analysis tasks. They have the opportunity to use and practice skills like collaboration, communication, writing reports and presenting the results.

Pathway 2: R

In this unit, more advanced topics are presented data structures, sub setting, imputing and normalising data using R and R Studio.

In this module, we discuss about basic statistics and descriptive methods, applied in  R. Also, all the methods used in the core modules about cleaning and preparing data will be re-introduced using R.

Using R, in this module, learners will use all the knowledge, skills and behaviours acquired in the previous months in projects created especially for them. They can combine using Power BI, Excel or even SQL Server to prepare the data and then can use a language like R or Python for performing some data analysis tasks. They have the opportunity to use and practice skills like collaboration, communication, writing reports and presenting the results.

Pathway 3: Python

In this unit, more advanced topics are presented data structures, sub setting, imputing and normalising data using Python

In this module, we discuss about basic statistics and descriptive methods, applied in  Python. Also, all the methods used in the core modules about cleaning and preparing data will be re-introduced using Python.

Using Python, in this module, learners will use all the knowledge, skills and behaviours acquired in the previous months in projects created especially for them. They can combine using Power BI, Excel or even SQL Server to prepare the data and then can use a language like R or Python for performing some data analysis tasks. They have the opportunity to use and practice skills like collaboration, communication, writing reports and presenting the results.

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One-to-one support

Your Technical Trainer and Progress Management Co-ordinator (PMC) will be on-hand to support you throughout your apprenticeship. Your PMC will contact you every 4 weeks to discuss your progress made to date and your Technical Trainer will work with you to set and support you with your projects. Once your training is complete, a dedicated EPA facilitator will help get you prepared for End Point Assessment.

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Your portfolio

Throughout the apprenticeship, you will contribute evidence towards your online e-portfolio. We use e-portfolios as they are accessible from anywhere, and enable you to track your progress throughout your apprenticeship. You’ll have access to your personal dashboard to monitor your progress and identify any gaps in your portfolio of evidence.

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Off-the-job training

Off-the-job (OTJ) training is comprised of, but not limited to activities such as: training with Estio, shadowing, journal entries and projects for e-portfolio. Completed within working hours as agreed with the employer but average at 6 hours per week (20% of your time on your apprenticeship). You can track your OTJ progress on your e-portfolio.

Phase three

Assessment Gateway, preparation & administration week

The Gateway week is used to finetune your skills and offer a simulated Synoptic Project for systems familiarisation, and to ensure that your Summative Portfolio and Employer Reference are completed before entering into EPA.

Phase four

End Point Assessment

You will be assessed by an End Point Assessment Organisation, chosen by your employer. This independent assessor will feedback the results (Pass, Merit or Distinction) and the ESFA will provide your certificate.

Where can this apprenticeship take you?

The Data Technician standard will give you the skills and experience to work as a data technician, data analyst, network technician, systems administrator or a business analyst. Over the course of your career you can then become a senior expert in one of these fields.

To further your education within this industry, we recommend that you progress onto a Level 4 Data Analyst apprenticeship to further your knowledge and experience.

Level 4 Data Analyst roles

Data Analyst, Data Manager, Data Scientist

You can find out more about our level 4 Data Analyst role by clicking here.

Alternatively more information can be found on the institute for apprenticeships website.

Get in touch!

Call our team on 01133 500 333 or fill out our enquiry form below