Junior Data Analyst Apprentice Level 3

Duration: 24 months

JGA’s new Junior Data Analyst apprenticeship programme for sales & marketing teams utilises a brand new level 3 apprenticeship standard (Data Technician) and represents a way to support sales and marketing teams’ increasing need to be comfortable with data-driven tools and techniques.

In a world full of databases, CRMs and marketing automation systems, 62% of members of the Data & Marketing Association (DMA) already use apprenticeships in some form. This standard is an opportunity to make sure that these apprenticeships are focused on the data-oriented needs of the sales & marketing teams.

The apprenticeship is suitable for business-to-business, business-to-consumer and business-to-government sales and marketing entry-level data focused roles.

Typical job titles might include Junior Information Analyst, Marketing Data Specialist/Coordinator, Data Technician, Database Technician, Data Support Analyst.

JGA offers a full suite of commercial apprenticeships. Marketing-related apprenticeship clients range from FTSE corporates Homeserve Plc and Kuehne & Nagel, to West Midlands Combined Authority and Pension Protection Fund and specialist agencies such as Blackrook Media and Predictable Marketing.

This apprenticeship is designed for on-programme apprentices to be eligible for Associate Membership of the Institute of Data & Marketing.

Course Content

Personal development, review of data types and purpose of holding and utilising data. Describing data in a sales and marketing context and how data adds value to the organisation in general and the sales and marketing function in particular.

The types and sources, formats and architecture of data. Access and extraction of data and the role of data in a complex digital world.

Data storage methods. The impact of data protection legislation on data storage conditions. Analysing the organisational and regulatory approaches of sharing data and reviewing other legal requirements, such as intellectual property rights and the ethics of data usage. 

How to collate, cleanse and format data in line with industry standards. Data cleansing and example tools such as OpenRefine. Industry trends and formatting tools such as Excel, Access, CRM systems, Google Analytics and marketing automation systems such as Hubspot, Adobe, Oracle, Salesforce, Marketo, Communigator and others.

Presenting data for review and analysis by others, using a range of formats, media and methods of communication. The importance of collaborative working. Assessing the different formats and techniques used for communication. Analysing the different communication needs for internal and external stakeholders/customers.

Explaining data and interpretation, preferred ways of presenting results. Developing a thorough and organised approach. learning to work independently and use initiative. Learning to value difference and diversity and to be sensitive to the needs of others.

Blending data sets from multiple sources and present in format appropriate to the objective. Manipulating and linking data sets. Using tools and techniques to identify data trends and patterns. Cleaning data i.e. removing duplicates, typos, outdated data, parse data (e.g. format telephone numbers according to a national standard) and test and assess confidence in the data and its integrity.

Algorithms, and how they work. Using a step-by-step solution to a problem or rules to follow to solve the problem and the potential to use automation. How to filter details, focusing on information relevant to the data project. Basic statistical methods and simple data modelling to extract relevant data and normalise unstructured data.

Tools and techniques to identify faulty results and support quality. The range of common data quality issues e.g. misclassification, duplicate entries, spelling errors, obsolete data, compliance issues and interpretation/translation of meaning. Different methods of validating data and the importance of taking corrective action. Application of cross checking techniques for identifying faults and data results for data project requirements.

Operating as part of a multi-functional team. Prioritising within the context of a project. Working independently and taking responsibility. Understanding the significance of customer issues, problems, business value, brand awareness, cultural awareness/ diversity, accessibility, internal/external audience, level of technical knowledge and profile in a business context. Demonstrating different ways of communicating meaning from data in line with audience requirements. Producing clear and consistent technical documentation using standard organisational templates. Explaining data and results to different audiences in a way that aids understanding. Keeping up to date with developments in technologies, trends and innovation using a range of sources. 

Delivery Model

The course is delivered through once monthly, digitally-led, full day seminars plus coaching from a sales and marketing data professional as well as additional online resources. We deliver nationally.

All teaching is presently delivered remotely and there is an active programme of starts despite Covid-19.

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