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Digital Business Accelerator

Multiverse Digital Business Accelerator: business analysis, data skills, productivity, aligned to Level 3 Data Technician apprenticeship.

Updated over a week ago

Digital Business Accelerator Programme Overview

This programme equips junior talent with the business analysis and data skills needed to drive meaningful business impact. It builds foundational skills to strengthen early talent retention, increase productivity, uncover cost-saving opportunities, and increase profitability. It is part of our Data Academy Programmes.

Key Skills Gained:

  • Data in business

  • Project management

  • Business intelligence

  • Communicate effectively

Business Outcomes:

  • Increase retention: Equip apprentices with the tools and coaching to support their long-term professional development.

  • Increase productivity: Provide easy access to clean, structured data that can be utilised by the business.

  • Increase profitability: Equip junior team members with core skills to project manage key initiatives, saving senior team members' time.

  • Identify cost-saving opportunities: Reduce manual analysis and utilise data to make business decisions.

Apprenticeship Qualification Achieved: Level 3 Data Technician

Duration: 12 month delivery, plus 2-3 month assessment


Digital Business Accelerator Indicative Curriculum Breakdown

Business and data fundamentals

  • Module 1: Personal power

    • Introduction to the module project and project writing 101

    • Industry and role awareness

    • Personal power and knowing your why

    • Taking initiative and managing upwards

  • Month 2: Business fundamentals

    • The role of data in decision making for internal stakeholders and customers

    • How data is stored, shared, and saved in compliance with organisational policy

    • Format a raw dataset in Excel

  • Module 3: Data in business

    • Foundations of project work: communication for stakeholder expectation setting and project scoping

    • The importance of data quality

    • Assessing the quality of data

    • Data cleaning in Excel

  • Module 4: Data proficiency

    • Describe trends in Excel data using simple formulas, filters, formatting, tables, and statistical analysis

    • Create and analyse data visualisations in Excel and Power BI

    • Task prioritisation, stakeholder management, and upward communication

Project management and communications

  • Module 5: Communicating effectively

    • Storytelling and influencing techniques to communicate data insights

    • Present data narratives to various types of stakeholders

    • Utilise accessible design principles for all visualisations and presentations

  • Module 6: Portfolio development and end point assessment (EPA) preparation

    • Working session to learn more about the EPA, practice for the interview, and work on evidence

  • Module 7: Project management - The Principles

    • Describe how to run a project against a clear timeline

    • Understand how to identify and communicate with stakeholders throughout a project

    • Use automation to make data work more efficient

  • Module 8: Project management - Data Projects

    • Manage change for data and support stakeholders through project-related changes

    • Normalise data

    • Use data modelling techniques to analyse large datasets

    • Regulatory requirements for data management

  • Module 9: Project delivery

    • Measure and communicate the impact of data projects

    • Evaluate and measure project outcomes, effectively conveying project impact

    • Create interactive visuals in Power BI to communicate data narrative

Decision making with data

  • Module 10: Business intelligence

    • Prepare, analyse, and visualise data in Excel and Power BI

    • Link data skills learned thus far, working end-to-end to take a raw dataset and turn it into insights and recommendations that can influence decision making

  • Module 11: Insights and decisions

    • Understanding IoT, big data, cloud, and machine learning

    • How these technologies relate to your organisation

    • Staying up to date with trends in data

    • The effectiveness and ethics of big data and machine learning

  • Module 12: Gateway and end point assessment (EPA) preparation

    • Apprentices are reaching the end of their apprenticeship programme and will be completing their End Point Assessments (EPA).

    • This module will ensure they are fully prepared to be successful in the EPA.

Note: This is an example curriculum, and specific details may vary per cohort.


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