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Data & Insights for Business Decisions

Multiverse Data & Insights: data to insights, communication, decision-making, aligned to Level 3 Data Technician apprenticeship.

Updated this week

Data & Insights For Business Decisions Programme Overview

This programme equips employees with the technical and analytical skills needed to turn data into actionable insights, while also building communication confidence through storytelling and presenting findings. It is part of our Data Academy Programmes.

Key Skills Gained:

  • Excel

  • PowerBI

  • Tableau

  • Data analysis

  • Visualisation and reporting

  • Automation processes

  • Data-driven decision making

Business Outcomes:

  • Enhanced decision-making: Empower your team to make data-led decisions with confidence.

  • Improved efficiency: Teams learn how to optimise processes using data, boosting overall organisational productivity.

  • Accelerated growth: Equip your workforce to spearhead data-driven strategies, driving sustainable business growth.

Apprenticeship Qualification Achieved: Level 3 Data Technician

Duration: 13 month delivery, plus 1 month assessment


Data & Insights For Business Decisions Indicative Curriculum Breakdown

Draw insights from data

  • Month 1: Business and data

    • Foundational spreadsheet skills

    • Graph and visualisation types

    • The data lifecycle

    • Exploring BI dashboards

  • Month 2: High-impact problem solving

    • Common data tools and languages

    • Data types and data formats

    • Identifying high-impact data problems, centering the customer/end user

    • Creating visualisations and dashboards in a BI tool

  • Month 3: Data quality

    • Data quality standards & common sources of data quality issues

    • Data cleaning fundamentals

    • Data cleaning vs normalising

    • Cleaning and normalising data in a spreadsheet

  • Month 4: Using and manipulating data

    • Data analysis steps

    • Advanced spreadsheet skills

    • Advanced dashboard skills

    • Integrating data in a BI tool

    • Trend types

    • Best practices for contextualising and interpreting trends

Impactful data applications

  • Month 5: Data analytics hackathon

    • Apply skills learned thus far in a competitive, team-based hackathon

  • Month 6: Measuring and improving impact

    • Calculating ROI for data projects

    • Strategies for communicating impact

    • Pilot projects

    • Technical documentation

    • Continuous improvement process

  • Month 7: Automation

    • Algorithms for automation (decision trees)

    • Automating in a spreadsheet tool

    • Advanced visualisation skills for BI tool

    • Sharing dashboards and data security

    • Automated data preparation for BI tool

  • Month 8: Data visualisation

    • Fit-for-purpose visualisations

    • Interactive and dynamic BI visualisations

    • Building and formatting BI dashboards

    • Communicating insights with UX design principles

    • Accessible design best practices

Build a data-driven organisation

  • Month 9: Data-driven storytelling and decision making

    • Data-driven decision-making

    • Stakeholder analysis

    • Data formats and implications for data analysis

    • Identifying and mitigating bias in data analysis

    • Stakeholder-driven presentation techniques and data storytelling best practices

  • Month 10: Change agent incubator and EPA readiness session

    • Becoming a change agent

    • Spheres of influence

    • Ripple effect

    • Four building blocks of change

    • Knowledge sharing

  • Month 11: Change management masterclass

    • Types, scopes, and depths of change

    • Influencing behaviour: ability and motivation

    • The six sources of influence

    • Empathy mapping

    • Adapting approaches for inclusivity

    • Persuasive communication

  • Month 12: Staying relevant

    • Big data

    • Machine learning

    • Generative AI

    • Elective topic (SQL, Python, blockchain, or NLP)

    • Professional development

  • Month 13: End point assessment (EPA) preparation

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

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


Data & Insights For Business Decisions Indicative Delivery Model

Monthly delivery model, approx. 26 hours per month total commitment. The exact time commitment will be outlined in the training plan that apprentices will receive at the start of their apprenticeship.

  • Structured Learning (~35% - 9 hours/month):

    • Live group learning (3 hours): Instructor-led, small-group interactive learning that dives deeper and reinforces the asynchronous content.

    • Asynchronous learning (4 hours): Online, self-paced content that sets the foundation of skills for the module.

    • Coach and peer support (1-2 hours): Includes tutoring, progress reviews, and other individual/group/peer support.

  • Working in Existing Role (~65% - 17 hours/month):

    • Tasks & applied learning (17 hours): Structured and unstructured application of learning to apprentices’ roles.


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