DIBD - Curriculum Deep Dive | Multiverse Help Center

Module Title	Module Description	Units	Learning Outcomes	Project Value
Module 1: Business and Data	Apprentices will investigate the value of data in the business and how it is used to solve business problems in different roles and functions. They will learn fundamental data analysis skills and start practising answering business questions using data with a Business Intelligence tool.	Commercial Awareness	Review your own development needs and apply a growth mindset to achieve your goals Develop your professional network by meeting apprentices on the programme Apply different learning techniques to access different sources of knowledge Understand the importance of data to businesses, driving business value and brand awareness Describe how the Data Lifecycle is relevant to the work you do Review and apply foundational Excel skills to data sources Describe when to use different graphs and visualisations Explore a BI dashboard created to solve a business problem Collect, format and save datasets Collate and format data in line with industry standards	In this foundational module, apprentices will engage with a team member to understand your organization’s data culture. They will identify a business problem that can be addressed through data, aligning personal development goals to enhance their impact throughout the apprenticeship. This project fosters a strong foundation in data-driven problem identification and personal goal setting, benefiting both the apprentice’s growth and the organization’s strategic data use.
Module 2: High-Impact Problem Solving	Apprentices will build on the previous module by learning problem-solving frameworks such as resulting impact frameworks to identify and execute high-impact opportunities to use data. In addition, they will learn important data structure foundations and data security principles to ensure they can collect, store, and use data competently and securely in spreadsheets and BI tools.	Data Management High-Impact Problem Solving	Explain the difference between on-premises and cloud storage and critically analyse when businesses should use each Explain the legal and ethical requirements for storing, managing, and distributing data. Understand common data vocabulary terms in order to describe data problems Explain the purpose and functionality of a BI tool Use a BI tool to build visualisations Use a BI tool to build interactive dashboards Describe different stakeholders that might work on a data project Choose communication methods based on stakeholder preference Employ an ROI framework to identify high-impact projects to work on Define ROI and identify high-impact projects	Apprentices will apply problem-solving frameworks to refine their data project plans, evaluating the organization’s data architecture and sourcing valuable data. This ensures that the data projects are clearly defined and strategically aligned with business goals from the outset. It will enable better prediction and potential optimization of business outcomes.
Module 3: Data Quality	Most organizations fail to utilize data to solve business problems because of poor data quality. In this module, apprentices will learn the best practices for validating and cleaning data to ensure data integrity, enabling them and their organizations to use data to solve impactful business problems.	Data Quality Data Integrity	Understand the importance of using quality data. Identify good quality data and poor quality data using key terminology. Critically analyze how to identify and solve data quality issues Validate data using a spreadsheet tool, including shortcuts and best practices. Understand the importance of validating and auditing data. Document your cleaning and normalization process Understand the purpose of data normalization. Clean and normalize large data sets Apply time management and prioritization skills in order to complete high-priority work Identify personal time management challenges.	Apprentices will enhance their data project by developing and implementing a robust data validation plan, ensuring data accuracy and reliability. This module will culminate in critical insights that feed into broader business objectives, ensuring that your organization's data projects are built on solid foundations.
Module 4: Using and Manipulating Data	Apprentices will learn data analytics techniques such as Pivot Tables and apply them to analyse complex structured and unstructured data and drive business outcomes. In addition, they will learn to blend data from multiple sources to create an integrated dataset for deeper analysis.	Data Analytics Data Integration	Evaluate the impact of data analysis on business outcomes Interpret trends, patterns, and outliers to generate insights from data visualizations Apply advanced spreadsheet functions to analyze data Evaluate the impact advanced spreadsheet functions have on data analysis Analyze data visualizations for trends, patterns, and outliers Describe how to identify and interpret trends in visualizations Interrogate business problems using the 4D Audience Framework Integrate and visualize data in a BI tool for analysis	Focusing on actionable steps, apprentices will lead initial data analyses to derive significant insights from your data. They will explore how these insights can inform strategic decision-making and predict the impact on business outcomes. This module ensures that the apprentice’s work directly translates to tangible business improvements.
Module 5: Data Analytics Hackathon	In this capstone module, apprentices will advance the business and data skills they have learned in the previous modules by applying them in teams to develop insights from a real-world scenario - it is a competition!	Data Analytics Hackathon	Define a problem statement from a real-world scenario Prepare and clean the accompanying data Analyze the data and produce reports and/or visualizations of findings in a BI tool Prepare and present findings to a panel of judges	Through a series of scenario-based tasks, apprentices will demonstrate their competencies in data integrity, analytics, and integration. This provides a rigorous test of their skills and prepares them for real-world data challenges, ensuring they are well-equipped to deliver substantial value to your organization.
Module 6: Measuring and Improving Impact	Apprentices will reconvene to evaluate their project progress by learning and applying an impact quantification framework. They will then learn techniques to improve the impact of their project, for example, by adding data sets and removing noisy attributes. In addition, apprentices will learn how to communicate their project progress impact to stakeholders.	Business Impact	Quantify the impact of data projects by calculating Return on Investment (ROI) Plan project impact in order to properly quantify it Communicate the impact of data projects using visualizations Communicate your business impact by drafting impact statements Critically analyze project outcomes to identify how to improve their impact Apply technical skills to improve the impact of data projects Identify opportunities to use technical documentation to improve business processes Apply best practices for technical documentation to log project improvements.	Apprentices will focus on assessing and amplifying the impact of a chosen project or task. They will communicate improvements to their manager, ensuring that their efforts are effectively aligned with the organization’s strategic objectives. This continuous improvement approach benefits both the apprentice and the organization by driving performance and effectiveness.
Module 7: Automation	Apprentices will learn algorithms and apply them to streamline and automate manual processes in their current roles and/or manual data analysis performed in previous modules. Apprentices will use tools such as Flow diagrams, Macros, and a BI workbook to improve the efficiency and precision of their work.	Algorithms	Identify use cases for automation across the data lifecycle Describe how algorithms can be used for the automation of manual processes Justify why algorithms are used to automate data processes Identify opportunities for automation within your role and organization Build decision trees in order to identify opportunities for automation Apply automated BI functions to identify trends and patterns in data Quantify the direct impact resulting from automation Apply Macros to automate data processes in a spreadsheet tool Automate data cleaning, transformation, and calculation using a BI tool	Apprentices will introduce automation to a manual process from a previous project, measuring and communicating its impact. This project's objective is to increase operational efficiency, reducing manual effort and enhancing accuracy, thus driving significant productivity gains for your organization.
Module 8: Data Visualization	In this module, apprentices will learn how to visualize data analysis results in the form of sophisticated, user-centred dashboards built using a BI tool to convert reports into insights and facilitate team’s decision-making.	Data Visualization	Describe methods for visualizing data analysis results in a BI tool Describe how advanced, user-centered dashboards facilitate decision making Apply best practice to create highly effective data visualizations in a BI tool Describe how advanced, user-centered dashboards facilitate decision making Critically evaluate dashboard visualizations to strengthen analysis Build advanced, user-centered dashboards in a BI tool Explain the results of gathered data Identify trends and patterns in data Describe accessible design principles for visualizations Justify the importance of accessible design for data visualization	Focusing on creating a sophisticated, user-centered dashboard, apprentices will measure and communicate the business impact of this tool. This module emphasizes the importance of intuitive data presentation, enhancing decision-making capabilities at all organizational levels and empowering stakeholders with actionable insights.
Module 9: Data-Driven Storytelling & Decision-Making	Apprentices will practice storytelling using data by learning to tailor their insights for different audiences. Apprentices will learn to draw the right insights from their dashboards by learning how to avoid common decision-making pitfalls and check the accuracy and the impact of their conclusions. Apprentices will learn to shape strategic business decisions through compelling narratives and create a culture of decision-making based on unbiased and objective analysis.	Data-Driven Storytelling Data-Driven Decision-Making	Tailor insights from data analysis for stakeholder needs Describe data-driven storytelling best practices Describe the importance of different data formats for analysis Justify why different presentation tools are used to present data for different stakeholders Evaluate data analysis for bias and propose bias mitigation strategies Describe data-driven decision making best practices Apply methods for communicating meaning from data analysis results to support audience understanding and decision making Analyse stakeholders to inform data-driven decision making and storytelling	Apprentices will revisit and improve a previously developed dashboard, focusing on bias reduction and stakeholder-specific storytelling techniques. This module ensures the dashboard is not only accurate but also compelling and tailored to drive better decision-making across various organizational levels.
Module 10: Change Agent Incubator & EPA Readiness Session	This full day session will empower apprentices to use their newfound data expertise to emerge as leaders among their peers and drive stronger team performance. Apprentices will ideate different approaches to share data tools and best practices and end the session with an actionable, personalized plan to implement on the job. Finally, apprentices will end the day preparing for the Professional Discussion of their End Point Assessment.	Change Agent Incubator EPA Readiness Session	Describe best practices for influencing change Evaluate your ability to influence change on your team or organization Evaluate your team and organisational context to identify data skill or knowledge gaps Evaluate data tools, skills, and best practices to determine their applicability and effectiveness in your specific team and organisational context Develop innovative strategies for sharing data tools and best practices Develop a comprehensive change agent plan to implement data-driven strategies across your team or organisation Describe the expectations for the End Point Assessment Describe the structure and expectations of the Portfolio & Professional Discussion assessment method Describe Portfolio & Professional Discussion best practices Evaluate professional discussion responses and portfolio evidence Identify evidence of standards in existing projects Justify evidence of standards in a mock Professional Discussion Evaluate Professional Discussion responses and Portfolio evidence against evaluation criteria Propose improvements to Professional Discussion responses and Portfolio evidence against evaluation criteria	Apprentices will draft and refine plans to advocate for the adoption of a data tool or skill, receiving managerial feedback. This module fosters a data-positive culture within your organization, promoting the widespread use of data-driven tools and techniques to enhance overall operational effectiveness.
Module 11: Change Management Masterclass	Technical skills alone will not drive business value. Apprentices must navigate organisational culture and interpersonal challenges inherent in championing the new, data-driven way of working to drive large-scale impact. In this module, apprentices will learn to influence through empathy and lead confidently through role plays and case studies. Apprentices will also learn relevant social science concepts such as authority, social proof, and similarity, which will increase their effectiveness as a change agent. After learning these valuable skills, apprentices will evaluate their progress as change agents and strategise to amplify their impact.	Organizational Behaviors	Describe change management best practices Evaluate change management strategies and propose improvements Apply social science concepts to change management strategies Identify solutions for common change management challenges Adapt strategies to meet the needs of different stakeholders (i.e. customers, managers, clients and peers) Apply persuasive communication techniques to influence others Describe empathy-driven strategies to influence behavioral change	Building on the previous project, apprentices will apply change management techniques to champion data tools or skills. This ensures effective stakeholder engagement and broad adoption across the organization, solidifying the data culture and driving measurable improvements.
Module 12: Staying Relevant	As they near the end of their apprenticeship journey, apprentices will be introduced to cutting-edge trends such as Machine Learning, Big Data, and Generative AI, evaluating how these trends can impact their roles in the future. Apprentices will plan their post-programme career paths and map out resources that can help them to stay relevant.	Digital Trends	Describe Big Data and evaluate how it fits into an organization's data architecture Describe opportunities provided by Machine Learning and cloud technologies Identify strategies to avoid ethical dilemmas when engaging with artificial intelligence Describe generative artificial intelligence and identify its use cases across the data analysis lifecycle Critically evaluate new technologies and innovations against ethical considerations Explore an emerging data skill and identify opportunities for application Develop professional development plans aligned to individual post-program career paths	In this culminating project, apprentices will explore new technologies to enhance past data projects and set professional development goals. This forward-looking approach ensures that both the apprentice and your organization stay ahead in the rapidly evolving digital landscape, continuously leveraging new tools for enhanced business performance.
Module 13: EPA Prep: Final Session	In this final, full day session, apprentices will wrap up their apprenticeship program by preparing for their End Point Assessment. The session will include key skills review, Portfolio refinement, mock Professional Discussion and Scenario Demonstration practice, and key logistics for their upcoming gateway meetings.	EPA Prep: Final	Describe the characteristics, logistics, and components of each End Point Assessment method Build a first draft of the final portfolio Assess understanding of key KSBs Improve understanding of key KSBs Practice defending the portfolio through a mock Professional Discussion Practice demonstrating the data gathering and analysis skills through a mock Scenario Demonstration Describe gateway and EPA logistics and top tips	None.

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