This module develops an understanding of how data is generated, managed, and used within organisations to support decision-making. In contemporary business environments, organisations operate as data-driven enterprises, requiring graduates who can move beyond technical analysis to interpret, apply, and communicate data within real organisational contexts. The module addresses this need by integrating principles of business information management with applied analytics, including data governance, enterprise systems, and the role of data in digital transformation. It equips students with the ability to understand how data flows across business functions, supports managerial decision-making, and must be used responsibly and ethically. As such, the module provides a critical bridge between quantitative skills and their application in practice, preparing students for further study and data-informed roles in modern organisations.

Organisations as data-driven enterprises; the strategic importance of business data in supporting evidence-based decision-making across business functions; understanding how business data is generated through organisational processes and how it flows across functional areas and systems; the role of enterprise systems in integrating data and supporting operational and managerial decision-making; principles of data quality and data governance, including accuracy, consistency, completeness, stewardship, and organisational responsibilities for managing data; ethical and legal considerations in the use of business data, including privacy, consent, GDPR, algorithmic fairness, and the wider societal implications of data-driven decision-making; the application of analytics in business contexts, including how data is used to support decision-making, identify patterns, and generate insights; integrating and combining information from multiple data sources to support problem-solving and managerial judgement; interpreting trends and patterns in business data within organisational contexts; principles of effective data visualisation and communication for decision-making, including clarity, integrity, appropriate chart selection, and the development of dashboards to support managerial insight; communicating analytical outputs through structured summaries, tables, visualisations, and short data-driven narratives for different stakeholders; the role of digital tools (particularly spreadsheet applications) in supporting data organisation, integration, analysis, and reporting across business domains; the role of data and analytics in digital transformation and the increasing importance of data as a strategic organisational asset. These concepts will be reinforced and developed through applied data analysis and problem-solving exercises completed during scheduled computer laboratories, with a focus on interpreting and using data in realistic business scenarios.

On successful completion of this module, students will be able to: 1. Identify and describe the fundamental concepts, sources, and structures of business data within organisational contexts. 2. Explain how business analytics supports evidence-based decision-making across key business functions. 3. Discuss data quality, governance, privacy, and ethical considerations relevant to the collection and use of business data. 4. Apply appropriate data organisation, graph construction, and calculation operations to support mathematical and statistical analysis. 5. Operate relevant spreadsheet functions to analyse data and inform business decisions.

On successful completion of this module, students will be able to: Demonstrate responsible data use by integrating ethical, legal, and governance considerations into analytical work.

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The module is delivered through a combination of lectures and scheduled computer laboratories. Lectures introduce theoretical concepts supported by contemporary research in business analytics, digital transformation, decision science, visualisation, and data ethics. Practical laboratory sessions enable students to apply these concepts using spreadsheet software to organise, prepare, summarise, and visualise data for managerial decision-making. Teaching is informed by current developments in analytics practice, including emerging trends in data governance, responsible data use, algorithmic fairness, and the evolving role of data in organisational decision-making. Examples and datasets drawn from industry and public sources are used to contextualise analytical techniques within real-world business scenarios. Active learning, applied problem-solving, and scaffolded skill development ensure meaningful integration of theory and practice throughout the module.