Analytics Fundamentals Training

This analytics fundamentals training course provides core knowledge about analytics, and how to successfully work with analytics in an organisation.

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      The purpose of the Analytics Fundamentals course is to provide attendees with a common foundational knowledge about data and analytics generally, and how to implement analytics within their organisation.

      After completing the course all attendees will have a common understanding of key analytics terms, what analytics is, how analytics used in organisations, and what leads to a successful analytics implementation.

      Key Topics

      • Analytics and the Business Landscape
      • Data-driven Decision Making
      • Analytics Case Studies
      • Analytics Success Factors
      • The Analytics Environment: People, Culture and Structure
      • The Analytics Environment: IT Systems, Technologies and Tools
      • Evolutionary Development
      • Analytics Adoption Factors
      • Introduction to Data Visualisation
      • Conclusion

      Learning Objectives

      This course will provide attendees with a general understanding of:

      • The use of analytics within the business landscape
      • Data-driven decision making
      • How analytics is used to support data-driven decision-making (DDDM)
      • Factors influencing analytics success
      • The people, cultural and structural aspects of the analytics environment
      • Why people use BI tools
      • IT systems, technologies and tools within the analytics environment
      • Evolutionary analytics development and its benefits
      • Factors influencing analytics adoption

      Topic Outline

      Analytics and the Business Landscape

      What is data and why is a strategic asset for organisations?

      • What is Analytics? How are data used to make decisions?
      • A Brief History of BI and Context
      • What are the key types of analytics and when should each type be used?
      • Data-driven Decision Making

      Insight creation vs. decision support

      • How do people make decisions?
      • Bias in data-driven decision-making
      • The levels and types of business decisions and how they are supported with analytics

      Analytics Case Studies

      • Case Study 1
      • Case Study 2

      Analytics Success Factors

      • Overview of the 10 Analytics success factors

      The Analytics Environment: People, Culture and Structure

      • Analytics system governance and stakeholders
      • Structure of analytics teams
      • Use of analytics in organisations
      • Who are the analytics stakeholders and how do we understand them?
      • Analytics team skills and structure
      • Establishing and analytics culture in an organisation

      The Analytics Environment: IT Systems, Technologies and Tools

      • Overview of the data landscape
      • Data sources
      • Data challenges
      • Data transformation and integration
      • Data structure (Data lake, data warehouse, data mart, etc.)
      • Artificial intelligence and advanced analytics

      Evolutionary Development

      • The analytics <–> business feedback loop
      • Evolutionary analytics development
      • Benefits of evolutionary development
      • Evolutionary development vs. agile development
      • Example of evolutionary development

      Analytics Adoption Factors

      • Why is user adoption important?
      • What factors drive adoption?
      • Human factors
      • Usability and design factors
      • Data and infrastructure factors

      Data Visualisation Design

      • Data visualisation is communication for a technology
      • Best practice chart design based on understanding human interpretation


      Recap and Questions