The Optimising Business Engagement in Analytics workshop is to improve team engagement in analytics projects by providing a common understanding of the activities involved in an analytics project. Participants also learn a process that helps them elicit a clear definition of business, data and analytics outcomes.
Launching a new digital investment requires the know-how to select technology, justify the investment and obtain stakeholders’ approval. This course gives you the knowledge and tools to justify your digital investment, compare real costs, understand the required resources and finally launch your project, program or product.
This course provides a practical framework for identifying digital change initiatives with enterprise analysis to highlight opportunities where real change is needed within the organisation. The framework covers how to appropriately prioritise these opportunities, identify missing competencies and resource them, and then how to evaluate and propose digital change solutions. The course concludes with how to devise and plan an appropriate implementation strategy and trajectory.
The Enterprise Digital Portfolio Management course covers key concepts required to manage an enterprise digital investment portfolio, including classical and goal-driven approaches. The course considers both the organisational and technological change potential of such investments.
This one day course builds on the foundation of Data Governance I, and dives deeper into selected areas that are designed to provide the most practical and real-world applications of data governance. It includes the change management journey to the “data-driven” organisation, and implications of the necessity of model governance in the context of data science, AI/ML initiatives and RPA/IPA .
Report automation can deliver powerful, time-saving results. This course teaches analytics professionals to automate the creation of PowerPoint packs from input Excel workbooks using R. Time is allotted for students to implement techniques taught so that, by the end of the course, students will have wrangled input data, created plots and tables, defined a PowerPoint template, and built a sample set of slides.
This course prepares data analytics professionals to communicate analytics results to business audiences, in a business context while being mindful of the skills, incentives, priorities and psychology of the audience. It also equips analysts [...]
Many people today have been developed emotionally and mentally for an era that no longer really exists. This has created a critical soft-skills gap between current workforce ability and business requirements today. In this course participants learn to ‘readapt’ their soft skills so that they are aligned with a thriving 21st century business. They are also given a simple framework from which to continue the self-development so that the training instigates sustainable change.
Real-time analytics is rapidly changing the landscape for deployment of decision support capability. The challenges of supporting extreme service levels in the areas of performance, availability, and data freshness demand new methods for data warehouse construction. Particular attention is paid to architectural topologies for successful implementation and the role of frameworks for Microservices deployment. In this workshop we will discuss evolution of data warehousing technology and new methods for meeting the associated service levels with each stage of evolution.
This full-day workshop examines the emergence of new trends in data warehouse implementation and the deployment of analytic ecosystems. We will discuss new platform technologies such as columnar databases, in-memory computing, and cloud-based infrastructure deployment. We will also examine the concept of a “logical” data warehouse – including and ecosystem of both commercial and open source technologies. Real-time analytics and in-database analytics will also be covered. The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics using AI and machine learning.