Data Culture Curriculum2021-09-08T06:38:15+00:00
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Data-Driven Decision-Making

The Data-Driven Decision-Making course is for executives and managers who want to leverage analytics to support their most vital decisions and enable better decision-making at the highest levels. It empowers senior executives with skills to make more effective use of data analytics. It covers contexts including strategic decision-making and shows attendees ways to use data to make better decisions. Attendees will learn how to receive, understand and make decisions from a range of analytics methods, including visualisation and dashboards. They will also be taught to work with analysts as effective customers.

Data Visualisation and Communication

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 [...]

Critical Thinking for Data Analytics

This course is a vital first step in the data literacy journey, and the one that introduces the most vital and basic skills of the effective 21st century professional or leader. Working with data is not just about manipulating software tools : it is first and foremost about effective reasoning, using all available information. As such, this course loads the key “software” into the most vital hardware of the business - the human professional, enabling them to reason effectively with data, and thus realise the value that data analytics promises, deriving more reliable and correct insights and making better decisions.

Data Literacy for Everyone

This course is for workers and managers without a strong quantitative background. It introduces a range of skills and applications related to data literacy for digital transformations and critical thinking in such areas as forecasting, population measurement, set theory and logic, causal impact and attribution, scientific reasoning and the danger of cognitive biases. There are no prerequisites beyond high-school mathematics; this course has been designed to be approachable for everyone.

Data Governance I

This two day course provides an informed, realistic and comprehensive foundation for establishing best practice data governance in your organisation. Suitable for every level from CDO to executive to data steward, this highly practical course will equip you with the tools and strategies needed to successfully create and implement a data governance strategy and roadmap.

Social Network Analysis: Practical Use Cases and Implementation

Social networking via Web 2.0 applications such as LinkedIn and Facebook has created huge interest in understanding the connections between individuals to predict patterns of churn, influencers related to early adoption of new products and services, successful pricing strategies for certain kinds of services, and customer segmentation. We will explain how to use these advanced analytic techniques with mini case studies across a wide range of industries including telecommunications, financial services, health care, retailing, and government agencies. 

Overcoming Information Overload with Advanced Practices in Data Visualisation

In this workshop, we explore best practices in deriving insight from vast amounts of data using visualisation techniques. Examples from traditional data as well as an in-depth look at the underlying technologies for visualisation in support of geospatial analytics will be undertaken. We will examine visualisation for both strategic and operational BI.

Best Practices in Enterprise Information Management

The effective management of enterprise information for analytics deployment requires best practices in the areas of people, processes, and technology. In this talk we will share both successful and unsuccessful practices in these areas. The scope of this workshop will involve five key areas of enterprise information management: (1) metadata management, (2) data quality management, (3) data security and privacy, (4) master data management, and (5) data integration.

Agile Data Management Architecture

This full-day workshop examines the trends in analytic technologies, methodologies, and use cases. 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.

Understand Blockchain, Smart Contracts and Cryptocurrency

Blockchain is one of the most disruptive and least understood technologies to emerge over the previous decade. This course gives participants an intuitive understanding of blockchain in both public and private contexts, allowing them to distinguish genuine use cases from hype. We explore public crypto-currencies, smart contracts and consortium chains, interspersing theory with case studies from areas such as financial markets, health care, trade finance, and supply chain. The course does not require a technical background.

Data Governance II

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 .

Agile Insights

This course presents a process and methods for an agile analytics delivery. Agile Insights reflects the capabilities required by any organisation to develop insights from data and validate potential business value. Content presented describes the process, how it is executed and how it can be deployed as a standard process inside an organisation. The course will also share best practices, highlight potential tripwires to watch out for, as well as roles and resources required.

Intro to R (+ data visualisation)

This R training course will introduce you to the R programming language, teaching you to create functions and customise code so you can manipulate data and begin to use R self-sufficiently in your work. R is the world’s most popular data mining and statistics package. It’s also free, and easy to use, with a range of intuitive graphical interfaces.

Intro to Python for Data Analysis

Python is a high-level, general-purpose language used by a thriving community of millions. Data-science teams often use it in their production environments and analysis pipelines, and it’s the tool of choice for elite data-mining competition winners and deep-learning innovations. This course provides a foundation for using Python in exploratory data analysis and visualisation, and as a stepping stone to machine learning.

Your Successful Digital Business Case

All participants in digital transformation will need to be digital business case literate in an automated, decision-focused future. This course is designed to increase non-expert level ability to competently turn data into concise data storytelling. It teaches you how to apply the right numbers to transform the story into a business benefit calculation, so that both parts are well understood by technical and business decision makers within a company. This course covers a broad range of business skills, including telling a concise story based on data (business storytelling), techniques to simplify and abstract complex situations and sharpening data stories to apply financial figures to the resulting business case.

AI and Data Science for Managers and Executives

Improve your project’s chance of success by avoiding common failures in AI and data science projects. This one-day workshop is aimed at current or aspiring leaders and managers of AI / machine learning teams and functions. The focus of the course is on the key concepts that are required to avoid the most common and far too frequent failures in AI projects and initiatives.

Agile Transition

This course describes the cultural and organisational aspects required for an organisation on the digital transformation path. A healthy corporate culture around data awareness is imperative to leverage the potential and value of data to the benefit of a company's business model. The organisation needs to reflect the culture and reward those who add value to a corporation by using data and analytics. Content presented explains personality and skill identification, how to prototype an agile analytics organisation and describe how to validate change capabilities, close gaps and execute a transition strategy.

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