An Introduction to Data Skills & Capabilities for Non Specialists
Build the skills & the confidence to use data to drive decision making
Today’s ever-growing volumes of data and the easy access to tools to make sense of that data is driving organisations, both public and private, to use data to answer questions and support decision making.
Using data to support decisions helps organisations move from a “I think the answer is…” mindset based on intuition to a “I know the answer is…” mindset based on facts.
However, simply having access to the data and the tools is not enough to promote data-driven decision-making.
The people answering the questions and making the decision must have the ability to define questions in the terms of data and then locate, interpret and analyse the data to come to an answer.
In this interactive workshop you will learn the language of data and how to apply a simple, structured process that will show you how to ask the right question, obtains the most relevant data, make sense of the data, come to conclusions supported by the data and present the results to stakeholders in a way that is easy for them to comprehend and act on.
What can I expect from this workshop?
- The support and guidance of an expert – Ask your questions and work through challenges at the right pace
- Small group-based problem activity sessions to translate theory into practice
- Real world learning with practical examples and case studies
- Networking opportunities – Build new connections with like minded peers in a small group setting
- Resources to walk away with – A copy of the Data-Driven Decision-Making Canvas template for you to use to plan future data-driven decision making
Who should attend?
This workshop is ideal for public sector professionals working in non data specialist roles who are interested in developing their data skills and capabilities to support decision making.
Don’t worry – we don’t expect you to be an expert. The workshop has been designed as an introduction and no prior knowledge of data analysis concepts or methods are required.