Data Analytics Initiatives Managing Analytics for Success

English | 2022 | ISBN: 1032302402, 978-1032208510 | 164 pages | True PDF EPUB | 16.39 MB
The three-axis approach to analytics projects The categorisation of analytical initiatives could help us leverage the knowledge we have already gained and reflect it in our work. Correctly defined categories could help us to simplify the complexity reasonably and, at the same time, understand the critical aspects of analytical work. But how can we do it, and what can make it so complex? Common attributes of analytics projects Throughout the book, we reiterate that each analytics project is different. At the same time, analytics projects have a lot in common, and these features make them unique compared to other projects. Describing these commonalities could move us further in the conceptual understanding of analytical work. These specific features impact the entire project lifecycle, and neglecting them (trying to use general approaches without tailoring them to analytics projects) can lead to failure. General ideas of risks and challenges Challenges and risks - another critical aspect of analytical initiatives that could be the same from the overall definition perspective, but the realisation and mitigation could significantly differ based on the previously described project categorisation. Typical failures and risks per project types To provide a more tangible point of view, we would like to look at things from the opposite angle. So far, we have been looking at the typical characteristics of the analytics project (and how to categorise them). We will look at specific types of projects, provide a high-level assessment of their characteristics from a risk perspective (highly generalised), and comment on the most common problems or challenges. Typical questions for analytics projects As the last chapter of the book, we will try to provide you with some examples of questions that could be asked of relevant people in order to analyse the project. These questions may help you properly pos5ition the project on to each axis and understand the commonalities and general project challenges. This serves only as an example and may differ a great deal based on your company and environment. Analytics projects have a great deal of complexity, which can be hidden and needs to be considered. This book is a guide to evaluating and setting up analytics projects. It gives a holistic view of all aspects of analytical project that can be easily leveraged before a project starts or when it needs to be re-evaluated.