The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex?
Data Analytics Initiatives: Managing Analytics for Success
emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure.
In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.
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Ond¿ej Bothe has spent his whole life working in analytics. He has worked in many different roles: from hands-on developer to manager leading a team responsible for project implementation and IT analytical landscape operation. He was on the customer side, receiving advice from a consultant, but he has also worn the consultant hat, advising clients on analytical issues across sectors. Thanks to his economic background, he has a unique view of analytical projects. He can combine the aspect of technology, the delivery approach, and an understanding of data with an economist's perspective to ensure the best possible results for analytical insight consumers.
Ond¿ej Kubera has spent most of his career in IT delivery and consulting, focusing on analytics, including areas such as business intelligence, information management, and data governance. He is passionate about bridging the gap between the business and technical perspectives in the data analytics domain. He graduated from the Czech Technical University in Prague and has experience from a variety of hands-on engineering, as well as client-facing and managerial roles. He has led, designed, and consulted analytics initiatives in major consulting firms, a boutique data intelligence company, and a global pharma company.
David Bednä loves data and its presentation, and he has spent most of his career in the analytics area. He benefits from experience from both the academic and the business spheres, where he works on projects that further develop his robust technological background. He is a person who likes to develop anything new and innovative, who can define new architectures and patterns, or lead young talents to growth. David graduated from the Technical University of Ostrava focusing on data management and custom data structures, where he helped with research of multidimensional data structures as a member of the Database Research Group. ¿
Martin Potan¿ok supports data-inspired decisions in commercial and research projects. He has experience in software development and analytics. He has worked as a business analyst and project manager on software projects delivering mainly budgeting and reporting systems for international companies. Recently, he has been working as a business analyst on data and analytics projects. At the Prague University of Economics and Business, he is in charge of data activities and research projects organized in cooperation with the Faculty of Informatics and Statistics.
Ota Novotny has over twenty years of practical experience in data and business analytics. He helps people understand the importance and principles of data analytics in both academic and business projects and shows them how to use them in their professional lives. He has already supported thousands of people, helping them familiarize themselves with this modern and increasingly promising area of interest, and a large proportion of them have chosen data analytics as their career path. He is always looking for new ways to harness the potential of data and the associated data analytics for modern business.
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