Buch, Englisch, 164 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 263 g
Managing Analytics for Success
Buch, Englisch, 164 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 263 g
ISBN: 978-1-032-20851-0
Verlag: Auerbach Publications
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.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
Weitere Infos & Material
I. The Framework Definition 1. The Three-Axis Approach to of Analytics Projects II. The Framework in Context 2. Common Attributes of Analytics Projects 3. General Areas and of Risks Challenges 4. Typical Failures and Risks per Project Type 5. Typical Questions for Analytics Projects
