Data Analytics for Business

Regular price €179.80
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Wolfgang Garn
Age Group_Uncategorized
Age Group_Uncategorized
Analytics
Artificial Intelligence
Author_Wolfgang Garn
automatic-update
Business
business performance indicators
Category1=Non-Fiction
Category=KJMK
Category=KJMV3
Category=KJMV5
Category=KJT
COP=United Kingdom
Data
Delivery_Pre-order
eq_bestseller
eq_business-finance-law
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Garn
interactive data exercises
knowledge discovery process
Language_English
PA=Not yet available
practical machine learning for business
Price_€100 and above
PS=Forthcoming
softlaunch
statistical learning methods
supervised classification models
unsupervised clustering techniques

Product details

  • ISBN 9781032372631
  • Weight: 980g
  • Dimensions: 174 x 246mm
  • Publication Date: 30 Apr 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
Secure checkout Fast Shipping Easy returns

We are drowning in data but are starved for knowledge. Data Analytics is the discipline of extracting actionable insights by structuring, processing, analysing and visualising data using methods and software tools. Hence, we gain knowledge by understanding the data. A roadmap to achieve this is encapsulated in the knowledge discovery in databases (KDD) process. Databases help us store data in a structured way. The structure query language (SQL) allows us to gain first insights about business opportunities. Visualising the data using business intelligence tools and data science languages deepens our understanding of the key performance indicators and business characteristics. This can be used to create relevant classification and prediction models; for instance, to provide customers with the appropriate products or predict the eruption time of geysers. Machine learning algorithms help us in this endeavour. Moreover, we can create new classes using unsupervised learning methods, which can be used to define new market segments or group customers with similar characteristics. Finally, artificial intelligence allows us to reason under uncertainty and find optimal solutions for business challenges. All these topics are covered in this book with a hands-on process, which means we use numerous examples to introduce the concepts and several software tools to assist us. Several interactive exercises support us in deepening the understanding and keep us engaged with the material.

This book is appropriate for master students but can be used for undergraduate students. Practitioners will also benefit from the readily available tools. The material was especially designed for Business Analytics degrees with a focus on Data Science and can also be used for machine learning or artificial intelligence classes. This entry-level book is ideally suited for a wide range of disciplines wishing to gain actionable data insights in a practical manner.

Wolfgang Garn is an Associate Professor at the University of Surrey. His research interests are in the areas of artificial intelligence, machine learning, operational research and business analytics. He is the CEO and founder of Smartana, which offers SMART analytics solutions and consulting services to businesses.

More from this author