Data Analytics for Business: AI-ML-PBI-SQL-R

Data analytics is the discipline of extracting actionable insights from data by structuring, processing, analyzing, and visualizing it. The knowledge discovery in databases (KDD) process is a roadmap to achieve this, and databases help store data in a structured way. Visualizing data using business intelligence tools and data science languages deepens understanding of key performance indicators and business characteristics, and machine learning algorithms help create new classes and find optimal solutions for business challenges. This book is appropriate for master students, undergraduate students, practitioners, and business analytics degrees with a focus on Data Science.

Format: Paperback / softback
Length: 270 pages
Publication date: 30 April 2024
Publisher: Taylor & Francis Ltd

In the vast ocean of data, we find ourselves desperately yearning for knowledge. Data Analytics emerges as a discipline, empowering us to extract valuable insights by structuring, processing, analyzing, and visualizing data through the use of methods and software tools. Through this process, we embark on a journey of gaining knowledge, as we unravel the mysteries hidden within the data.

A roadmap to achieve this knowledge is encapsulated in the knowledge discovery in databases (KDD) process. Databases serve as repositories, allowing us to organize data in a structured manner. The structure query language (SQL) empowers us to gain initial insights into business opportunities, providing a foundation for further exploration.

Visualizing the data through business intelligence tools and data science languages deepens our understanding of key performance indicators and business characteristics. This knowledge empowers us to create relevant classification and prediction models, such as delivering personalized products to customers or predicting the eruption time of geysers. Machine learning algorithms play a pivotal role in this endeavor, aiding us in identifying patterns and making informed decisions.

Furthermore, we can employ unsupervised learning methods to create new classes, defining new market segments or grouping customers with similar characteristics. Artificial intelligence emerges as a powerful ally, enabling us to reason under uncertainty and find optimal solutions to business challenges.

This comprehensive book covers these topics in depth, employing a hands-on approach that utilizes numerous examples to introduce concepts and provides software tools to assist in our journey. Interactive exercises further enhance our understanding and keep us engaged with the material.

While this book is primarily designed for master students, it can also be valuable for undergraduate students. Practitioners, too, will find great benefit in the readily available tools and methodologies presented. The material was meticulously crafted with a focus on Business Analytics degrees, particularly emphasizing Data Science, and can also be utilized for machine learning or artificial intelligence.

In summary, this book offers a comprehensive and practical guide to Data Analytics, equipping us with the skills and knowledge needed to navigate the vast ocean of data and extract actionable insights. Whether you are a student, practitioner, or enthusiast, this book is your gateway to a world of knowledge and opportunities.

Weight: 618g
Dimension: 172 x 245 x 17 (mm)
ISBN-13: 9781032372624