Data Science and Analytics for SMEs
Apress (Verlag)
978-1-4842-8669-2 (ISBN)
SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing with the ongoing digital revolution. The topics covered in the books will help to provide the knowledge leverage needed for implementing data science in small business. The demand of small business for data analytics are in conjunction with the growing number of freelance data science consulting opportunities; hence this book will provide insight on how to navigate this new terrain.
This book uses a do-it-yourself approach to analytics and introduces tools that are easily available online and are non-programming based. Data science will allow SMEs to understand their customer loyalty, market segmentation, sales and revenue increase etc. more clearly. Data Science and Analytics for SMEs is particularly focused on small businesses and explores the analytics and data that can help them succeed further in their business.
What You'll Learn
Create and measure the success of their analytics project
Start your business analytics consulting career
Use solutions taught in the book in practical uses cases and problems
Who This Book Is For
Business analytics enthusiasts who are not particularly programming inclined, small business owners and data science consultants, data science and business students, and SME (small-to-medium enterprise) analysts
Afolabi Ibukun is a Data Scientist and is currently a Senior Lecturer in the Department of Computer and Information Sciences, Covenant University. She holds a B.Sc in Engineering Physics, an M.Sc and Ph.D in Computer Science. Afolabi Ibukun has over 15 years working experience in Computer Science research, teaching and mentoring. Her specific areas of interest are Data & Text Mining, Programming and Business Analytics. She has supervised several undergraduate and postgraduate students and published several articles in international journals and conferences. Afolabi Ibukun is also a Data Science Nigeria Mentor and currently runs a Business Analytics Consulting and Training firm named I&F Networks Solutions
Chapter 1: Introduction.- Chapter 2: Data for Analytics in Small Businesses.- Chapter 3: Business Analytics Consulting.- Chapter 4: Business Analytics Consulting Phases.- Chapter 5: Descriptive Analytics Tools.- Chapter 6: Predicting Numeric Outcomes.- Chapter 7: Classification Techniques.- Chapter 8: Advanced Descriptive Analytics.- Chapter 9: Case Study Part 1.- Chapter 10: Case Study Part 2.
“By reading the book and working out the use case, subject matter experts will be able to get a coherent roadmap to the main techniques available for both descriptive and predictive data analytics, as well as be able to provide simple services related to their company data and future prospects.” (Rosario Uceda-Sosa, Computing Reviews, October 2, 2023)
Erscheinungsdatum | 01.10.2022 |
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Zusatzinfo | 213 Illustrations, black and white; XVII, 335 p. 213 illus. |
Verlagsort | Berkley |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Mathematik / Informatik ► Informatik ► Netzwerke | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Mathematik / Informatik ► Mathematik | |
Schlagworte | business • Business Analytics • business problems • Consulting • data analytics • Data Mining • Data Science • data science for business • Descriptive Analytics • predictive analytics • Rapid Miner • Small Business |
ISBN-10 | 1-4842-8669-3 / 1484286693 |
ISBN-13 | 978-1-4842-8669-2 / 9781484286692 |
Zustand | Neuware |
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