Ebook: Data Science and Data Analytics: Opportunities and Challenges

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured (labelled) and unstructured (unlabelled) data. It is the future of Artificial Intelligence (AI) and the necessity of future to make things easier and more productive. In simple terms, Data science is the discovery of data or uncovering hidden patterns (like complex behaviors, trends, and inferences) from data. Moreover, Big Data Analytics/Data Analytics are the analysis mechanism used in Data Science by Data Scientist. Several tools like Hadoop, R, etc., are being used to analyse this large amount of data that can be used in predicting the valuable information/ making decisions. Note that structured data can be easily analysed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in unstructured form that requires advanced analytics tools. But while analysing, we face several concerns like complexity, scalability, privacy leaking and trust issues. Data science helps us in extracting meaningful information (or insights) from the unstructured or complex or large amount of data (available or stored around us virtually at cloud).

In summary, this book will cover all the possible areas, applications with arising serious concerns, and challenges towards this emerging area/ field in detail (with a comparative analysis/ taxonomy). This books provides information to its readers

1. This book gives concept of Data Science, Tools and Algorithms existed for many useful applications
2. This book provides many challenges and Opportunities in Data Science and Data Analytics, which help researchers in identifying research gaps or problems to continue their research work
3. All possible areas and uses of data science in this smart era
4. This book is in written many areas like agriculture, healthcare, Graph mining, Education, Security, etc., for providing a clear understanding to readers.

Academician, Data Scientist, and Stockbrokers from Industry/Business will find this book useful in knowing optimal strategies for enhancing their firm's productivity.