Fundamental Of Data Science And Big Data Analytics
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Fundamental Of Data Science And Big Data Analytics
Author: N. Narayanan Prasanth
language: en
Publisher: Academic Guru Publishing House
Release Date: 2023-11-29
The book provides a thorough, accessible, and current comprehension of Big Data for both business people and engineers. This book presents essential ideas, theories, terminology, and technologies related to Big Data. It also covers important analysis and analytics approaches. The information is rationally organized, given in clear and simple language, and backed with easily comprehensible examples. The objective of “Fundamentals of Data Science and Big Data Science” is to enhance decision-making by analyzing data. Currently, data science plays a crucial role in determining the advertisements that appear on the internet, the recommendations you get for books and films, the classification of emails into your spam folders, as well as the pricing of health insurance. This book provides a brief description of the developing discipline of data science, elucidating its progression, present applications, data infrastructure concerns, and legal issues. The text adopts a conversational tone and stays clear of complex mathematical ideas often associated with data science, instead focusing on straightforward explanations and real-world use cases. Upon concluding the book, readers will have acquired proficiency in controlling data, using data in the context of business challenges, and implementing optimal methodologies for data analysis. This book functions as a practical guide for Science/Engineering/MBA students, including both undergraduate and graduate students, who have an interest in the field of Data Science.
Fundamentals of Data Science
Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.
Fundamentals of Big Data Analytics
Author: Mahmoud Ahmad Al-Khasawneh
language: en
Publisher: Xoffencer International Book Publication House
Release Date: 2025-05-29
The exponential rise of data in the modern digital era has been responsible for a transformation in the way that individuals, corporations, and governments conduct their operations. Every single click on the internet, every single transaction at a store, every single sensor in a machine, and every single post on social media all add to the massive amount of data that is known as Big Data, which is continuing to grow at an exponential rate. The tools and methods that have been used traditionally for data processing are no longer enough to effectively manage, process, or derive useful insights from the flood of information that is currently available. Big Data Analytics is a multidisciplinary area that integrates computer science, statistics, mathematics, and domain expertise in order to analyse and interpret vast and complex information. This has led to the birth of Big Data Analytics. In general, Big Data may be characterised by five fundamental aspects, which are sometimes referred to as the 5Vs. Volume refers to the volume of data that is produced each and every second. The rate at which information is generated and processed is referred to as velocity. A variety of data forms and kinds, including structured, semi-structured, and unstructured data, are referred to as variety. The trustworthiness and precision of the data is referred to as veracity. Value is defined as the possible advantages and insights that may be generated from data. The act of analysing these enormous databases in order to unearth previously concealed patterns, correlations, trends, and other important information is referred to as Big Data Analytics. With its help, businesses are able to make decisions based on data, improve the experiences of their customers, optimise their operations, and acquire a competitive advantage. It provides assistance for evidence-based approaches to the resolution of difficult issues in the realms of scientific research and public policy research. The capabilities of big data systems have been considerably improved as a result of the development of cutting-edge technologies such as distributed computing, cloud platforms, NoSQL databases, and real-time processing frameworks (such as Apache Hadoop and Apache Spark).