Principle Practices Of Data Analytics
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Principle Practices Of Data Analytics
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Author : Mr. Vaishnavi Dutt Mishra
language : en
Publisher: Academic Guru Publishing House
Release Date : 2023-09-27
Principle Practices Of Data Analytics written by Mr. Vaishnavi Dutt Mishra and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-27 with Study Aids categories.
Data analytics is an umbrella term for a wide range of specific data-analysis techniques. Information of any kind may be put through data analytics processes to get useful understanding. Trends and metrics may be uncovered using data analytics methods that might have been obscured by the volume of data. Afterwards, this data may be utilized to fine-tune operations and boost the system's overall effectiveness. Companies that invest in data analytics see gains in revenue, efficiency, campaign effectiveness, and customer service. Companies may stay ahead of the competition by promptly adapting to new market trends with the help of analytics. The data used for analysis may be previously collected records or freshly processed data used for real-time analysis. Data may also be compiled from a variety of internal and external sources. Data analytics is a broad phrase that covers a wide range of fields and techniques, from traditional business intelligence (BI) and reporting to sophisticated OLAP and other kinds of online analytical processing (OLAP). Business analytics, another catch-all phrase for methods of data analysis, is similar in this respect. The latter has a concentration on commercial applications, whereas data analytics is more general. However, not everyone shares this broad definition; in other contexts, "data analytics" refers only to "advanced analytics," whereas "business intelligence" is considered a different entity.
Data Analytics Principles Tools And Practices
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Author : Gaurav Aroraa
language : en
Publisher: BPB Publications
Release Date : 2022-01-24
Data Analytics Principles Tools And Practices written by Gaurav Aroraa and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-24 with Antiques & Collectibles categories.
A Complete Data Analytics Guide for Learners and Professionals. KEY FEATURES ● Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database. ● Dive into Machine Learning, its tools, and applications. ● Coverage of applications of Big Data, Data Analysis, and Business Intelligence. DESCRIPTION These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science. WHAT YOU WILL LEARN ● Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. ● Learn to manage data warehousing with real time transaction processing. ● Explore various machine learning techniques that apply to data analytics. ● Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry. ● Acquaint yourself with Big Data tools and statistical techniques for machine learning. WHO THIS BOOK IS FOR IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book. TABLE OF CONTENTS 1. Database Management System 2. Online Transaction Processing and Data Warehouse 3. Business Intelligence and its deeper dynamics 4. Introduction to Data Visualization 5. Advanced Data Visualization 6. Introduction to Big Data and Hadoop 7. Application of Big Data Real Use Cases 8. Application of Big Data 9. Introduction to Machine Learning 10. Advanced Concepts to Machine Learning 11. Application of Machine Learning
Big Data Management
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-11-09
Big Data Management written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-09 with Business & Economics categories.
Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
Principles And Methods For Data Science
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Author :
language : en
Publisher: Elsevier
Release Date : 2020-05-28
Principles And Methods For Data Science written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with Mathematics categories.
Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Principles and Methods for Data Science
Principles Of Big Data
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Author : Jules J. Berman
language : en
Publisher: Newnes
Release Date : 2013-05-20
Principles Of Big Data written by Jules J. Berman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.
Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers Avoid the pitfalls in Big Data design and analysis Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources
Applied Predictive Analytics
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Author : Dean Abbott
language : en
Publisher: Wiley
Release Date : 2020-05-19
Applied Predictive Analytics written by Dean Abbott and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Computers categories.
Learn the art and science of predictive analytics - the latest techniques Predictive analytics is what translates big data into meaningful, usable business information. This guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory of analytics projects and offers tips and tricks for successful predictive modeling. Hands-on examples and case studies are included. Applied Predictive Analytics, 2nd Edition arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.
Applied Predictive Analytics
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Author : Dean Abbott
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-14
Applied Predictive Analytics written by Dean Abbott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-14 with Computers categories.
Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling. Hands-on examples and case studies are included. The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today This guide teaches not only the principles of predictive analytics, but also how to apply them to achieve real, pragmatic solutions Explains methods, principles, and techniques for conducting predictive analytics projects from start to finish Illustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenarios A companion website provides all the data sets used to generate the examples as well as a free trial version of software Applied Predictive Analytics arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.
Big Data
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Author : James Warren
language : en
Publisher: Simon and Schuster
Release Date : 2015-04-29
Big Data written by James Warren and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-29 with Computers categories.
Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth
Principles Of Data Science
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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2020-07-08
Principles Of Data Science written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-08 with Technology & Engineering categories.
This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice
Managerial Analytics
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Author : Michael Watson
language : en
Publisher:
Release Date : 2013
Managerial Analytics written by Michael Watson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Big data categories.