Data Analytics

3 Books in 1 - The New Ultimate Bible for Understanding & Using Data Analytics, Big Data + Data Science For Business + Data Mining

Author: John Harper

Publisher: N.A

ISBN: 9781074535988

Category:

Page: 170

View: 390

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Data Analytics: 3 Books in 1 - The New Ultimate Bible for Understanding & Using Data Analytics, Big Data + Data Science For Business + Data MiningIn this 3 Book Bible we will discuss everything you will need to know to start understanding the world of Data Analytics, Big Data and Data Science For BusinessThere are plenty of books on this subject on the market, thanks again for choosing thisone! Every effort was made to ensure it is full of as much useful information as possible.Please enjoy! Here Is A Preview Of What You'll Learn...In Book 1: Data Analytics: The New Ultimate Guide To Understanding & Using Data Analytics, Data Mining, Big DataData Analytics UtilizationTypes of AnalyticsTechniques Applied in Data AnalyticsIntegrating Business and Data AnalyticsIn Book 2: Data Science For Business: How To Use Data Analytics and Data Mining in Business, Big Data For BusinessHow to Undertake Data ScienceVisualizing the DataApplication of Big Data in Data ScienceHow to Use Data Science AppropriatelyIn Book 3: Data Mining: The Complete Beginner's Guide - Discover How To Use Data Mining in Business, Data AnalyticsAssociation Rule MiningGenetic AlgorithmMachine LearningRegression AnalysisAnd Much Much More..Get Your Copy Right Now!
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Artificial Intelligence and Machine Learning for Business

The Ultimate Guide to Use Data Science for Business Through Applied Artificial Intelligence. Includes Big Data and Data Mining for Business

Author: Oliver Tensor

Publisher: N.A

ISBN: 9781087192789

Category:

Page: 122

View: 7866

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Are you a new business owner? Or an entrepreneur looking to catch up to the big companies in your industrial sector? If you want to understand and master the fundamentals and importance of data science technologies to kick start your business or take it to the next level, then keep reading. Thanks to the smart and savvy customer of today, the competition to gain new customers while retaining the existing customers is fierce. As a result, companies are increasingly relying upon cutting edge technologies such as big data analytics, data mining technology, machine learning, and artificial intelligence technology to gain an edge over the competition.Today, machine learning and artificial intelligence have given rise to sophisticated machines that can study human behavior and activity to identify underlying human behavioral patterns and precisely predict what products and services consumers are interested in. Businesses with an eye on the future are gradually turning into technology companies under the façade of their intended business model. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. Those entrepreneurs and business executives who have a sound understanding of the current challenges and status of their business will be primed to make informed decisions to meet the challenges head-on and improve their bottom line. Receive overarching guidance on how you can adopt any and all of the Data Science technologies in your business model to accelerate your growth rate. Learn how researchers are breaking the boundaries of data science to mimic human intelligence in machines. Learn the data science lifecycle in such extensive detail that you will be fully prepared to initiate and complete a data science implementation project in your business. Learn all about the historical development to the current explosion in this field of Big Data Analytics and how it differs data visualization techniques. Dig deep into the data mining process, the benefits of using data mining technology, the challenges facing the data mining technology and learn about some data mining tools that you can leverage for your business. Gain an in-depth understanding of various machine learning algorithms do assess the best Machine learning algorithm applicable to your business model. Learn the very important concept of data science and machine learning Decision Trees, applicable to small and large businesses across the industrial spectrum, explained thoroughly using real-life examples for ease of understanding. Master the concept of sales and marketing funnel along with the tools available for sales funnel analytics in the market today. Deep dive into the concept of personalized marketing, predictive analytics, customer analytics, and exploratory data analysis presented with details on how you can make sense out of all your customer behavioral data. This book is filled with real-life examples to help you understand the nitty-gritty of all the concepts as well as names and description of multiple tools that you can further explore and selectively implement in your business to reap the benefits of these cutting-edge technologies. Would You Like to Know More? ? Download Now to get access to Artificial Intelligence and Machine Learning power. Scroll to the top of the page and select BUY NOW button
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Understanding the Role of Business Analytics

Some Applications

Author: Hardeep Chahal,Jeevan Jyoti,Jochen Wirtz

Publisher: Springer

ISBN: 9811313342

Category: Business & Economics

Page: 205

View: 7730

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This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in applying the data analytical techniques; and also analyses how these techniques are effective in decision-making in different contexts. Especially, the application of regression modeling, financial modelling, multi-group modeling, cluster analysis, and sentiment analysis will help the readers in understanding critical business scenarios in the best possible way, and which later can help them in arriving at best solution for the business related problems. The individual chapters will help the readers in understanding the role of specific data analytic tools and techniques in resolving business operational issues experienced in manufacturing and service organisations in India and in developing countries. The book offers a relevant resource that will help readers in the application and interpretation of data analytical statistical practices relating to emerging issues like customer experience, marketing capability, quality of manufactured products, strategic orientation, high-performance human resource policy, employee resilience, financial resources, etc. This book will be of interest to a professional audience that include practitioners, policy makers, NGOs, managers and employees as well as academicians, researchers and students.
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Predictive Analytics, Data Mining and Big Data

Myths, Misconceptions and Methods

Author: S. Finlay

Publisher: Springer

ISBN: 1137379286

Category: Business & Economics

Page: 260

View: 3874

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This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.
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Enterprise Analytics

Optimize Performance, Process, and Decisions Through Big Data

Author: Thomas H. Davenport

Publisher: FT Press

ISBN: 0133039463

Category: Business & Economics

Page: 304

View: 5807

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Normal 0 false false false MicrosoftInternetExplorer4 The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.
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Spark: The Definitive Guide

Big Data Processing Made Simple

Author: Bill Chambers,Matei Zaharia

Publisher: "O'Reilly Media, Inc."

ISBN: 1491912308

Category: COMPUTERS

Page: 608

View: 1988

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Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation
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International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018

Author: Jude Hemanth,Xavier Fernando,Pavel Lafata,Zubair Baig

Publisher: Springer

ISBN: 3030031462

Category: Computers

Page: 1590

View: 5111

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This book discusses data communication and computer networking, communication technologies and the applications of IoT (Internet of Things), big data, cloud computing and healthcare informatics. It explores, examines and critiques intelligent data communications and presents inventive methodologies in communication technologies and IoT. Aimed at researchers and academicians who need to understand the importance of data communication and advanced technologies in IoT, it offers different perspectives to help readers increase their knowledge and motivates them to conduct research in the area, highlighting various innovative ideas for future research.
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Big Data: Concepts, Methodologies, Tools, and Applications

Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 1466698411

Category: Computers

Page: 2478

View: 6875

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The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.
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