Data Science for Business

This guide also helps you understand the many data-mining techniques in use today.

Author: Foster Provost

Publisher: "O'Reilly Media, Inc."

ISBN: 144937428X

Category: Computers

Page: 414

View: 714

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Data Science for Business and Decision Making

As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work.

Author: Luiz Paulo Fávero

Publisher: Academic Press

ISBN: 0128112174

Category: Business & Economics

Page: 1240

View: 483

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Business Data Science Combining Machine Learning and Economics to Optimize Automate and Accelerate Business Decisions

Unlike most machine learning texts, this book provides methods of extracting reliable understanding from data, addressing the problem that correlation is not causation.” —PRESTON MCAFEE, former Chief Economist and Corporate Vice ...

Author: Matt Taddy

Publisher: McGraw-Hill Education

ISBN: 9781260452778

Category: Business & Economics

Page: 352

View: 876

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: •Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling•Understand how use ML tools in real world business problems, where causation matters more that correlation•Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.

Data Science for Business

Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the ...

Author: Foster Provost

Publisher:

ISBN: 9781449374273

Category: Big data

Page:

View: 712


Data Science for Business Professionals

The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.Ê WHAT WILL YOU LEARNÊÊ - Understand the multi-disciplinary nature of Data Science - Get familiar with ...

Author: Probyto Data Science and Consulting Pvt. Ltd.

Publisher: BPB Publications

ISBN: 9389423287

Category: Computers

Page: 368

View: 967

Primer into the multidisciplinary world of Data Science KEY FEATURES - Explore and use the key concepts of Statistics required to solve data science problems - Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app - Learn how to build Data Science solutions with GCP and AWS DESCRIPTION The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset. WHAT WILL YOU LEARN - Understand the multi-disciplinary nature of Data Science - Get familiar with the key concepts in Mathematics and Statistics - Explore a few key ML algorithms and their use cases - Learn how to implement the basics of Data Pipelines - Get an overview of Cloud Computing & DevOps - Learn how to create visualizations using Tableau WHO THIS BOOK IS FOR This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science. TABLE OF CONTENTS 1. Data Science in Practice 2. Mathematics Essentials 3. Statistics Essentials 4. Exploratory Data Analysis 5. Data preprocessing 6. Feature Engineering 7. Machine learning algorithms 8. Productionizing ML models 9. Data Flows in Enterprises 10. Introduction to Databases 11. Introduction to Big Data 12. DevOps for Data Science 13. Introduction to Cloud Computing 14. Deploy Model to Cloud 15. Introduction to Business Intelligence 16. Data Visualization Tools 17. Industry Use Case 1 – FormAssist 18. Industry Use Case 2 – PeopleReporter 19. Data Science Learning Resources 20. Do It Your Self Challenges 21. MCQs for Assessments

Data Science for Business

In this guidebook, you will discover more about data science and how to get started in this field. This book will discuss the following topics: What is data science?

Author: Herbert Jones

Publisher: Createspace Independent Publishing Platform

ISBN: 9781727618570

Category:

Page: 100

View: 591

Do you want to learn about data science but aren't in the mood to read a boring textbook? Data science has a huge impact on how companies conduct business, and those who don't learn about this revolutionaryfield could be left behind. You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers. And it is all done by collecting and sorting through a large amount of information, so you have the right sources behind you when you make a major decision. In this guidebook, you will discover more about data science and how to get started in this field. This book will discuss the following topics: What is data science? How Big Data works and why it is so important How to do an explorative data analysis Working with data mining How to mine text to get the data Some amazing machine learning algorithms to help with data science How to do data modeling Data visualization How to use data science to help your business grow Tips to help you get started with data science And much, much more! So if you are ready to get started with data science, click "add to cart"!

Data Science and Digital Business

This book combines the analytic principles of digital business and data science with business practice and big data.

Author: Fausto Pedro García Márquez

Publisher: Springer

ISBN: 9783319956503

Category: Business & Economics

Page: 321

View: 406

This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

Data Science for Business

Fundamental concepts: Our principles as the basis of success for a data-driven
business; Acquiring and sustaining competitive advantage via data science; The
importance of care‐ful curation of data science capability. In this chapter we ...

Author: Foster Provost

Publisher: "O'Reilly Media, Inc."

ISBN: 1449374298

Category: Business & Economics

Page: 414

View: 566

Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, you will understand the many data-mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques.

Data Science For Dummies

Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights.

Author: Lillian Pierson

Publisher: John Wiley & Sons

ISBN: 1119327636

Category: Computers

Page: 384

View: 388

Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

Data Science

Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions.

Author: Vijay Kotu

Publisher: Morgan Kaufmann

ISBN: 0128147628

Category: Computers

Page: 568

View: 995

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You’ll be able to: Gain the necessary knowledge of different data science techniques to extract value from data. Master the concepts and inner workings of 30 commonly used powerful data science algorithms. Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... Contains fully updated content on data science, including tactics on how to mine business data for information Presents simple explanations for over twenty powerful data science techniques Enables the practical use of data science algorithms without the need for programming Demonstrates processes with practical use cases Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language Describes the commonly used setup options for the open source tool RapidMiner

Analytics and Data Science

This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data.

Author: Amit V. Deokar

Publisher: Springer

ISBN: 3319580973

Category: Computers

Page: 297

View: 243

This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.

DATA SCIENCE

While this book is a comprehensive guide on various method methods and strategies to learn data science for business, it doesn’t include the general basic knowledge of data science.

Author: William Vance

Publisher: joiningthedotstv

ISBN:

Category: Computers

Page: 95

View: 911

Discover advanced methods and strategies to learn data science for business. When the concept ‘data science’ was incorporated into some basic business decision processes, it was, at some point, neglected. But with the recent technological advancement, this method of analytics can no longer be neglected in the various decision-making process of a business. Yet, a lot of business owners are unaware of the ubiquity of data opportunities in business The book introduces various methods and strategies that are essential to facilitate your learning path into data science and how it can be used for business decisions and organizational growth. In simple terms, it provides real-world situations that can be used to explain the pervasiveness of data opportunities in business. Hence, as a business owner, you can learn how to participate smartly on your data science project even without the help of a data scientist. You will also discover advanced methods and strategies on how to think analytically while using various data mining strategies to collate data for your analysis. In this book, you will learn how to wrangle, program, explore data sets, model your data, and how to communicate business decisions and findings using data visualization techniques. While this book is a comprehensive guide on various method methods and strategies to learn data science for business, it doesn’t include the general basic knowledge of data science. Hence, the following are some of the things you should expect: · The pervasiveness of data opportunities · The overall process of business decisions and how data science is useful during this process · Various analytical approaches to business · Programming languages · And data visualization Finally, the opportunities that big data provides are vast; let this book help you harness those opportunities. Now is the time to start collating essential information, making rational predictions, and gaining a competitive advantage over other businesses using the vast array of data available online.

Big Data MBA

This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity.

Author: Bill Schmarzo

Publisher: John Wiley & Sons

ISBN: 1119181119

Category: Computers

Page: 312

View: 859

Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

The Data Science Handbook

This book provides a crash course in data science, combining all the necessary skills into a unified discipline.

Author: Field Cady

Publisher: John Wiley & Sons

ISBN: 1119092949

Category: Mathematics

Page: 416

View: 828

A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Applying Data Science

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods.

Author: Arthur K. Kordon

Publisher: Springer

ISBN: 9783030363741

Category: Computers

Page: 494

View: 932

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.

Data Science for Business with R

To keep the book practical and applied, the authors feature a running case using a global airline business's customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout.

Author: Jeffrey S. Saltz

Publisher: Sage Publications, Incorporated

ISBN: 9781544370453

Category:

Page: 280

View: 788

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business's customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.

Data Science for Business

Alternatively, you might be looking for more information on the field so as to launch a career as a data analyst. Well, this book can certainly help you out in both ways. Here Is A Preview Of What You'll Learn.

Author: J. F. Thompson

Publisher: Createspace Independent Publishing Platform

ISBN: 9781987513332

Category:

Page: 48

View: 765

Data Science For Business: The Complete Guide To Using Data Analytics and Data Mining in Business I want to thank you and congratulate you for downloading the book, "Data Science For Business: The Complete Guide to Using Data Analytics and Data Mining in Business." How do you define the success of a company? It could be by the number of employees or level of employee satisfaction. Perhaps the size of the customer base is a measure of success or the annual sales numbers. How does management play a role in the operational success of the business? How critical is it to have a data scientist to help determine what's important? Is fiscal responsibility a factor of success? To determine what makes a business successful, it is important to have the necessary data about these various factors. You might be looking to get a better grasp of data analytics so as to use in your own business. Alternatively, you might be looking for more information on the field so as to launch a career as a data analyst. Well, this book can certainly help you out in both ways. Here Is A Preview Of What You'll Learn... Data Analytics Explained Methodologies of Data Analytics Importance of Data Data Science and Data Analytics Foundation of Data Analytics Data Gathering and Mining Connecting Data Analytics to the Outcomes of a Business And Much Much More.. Get Your Copy Right Now!

Analytics

Many people make the mistake of making plans but having no follow-through. This is where analytics comes in. Don't you wish to have the power to know what your target consumers are thinking?

Author: Daniel Covington

Publisher: Lulu.com

ISBN: 9780359828524

Category: Business & Economics

Page: 288

View: 626

SO MANY PEOPLE DREAM OF BECOMING THEIR OWN BOSS OR SUCCEEDING IN THEIR CHOSEN PROFESSION, AND WITH THE RESOURCES AVAILABLE TODAY, MORE ENTREPRENEURS AND PROFESSIONALS ARE ACHIEVING GREAT SUCCESS! HOWEVER, SUCCESS SHOULD BE DEFINED FOR THE LONG TERM, AND AS OPPORTUNITIES START TO GROW, SO DOES THE COMPETITION. Getting your business up and running or starting on your career path is one thing, but have a sustainable business or career is completely another. Many people make the mistake of making plans but having no follow-through. This is where analytics comes in. DonÕt you wish to have the power to know what your target consumers are thinking? WonÕt you want to have a preview of what future trends to expect in the market you are in? Well, this book is just the one you need. This book will teach you, in simple and easy-to-understand terms, how to take advantage of data from your daily operations and make such data a powerful tool that can influence how well your business does over time.

Data Analytics

Data Analytics: 3 Books in 1 - The New Ultimate Bible for Understanding & Using Data Analytics, Big Data + Data Science For Business + Data Mining **BONUS** Buy a paperback copy of this book NOW and you will get the Kindle version ...

Author: John Harper

Publisher:

ISBN: 9781074535988

Category:

Page: 170

View: 815

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!

Data Science

2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data ...

Author: Herbert Jones

Publisher:

ISBN: 9781647483043

Category: Computers

Page: 134

View: 242

2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying