Numsense! Data Science for the Layman

No Math Added

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Author: Annalyn Ng

Publisher: Annalyn Ng & Kenneth Soo

ISBN: 9789811110689

Category:

Page: N.A

View: 4090

Used in Stanford's CS102 Big Data (Spring 2017) course. Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations, as well as lots of visuals, all of which are colorblind-friendly. Popular concepts covered include: A/B Testing Anomaly Detection Association Rules Clustering Decision Trees and Random Forests Regression Analysis Social Network Analysis Neural Networks Features: Intuitive explanations and visuals Real-world applications to illustrate each algorithm Point summaries at the end of each chapter Reference sheets comparing the pros and cons of algorithms Glossary list of commonly-used terms With this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

Building Data Science Teams

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Author: DJ Patil

Publisher: "O'Reilly Media, Inc."

ISBN: 1449316778

Category: Computers

Page: 24

View: 1571

As data science evolves to become a business necessity, the importance of assembling a strong and innovative data teams grows. In this in-depth report, data scientist DJ Patil explains the skills, perspectives, tools and processes that position data science teams for success. Topics include: What it means to be "data driven." The unique roles of data scientists. The four essential qualities of data scientists. Patil's first-hand experience building the LinkedIn data science team.

Principles of Data Science

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Author: Sinan Ozdemir

Publisher: Packt Publishing Ltd

ISBN: 1785888927

Category: Computers

Page: 388

View: 6825

Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn Get to know the five most important steps of data science Use your data intelligently and learn how to handle it with care Bridge the gap between mathematics and programming Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results Build and evaluate baseline machine learning models Explore the most effective metrics to determine the success of your machine learning models Create data visualizations that communicate actionable insights Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Data Science For Dummies

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Author: Lillian Pierson

Publisher: John Wiley & Sons

ISBN: 1119327644

Category: Computers

Page: 384

View: 4901

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.

Confident Data Skills

Master the Fundamentals of Working with Data and Supercharge Your Career

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Author: Kirill Eremenko

Publisher: Kogan Page Publishers

ISBN: 0749481552

Category: Computers

Page: 272

View: 8666

Data science is the most exciting skill you can master. Data has dramatically changed how our world works. From entertainment to politics, from technology to advertising and from science to the business world, data is integral and its only limit is our imagination. If you want to have a vibrant and valuable professional life, being skilled with data is the key to a cutting-edge career. Learning how to work with data may seem intimidating or difficult but with Confident Data Skills you will be able to master the fundamentals and supercharge your professional abilities. This essential book covers data mining, preparing data, analysing data, communicating data, financial modelling, visualizing insights and presenting data through film making and dynamic simulations. In-depth international case studies from a wide range of organizations, including Netflix, LinkedIn, Goodreads, Deep Blue, Alpha Go and Mike's Hard Lemonade Co. show successful data techniques in practice and inspire you to turn knowledge into innovation. Confident Data Skills also provides insightful guidance on how you can use data skills to enhance your employability and improve how your industry or company works through your data skills. Expert author and instructor, Kirill Eremenko, is committed to making the complex simple and inspiring you to have the confidence to develop an understanding, adeptness and love of data.

The Data Science Handbook

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Author: Field Cady

Publisher: John Wiley & Sons

ISBN: 1119092949

Category: Mathematics

Page: 416

View: 4127

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.

Naked Statistics: Stripping the Dread from the Data

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Author: Charles Wheelan

Publisher: W. W. Norton & Company

ISBN: 0393089827

Category: Mathematics

Page: 302

View: 9584

“Brilliant, funny . . . the best math teacher you never had.”—San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

Data Scientist's Book of Quotes

Insights and Advice from Data Science Leaders and Key Influencers

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Author: Matt Corey

Publisher: Independently Published

ISBN: 9781980914815

Category:

Page: 203

View: 1316

The Data Scientist's Book of Quotes includes over 300 insightful and inspiring quotes from the world's leading Data Science thought leaders and key influencers across the world, including Andrew Ng, Bernard Marr, Vincent Granville, Carla Gentry, Cathy O'Neil and Hilary Mason. The Data Scientist role is one of the most pivotal and disruptive roles in today's global marketplace, that is, and will be transforming and revolutionising our business and societal DNA to unrecognisable proportions. The role requires a unique set of hybrid skills, abilities and tools in the areas of mathematics and statistics, computer programming and coding (including databases and visualisation), business and industry knowledge, and being a solid and convincing communicator. In many cases, he/she may be the key driver and flagbearer of creating a data-driven culture of accepting and adapting change to further the organisation's growth potential. This book offers Data Scientists and Data Science professionals - through its contributors - valued insights and essential facts and advice on better understanding the Data Scientist role and its significant importance to uncover and drive insights towards greater growth and innovation for the respective organisation and society as a whole. Topics include: · What is a Data Scientist?· Power and Potential of Data and Data Science· Potential Risks of Data· Challenges within Data· Machine Learning· Deep Learning· Artificial Intelligence· Data Ethics and Data Privacy· Future of Data· End of Chapter Exercises· Data Science - Book and Film Recommendations About the Author Matt Corey is the leader of Change Force, an exclusive Data Scientist Recruitment Practice. He is committed and passionate to helping organisations reach their growth potential through Data Scientists and their respective contributions to making a positive impact within the marketplace and society. He is available for talks and conferences on the subjects of Data Science, Data-Driven Culture and Organisation and the Attraction, Retention, Recruitment and Employee Integration of Data Scientists. Matt lives in London, United Kingdom and you can visit the company website at www.changeforceinc.com

Machine Learning for Hackers

Case Studies and Algorithms to Get You Started

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Author: Drew Conway,John Myles White

Publisher: "O'Reilly Media, Inc."

ISBN: 1449330533

Category: Computers

Page: 324

View: 9242

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research. Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text Use linear regression to predict the number of page views for the top 1,000 websites Learn optimization techniques by attempting to break a simple letter cipher Compare and contrast U.S. Senators statistically, based on their voting records Build a “whom to follow” recommendation system from Twitter data

Data Analytics

Master the Techniques for Data Science, Big Data and Data Analytics

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Author: Robert Keane

Publisher: Createspace Independent Publishing Platform

ISBN: 9781977616555

Category: Big data

Page: 70

View: 1951

Data Analytics Master The Techniques For Data Science, Big Data And Data Analytics If your business is like most, it is already generating a staggering amount of data on a regular basis. Understanding what this data truly means is key to succeeding in the marketplace these days and if you are looking for a way to give yourself an edge then Data Analytics is the book you have been waiting for. Inside you will find the tools you need in order to take full advantage of all of the data that your business is already generating regardless if you are part of a major corporation or if you are a small business that is just starting out. There are currently over a quintillion byte of data being created each and every day and if you aren't considering how you can make the most of your share then you are already losing out to the competition. Inside this book you will find: Everything you need to know to get started completing the right kind of data analysis to benefit your business regardless of what that business is. The best ways to utilize predictive analysis effectively. Easy to use machine learning and regression techniques. The reasons why you need discrete choice models in your life. And more... So, what are you waiting for? Don't get left behind, do your business a favor and buy this book today! Scroll Up And Click The "BUY" Button!

Data Analytics

A Practical Guide to Data Analytics for Business, Beginner to Expert

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Author: James Fahl

Publisher: Createspace Independent Publishing Platform

ISBN: 9781546859543

Category:

Page: 56

View: 8774

Understand Data Analytics and Implement it in Your Business Today Do you want improve your revenue and stop missing out on profit? Do you want to learn about how data analytics in a style and approach that is suitable for you, regardless of your current knowledge? This book not only provides step-by-step guide to data analytics, but teaches you actionable steps to improve your analysis in all environments! Are you ready to learn? If so, Data Analytics: The Ultimate Step-by-Step guide to master emotional intelligence, interpersonal skills, relationships, self-awareness, habits and increase your workplace success.by James Fahl is THE book for you! It covers the most essential topics you must learn to become a master of Data Analytics. What Separates This Book From The Rest? What separates this book from the rest? The unique way you will learn with examples and steps. Many books leave you more confused than before you picked them up, not this book, it's clear concise and implementable. We make it our goal to write this book in plain easy to understand English that anyone can understand. Gone are the days of highly technical language. This allows you to quickly learn topics, and use your new skills immediately. To aid you in learning the topics quickly and effectively this book has been designed to be the ultimate step-by-step guide. Making sure that you're confident and clear with each topic before moving on! You Will Learn The Following: What is Data Analytics? Why use Data Analytics The importance of Data Analytics Types of Data Analytics Explanations of Different models Collecting Data Mistakes to avoid Whether you just want to learn more about Data Analysis or already know but want a step-by-step guide to implement it in your life, this is the book for you! So don't delay it any longer. Take this opportunity and invest in your self by buying this guide now. You will be shocked by how fast you learn about Data Analytics! Don't Delay And Scroll Up To Buy With 1 Click

Analytics

Data Science, Data Analysis and Predictive Analytics for Business

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Author: Daniel Covington

Publisher: Createspace Independent Publishing Platform

ISBN: 9781530135608

Category:

Page: 288

View: 6171

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. Don't you wish to have the power to know what your target consumers are thinking? Won't 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. The contents of this book are designed to help you use data to your advantage to enhance business outcomes! Here's what this book will teach you: Why data is your single most powerful tool How to conduct data analysis to enhance your business Which steps to take in performing predictive analysis What techniques you need to employ to achieve sustainable success PLUS: Regression techniques Machine learning strategies Risk management tips And much, much, more

Social Media Mining

An Introduction

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Author: Reza Zafarani,Mohammad Ali Abbasi,Huan Liu

Publisher: Cambridge University Press

ISBN: 1107018854

Category: Computers

Page: 320

View: 6456

Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.

State Estimation for Robotics

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Author: Timothy D. Barfoot

Publisher: Cambridge University Press

ISBN: 1107159393

Category: Computers

Page: 350

View: 2334

A modern look at state estimation, targeted at students and practitioners of robotics, with emphasis on three-dimensional applications.

Financial Ratios for Executives

How to Assess Company Strength, Fix Problems, and Make Better Decisions

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Author: Michael Rist,Albert J. Pizzica,PENHAGENCO LLC

Publisher: Apress

ISBN: 1484207319

Category: Business & Economics

Page: 148

View: 4490

Financial Ratios for Executives is written specifically with today’s global executive in mind. It makes financial ratios easy to understand and use effectively. This short book will prove invaluable to both financial and non-financial executives looking for easy, intuitive methods to assess corporate health and assist in strategic decision making. Financial Ratios for Executives contains over 100 financial ratios and other useful calculations. It includes ratios that are commonly used, such as return on investment (ROI), return on assets (ROA), return on equity (ROE), economic value added (EVA), and debt-to-equity ratio, just to name a few. It also includes many less-well known—yet powerful—ratios that can provide unparalleled insight into operations, financial management, sales and marketing efforts, and overall performance, among other areas. Using realistic financial and operational data from two fictional companies, the explanation of each ratio includes: Type of ratio Formula for calculating the ratio Description of the ratio Example based on ABC Company or XYZ Company Additional comments or insights In addition to the section on financial ratios, financial experts Michael Rist and Albert Pizzica have included a section on capital budgeting, an understanding of which is essential for both the financial and non-financial executives before they take part in an annual budget meeting or any other business meeting where capital allocation is discussed. It includes the most important tools of finance, such as net present value (NPV), internal rate of return (IRR), payback method, and total cost of ownership. Who gets ahead in the business world? Those who understand the numbers. It’s as simple as that. Financial Ratios for Executives is for those who want to understand how to use financial data to support their initiatives, solve persistent problems, uncover opportunities, bolster company health, and shine in corporate meetings.

Oracle Exadata Expert's Handbook

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Author: Tariq Farooq,Charles Kim,Nitin Vengurlekar,Sridhar Avantsa,Guy Harrison,Syed Jaffar Hussain

Publisher: Addison-Wesley Professional

ISBN: 0133780988

Category: Computers

Page: 544

View: 9705

The Practical, Authoritative, 360-Degree Technical Guide to Oracle Exadata: From Setup to Administration, Optimization, Tuning, and Troubleshooting The blazingly fast Oracle Exadata Database Machine is being embraced by thousands of large-scale users worldwide: by governments, the military, enterprise organizations, cloud service providers, and anyone who needs extreme performance. Now, Oracle Exadata Expert’s Handbook provides authoritative guidance to running Oracle Exadata with maximum reliability, effectiveness, performance, and efficiency. Six renowned Oracle technology experts have brought together core technical information, experience, best practices, and insider tips in a concise reference. Covering both 11g and 12c versions of Oracle Exadata software, they deliver hands-on coverage of best practices, setup, migration, monitoring, administration, performance tuning, and troubleshooting. Whether you’re an Oracle Exadata DBA, DMA, architect, or manager, you need these insights. Get a 360-degree overview of the Oracle Exadata Database Machine Efficiently deploy RAC within the Oracle Exadata ecosystem Fully leverage Storage Cell’s extraordinary performance, via Offloading, Smart Scans, and Hybrid Columnar Compression Manage Exadata with OEM 12c: perform setup, configuration, asset/target discovery, and day-to-day administration Tune Oracle Exadata for even better performance Perform Exadata Backup/Recovery/DR with RMAN and Data Guard Migrate to Oracle Exadata from other platforms Use Oracle Exadata with the ZFS Storage Appliance Consolidate within the Exadata Database Cloud

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

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Author: VINOD CHANDRA S.S.,ANAND HAREENDRAN S.

Publisher: PHI Learning Pvt. Ltd.

ISBN: 8120349342

Category: Computers

Page: 368

View: 8994

Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this text bridges the gaps in knowledge of the seemingly difficult areas of artificial intelligence and machine learning. This book promises to provide the most number of case studies and worked out examples than any other of its genre. The text is written in a highly interactive manner which makes for an avid reading. More into the text, the contents are well placed that it takes off from the introduction to AI, which is followed by heuristics searching and game playing. The machine learning section begins with the basis of learning, and the various association rule learning algorithms. Various types of learning like, reinforced, supervised, unsupervised and statistical are also included with numerous case studies and application exercises. The well explained algorithms and pseudo codes for each topic make this book useful for students. KEY FEATURES • Includes Case studies for each machine learning algorithm • Incorporates day to day examples and pictorial representations for a deeper understanding of the subject • Helps students to create programs easily

Thinking Statistically

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Author: Uri Bram

Publisher: Createspace Independent Pub

ISBN: 9781481173506

Category: Business & Economics

Page: 72

View: 8753

Thinking Statistically is the book that shows you how to think like a statistician, without worrying about formal statistical techniques. Along the way we learn how selection bias can explain why your boss doesn't know he sucks (even when everyone else does); how to use Bayes' Theorem to decide if your partner is cheating on you; and why Mark Zuckerberg should never be used as an example for anything. See the world in a whole new light, and make better decisions and judgements without ever going near a t-test. Think. Think Statistically.

What Is Data Science?

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Author: Mike Loukides

Publisher: "O'Reilly Media, Inc."

ISBN: 1449336094

Category: Computers

Page: 22

View: 7343

We've all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O'Reilly said that "data is the next Intel Inside." But what does that statement mean? Why do we suddenly care about statistics and about data? This report examines the many sides of data science -- the technologies, the companies and the unique skill sets.The web is full of "data-driven apps." Almost any e-commerce application is a data-driven application. There's a database behind a web front end, and middleware that talks to a number of other databases and data services (credit card processing companies, banks, and so on). But merely using data isn't really what we mean by "data science." A data application acquires its value from the data itself, and creates more data as a result. It's not just an application with data; it's a data product. Data science enables the creation of data products.