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| data science for dummies: Data Science For Dummies Lillian Pierson, 2021-08-20 Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today. |
| data science for dummies: Data Science For Dummies Lillian Pierson, 2015-03-09 Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization.--Provided by publisher. |
| data science for dummies: Python for Data Science For Dummies John Paul Mueller, Luca Massaron, 2019-01-25 The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction. |
| data science for dummies: Data Science Programming All-in-One For Dummies John Paul Mueller, Luca Massaron, 2020-01-09 Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s! |
| data science for dummies: Predictive Analytics For Dummies Anasse Bari, Mohamed Chaouchi, Tommy Jung, 2014-03-06 Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies. |
| data science for dummies: Data Science Strategy For Dummies Ulrika Jägare, 2019-06-12 All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value. |
| data science for dummies: Big Data For Dummies Judith S. Hurwitz, Alan Nugent, Fern Halper, Marcia Kaufman, 2013-04-02 Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization. |
| data science for dummies: Machine Learning For Dummies John Paul Mueller, Luca Massaron, 2021-02-09 One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world. |
| data science for dummies: Storage Area Networks For Dummies Christopher Poelker, Alex Nikitin, 2009-01-09 If you’ve been charged with setting up storage area networks for your company, learning how SANs work and managing data storage problems might seem challenging. Storage Area Networks For Dummies, 2nd Edition comes to the rescue with just what you need to know. Whether you already a bit SAN savvy or you’re a complete novice, here’s the scoop on how SANs save money, how to implement new technologies like data de-duplication, iScsi, and Fibre Channel over Ethernet, how to develop SANs that will aid your company’s disaster recovery plan, and much more. For example, you can: Understand what SANs are, whether you need one, and what you need to build one Learn to use loops, switches, and fabric, and design your SAN for peak performance Create a disaster recovery plan with the appropriate guidelines, remote site, and data copy techniques Discover how to connect or extend SANs and how compression can reduce costs Compare tape and disk backups and network vs. SAN backup to choose the solution you need Find out how data de-duplication makes sense for backup, replication, and retention Follow great troubleshooting tips to help you find and fix a problem Benefit from a glossary of all those pesky acronyms From the basics for beginners to advanced features like snapshot copies, storage virtualization, and heading off problems before they happen, here’s what you need to do the job with confidence! |
| data science for dummies: People Analytics For Dummies Mike West, 2019-03-19 Maximize performance with better data Developing a successful workforce requires more than a gut check. Data can help guide your decisions on everything from where to seat a team to optimizing production processes to engaging with your employees in ways that ring true to them. People analytics is the study of your number one business asset—your people—and this book shows you how to collect data, analyze that data, and then apply your findings to create a happier and more engaged workforce. Start a people analytics project Work with qualitative data Collect data via communications Find the right tools and approach for analyzing data If your organization is ready to better understand why high performers leave, why one department has more personnel issues than another, and why employees violate, People Analytics For Dummies makes it easier. |
| data science for dummies: Data Mining For Dummies Meta S. Brown, 2014-09-04 Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business's entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn't take a data scientist to gain this advantage, and empowers average business people to start shaping a process relevant to their business's needs. In this book, you'll learn the hows and whys of mining to the depths of your data, and how to make the case for heavier investment into data mining capabilities. The book explains the details of the knowledge discovery process including: Model creation, validity testing, and interpretation Effective communication of findings Available tools, both paid and open-source Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data. You'll gain the confidence you need to start making data mining practices a routine part of your successful business. If you're serious about doing everything you can to push your company to the top, Data Mining for Dummies is your ticket to effective data mining. |
| data science for dummies: Blockchain Data Analytics For Dummies Michael G. Solomon, 2020-09-02 Get ahead of the curve—learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain. Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big data Discover the power and potential of blockchain analytics Establish data models and quickly mine for insights and results Create data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line! |
| data science for dummies: Microsoft Power BI For Dummies Jack A. Hyman, 2022-02-08 Reveal the insights behind your company’s data with Microsoft Power BI Microsoft Power BI allows intuitive access to data that can power intelligent business decisions and insightful strategies. The question is, do you have the Power BI skills to make your organization’s numbers spill their secrets? In Microsoft Power BI For Dummies, expert lecturer, consultant, and author Jack Hyman delivers a start-to-finish guide to applying the Power BI platform to your own firm’s data. You’ll discover how to start exploring your data sources, build data models, visualize your results, and create compelling reports that motivate decisive action. Tackle the basics of Microsoft Power BI and, when you’re done with that, move on to advanced functions like accessing data with DAX and app integrations Guide your organization’s direction and decisions with rock-solid conclusions based on real-world data Impress your bosses and confidently lead your direct reports with exciting insights drawn from Power BI’s useful visualization tools It’s one thing for your company to have data at its disposal. It’s another thing entirely to know what to do with it. Microsoft Power BI For Dummies is the straightforward blueprint you need to apply one of the most powerful business intelligence tools on the market to your firm’s existing data. |
| data science for dummies: Data Warehousing For Dummies Thomas C. Hammergren, 2009-04-13 Data warehousing is one of the hottest business topics, and there’s more to understanding data warehousing technologies than you might think. Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. Data is probably your company’s most important asset, so your data warehouse should serve your needs. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. You’ll learn to: Analyze top-down and bottom-up data warehouse designs Understand the structure and technologies of data warehouses, operational data stores, and data marts Choose your project team and apply best development practices to your data warehousing projects Implement a data warehouse, step by step, and involve end-users in the process Review and upgrade existing data storage to make it serve your needs Comprehend OLAP, column-wise databases, hardware assisted databases, and middleware Use data mining intelligently and find what you need Make informed choices about consultants and data warehousing products Data Warehousing For Dummies, 2nd Edition also shows you how to involve users in the testing process and gain valuable feedback, what it takes to successfully manage a data warehouse project, and how to tell if your project is on track. You’ll find it’s the most useful source of data on the topic! |
| data science for dummies: Data Driven Marketing For Dummies David Semmelroth, 2013-10-07 Embrace data and use it to sell and market your products Data is everywhere and it keeps growing and accumulating. Companies need to embrace big data and make it work harder to help them sell and market their products. Successful data analysis can help marketing professionals spot sales trends, develop smarter marketing campaigns, and accurately predict customer loyalty. Data Driven Marketing For Dummies helps companies use all the data at their disposal to make current customers more satisfied, reach new customers, and sell to their most important customer segments more efficiently. Identifying the common characteristics of customers who buy the same products from your company (or who might be likely to leave you) Tips on using data to predict customer purchasing behavior based on past performance Using customer data and marketing analytics to predict when customers will purchase certain items Information on how data collected can help with merchandise planning Breaking down customers into segments for easier market targeting Building a 360 degree view of a customer base Data Driven Marketing For Dummies assists marketing professionals at all levels of business in accelerating sales through analytical insights. |
| data science for dummies: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| data science for dummies: Probability For Dummies Deborah J. Rumsey, 2018-05-25 Packed with practical tips and techniques for solving probability problems Increase your chances of acing that probability exam -- or winning at the casino! Whether you're hitting the books for a probability or statistics course or hitting the tables at a casino, working out probabilities can be problematic. This book helps you even the odds. Using easy-to-understand explanations and examples, it demystifies probability -- and even offers savvy tips to boost your chances of gambling success! Discover how to * Conquer combinations and permutations * Understand probability models from binomial to exponential * Make good decisions using probability * Play the odds in poker, roulette, and other games |
| data science for dummies: Business Intelligence For Dummies Swain Scheps, 2011-02-04 You're intelligent, right? So you've already figured out that Business Intelligence can be pretty valuable in making the right decisions about your business. But you’ve heard at least a dozen definitions of what it is, and heard of at least that many BI tools. Where do you start? Business Intelligence For Dummies makes BI understandable! It takes you step by step through the technologies and the alphabet soup, so you can choose the right technology and implement a successful BI environment. You'll see how the applications and technologies work together to access, analyze, and present data that you can use to make better decisions about your products, customers, competitors, and more. You’ll find out how to: Understand the principles and practical elements of BI Determine what your business needs Compare different approaches to BI Build a solid BI architecture and roadmap Design, develop, and deploy your BI plan Relate BI to data warehousing, ERP, CRM, and e-commerce Analyze emerging trends and developing BI tools to see what else may be useful Whether you’re the business owner or the person charged with developing and implementing a BI strategy, checking out Business Intelligence For Dummies is a good business decision. |
| data science for dummies: Artificial Intelligence For Dummies John Paul Mueller, Luca Massaron, 2018-03-16 Step into the future with AI The term Artificial Intelligence has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever! |
| data science for dummies: Data Visualization For Dummies Mico Yuk, Stephanie Diamond, 2014-01-21 A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more! Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography Enables you to present vast amounts of data in ways that won't overwhelm your audience Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember. |
| data science for dummies: Beginning Programming with Python For Dummies John Paul Mueller, 2018-02-13 The easy way to learn programming fundamentals with Python Python is a remarkably powerful and dynamic programming language that's used in a wide variety of application domains. Some of its key distinguishing features include a very clear, readable syntax, strong introspection capabilities, intuitive object orientation, and natural expression of procedural code. Plus, Python features full modularity, supporting hierarchical packages, exception-based error handling, and modules easily written in C, C++, Java, R, or .NET languages, such as C#. In addition, Python supports a number of coding styles that include: functional, imperative, object-oriented, and procedural. Due to its ease of use and flexibility, Python is constantly growing in popularity—and now you can wear your programming hat with pride and join the ranks of the pros with the help of this guide. Inside, expert author John Paul Mueller gives a complete step-by-step overview of all there is to know about Python. From performing common and advanced tasks, to collecting data, to interacting with package—this book covers it all! Use Python to create and run your first application Find out how to troubleshoot and fix errors Learn to work with Anaconda and use Magic Functions Benefit from completely updated and revised information since the last edition If you've never used Python or are new to programming in general, Beginning Programming with Python For Dummies is a helpful resource that will set you up for success. |
| data science for dummies: Python All-in-One For Dummies John C. Shovic, Alan Simpson, 2019-05-07 Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox. |
| data science for dummies: Deep Learning For Dummies John Paul Mueller, Luca Massaron, 2019-05-14 Take a deep dive into deep learning Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it. In no time, you’ll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then provides examples of the major deep learning application types. Includes sample code Provides real-world examples within the approachable text Offers hands-on activities to make learning easier Shows you how to use Deep Learning more effectively with the right tools This book is perfect for those who want to better understand the basis of the underlying technologies that we use each and every day. |
| data science for dummies: Adobe Analytics For Dummies David Karlins, Eric Matisoff, 2019-04-02 Use Adobe Analytics as a marketer —not a programmer! If you're a marketer in need of a non-technical, beginner's reference to using Adobe Analytics, this book is the perfect place to start. Adobe Analytics For Dummies arms you with a basic knowledge of the key features so that you can start using it quickly and effectively. Even if you're a digital marketer who doesn't have their hands in data day in and day out, this easy-to-follow reference makes it simple to utilize Adobe Analytics. With the help of this book, you'll better understand how your marketing efforts are performing, converting, being engaged with, and being shared in the digital space. Evaluate your marketing strategies and campaigns Explore implementation fundamentals and report architecture Apply Adobe Analytics to multiple sources Succeed in the workplace and expand your marketing skillset The marketing world is continually growing and evolving, and Adobe Analytics For Dummies will help you stay ahead of the curve. |
| data science for dummies: Data Analytics for Absolute Beginners: a Deconstructed Guide to Data Literacy Oliver Theobald, 2019-07-21 While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence |
| data science for dummies: Data Science Field Cady, 2020-12-30 Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation. |
| data science for dummies: Data Lakes For Dummies Alan R. Simon, 2021-07-14 Take a dive into data lakes “Data lakes” is the latest buzz word in the world of data storage, management, and analysis. Data Lakes For Dummies decodes and demystifies the concept and helps you get a straightforward answer the question: “What exactly is a data lake and do I need one for my business?” Written for an audience of technology decision makers tasked with keeping up with the latest and greatest data options, this book provides the perfect introductory survey of these novel and growing features of the information landscape. It explains how they can help your business, what they can (and can’t) achieve, and what you need to do to create the lake that best suits your particular needs. With a minimum of jargon, prolific tech author and business intelligence consultant Alan Simon explains how data lakes differ from other data storage paradigms. Once you’ve got the background picture, he maps out ways you can add a data lake to your business systems; migrate existing information and switch on the fresh data supply; clean up the product; and open channels to the best intelligence software for to interpreting what you’ve stored. Understand and build data lake architecture Store, clean, and synchronize new and existing data Compare the best data lake vendors Structure raw data and produce usable analytics Whatever your business, data lakes are going to form ever more prominent parts of the information universe every business should have access to. Dive into this book to start exploring the deep competitive advantage they make possible—and make sure your business isn’t left standing on the shore. |
| data science for dummies: Data Science Using Python and R Chantal D. Larose, Daniel T. Larose, 2019-04-09 Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R. Data science is hot. Bloomberg called data scientist “the hottest job in America.” Python and R are the top two open-source data science tools in the world. In Data Science Using Python and R, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. Data Science Using Python and R is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining. Further, exciting new topics such as random forests and general linear models are also included. The book emphasizes data-driven error costs to enhance profitability, which avoids the common pitfalls that may cost a company millions of dollars. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. Readers will therefore have plenty of opportunity to test their newfound data science skills and expertise. In the Hands-on Analysis exercises, readers are challenged to solve interesting business problems using real-world data sets. |
| data science for dummies: Python Crash Course Eric Matthes, 2015-11-01 Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: –Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal –Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses –Work with data to generate interactive visualizations –Create and customize Web apps and deploy them safely online –Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3 |
| data science for dummies: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| data science for dummies: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms |
| data science for dummies: The R Inferno Patrick Burns, 2011 An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for most data analysis tasks. R is free, open-source, and has thousands of contributed packages. It is used in such diverse fields as ecology, finance, genomics and music. If you are using spreadsheets to understand data, switch to R. You will have safer -- and ultimately, more convenient -- computations. |
| data science for dummies: Data Science and Machine Learning Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman, 2019-11-20 Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code |
| data science for dummies: Data Science in Theory and Practice Maria Cristina Mariani, Osei Kofi Tweneboah, Maria Pia Beccar-Varela, 2021-10-12 DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia. |
| data science for dummies: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| data science for dummies: Statistics for Big Data For Dummies Alan Anderson, 2015-08-31 The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word statistics alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining—without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed. |
| data science for dummies: Excel Data Analysis For Dummies Paul McFedries, 2018-11-13 Take Excel to the next level Excel is the world’s leading spreadsheet application. It’s a key module in Microsoft Office—the number-one productivity suite—and it is the number-one business intelligence tool. An Excel dashboard report is a visual presentation of critical data and uses gauges, maps, charts, sliders, and other graphical elements to present complex data in an easy-to-understand format. Excel Data Analysis For Dummies explains in depth how to use Excel as a tool for analyzing big data sets. In no time, you’ll discover how to mine and analyze critical data in order to make more informed business decisions. Work with external databases, PivotTables, and Pivot Charts Use Excel for statistical and financial functions and data sharing Get familiar with Solver Use the Small Business Finance Manager If you’re familiar with Excel but lack a background in the technical aspects of data analysis, this user-friendly book makes it easy to start putting it to use for you. |
| data science for dummies: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| data science for dummies: Cybersecurity For Dummies Joseph Steinberg, 2019-10-15 Protect your business and family against cyber attacks Cybersecurity is the protection against the unauthorized or criminal use of electronic data and the practice of ensuring the integrity, confidentiality, and availability of information. Being cyber-secure means that a person or organization has both protected itself against attacks by cyber criminals and other online scoundrels, and ensured that it has the ability to recover if it is attacked. If keeping your business or your family safe from cybersecurity threats is on your to-do list, Cybersecurity For Dummies will introduce you to the basics of becoming cyber-secure! You’ll learn what threats exist, and how to identify, protect against, detect, and respond to these threats, as well as how to recover if you have been breached! The who and why of cybersecurity threats Basic cybersecurity concepts What to do to be cyber-secure Cybersecurity careers What to think about to stay cybersecure in the future Now is the time to identify vulnerabilities that may make you a victim of cyber-crime — and to defend yourself before it is too late. |
| data science for dummies: Advances in Financial Machine Learning Marcos Lopez de Prado, 2018-01-23 Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
