Showing results for "Big data" in Data Science

The volumes of data we now access can give unparalleled abilities to make predictions, respond to customer demand and solve problems. But Big Brother’s shadow hovers over it. Though big data can set us free and enhance our lives, it has the potential to create an underclass and a totalitarian state. With big data ever-present, you can’t afford to ignore it. Acclaimed science writer Brian Clegg - a habitual early adopter of new technology (and the owner of the second-ever copy of Windows in the UK) - brings big data to life.

Big data knows where you've been and who your friends are. It knows what you like and what makes you angry. It can predict what you'll buy, where you'll be the victim of crime and when you'll have a heart attack. Big data knows you better than you know yourself, or so it claims. But how well do you know big data? You've probably seen the phrase in newspaper headlines, at work in a marketing meeting, or on a fitness-tracking gadget. But can you understand it without being a Silicon Valley nerd who writes computer programs for fun? Yes. Yes, you can.

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

This audiobook has lots of valuable, eye-opening information about data analytics, which will help you understand the concept of data mining, data collection, big data analytics for business, and business intelligence concepts. With this audiobook, not only will you understand all the internal nitty-gritties about data analytics, you will also understand why data analytics is changing the business arena. You’ll realize that the high-performance analytics will enable you to do stuff that you never thought about before.

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

This new edition - more than 50 percent new and revised - is a significant update from the previous one and reveals how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics, such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.

"Big Data" is on the covers of Science, Nature, The Economist, and Wired magazines, on the front pages of the Wall Street Journal and The New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure.

From technology, media, and retail to sport teams, government agencies, and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety, and so much more. Organized for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved, and the processes put in place to make it practical, as well as the technical details, challenges, and lessons learned from each unique scenario.

In this book, Michael Smith and Rahul Telang, experts on entertainment analytics, show how the success of House of Cards upended the film and TV industries - and how companies like Amazon and Apple are changing the rules in other entertainment industries, notably publishing and music. We're living through a period of unprecedented technological disruption in the entertainment industries.

If you are a budding analyst or want to freshen up on your concepts, this book is for you. It has all the basic information you need to help you become a data analyst or scientist.

In From Big Data to Big Profits, Russell Walker investigates the use of Big Data to stimulate innovations in operational effectiveness and business growth. Walker examines the nature of Big Data and how businesses can use it to create new monetization opportunities. Using case studies of Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leaders in the use of Big Data, Walker explores how digital platforms such as mobile apps and social networks are changing the nature of customer interactions and the way Big Data is created and used by companies.

This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data.

Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of big data. Listeners are guided through tried-and-true methodologies for getting more out of data and using it to the utmost advantage. This audiobook describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding big data, all while guiding listeners toward better decision-making from the perspective of a data scientist.

Did you know the value of data usage has increased job opportunities but that there are few specialists? These days, everyone is aware of the role data can play, whether it is an election, business, or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This audiobook presents you with a step-by-step approach to data science as well as secrets only known by the best data scientists.

Big data - the enormous amount of data that is created as virtually every movement, transaction, and choice we make becomes digitized - is revolutionizing business. Offering real-world insight and explanations, this audiobook provides a roadmap for organizations looking to develop a profitable big data strategy...and reveals why it's not something they can leave to the I.T. department. Think Bigger is an essential resource for anyone who wants to ensure that their company isn't left in the dust.

This is a collection of two comprehensive books about data analytics and data mining.

Interest in applying analytics, machine learning, and artificial intelligence to sales and marketing has grown dramatically, with no signs of slowing down. This book provides essential guidance to apply advanced analytics and data mining techniques to real-world business applications.

Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values, and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits, and identify new business opportunities.

Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves. The way toward learning starts with perceptions or data - for example, models, direct understanding, or guidance, so as to search for designs in data and settle on better choices later, depending on the models that we give.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.