Showing results for "Big data" in Computers & Technology

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.

Like it or not, your every move is being watched and analyzed. Consumers' identities are being stolen, and a person's every step is being tracked and stored. What once might have been dismissed as paranoia is now a hard truth, and privacy is a luxury few can afford or understand. In this explosive yet practical book, Kevin Mitnick illustrates what is happening without your knowledge - and he teaches you "the art of invisibility".

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.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a loan, how much we pay for insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: everyone is judged according to the same rules and bias is eliminated. And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated and incontestable, even when they're wrong. Most troubling, they reinforce discrimination.

Do you want to understand what big data is all about, but you don’t get all the hype? Are you intrigued by the idea of building a career around big data and data science, but you just don’t understand it? If so, this audiobook could be what you are looking for. If you know nothing about big data now, you will come away with a good overview of the subject and how it integrates into the other hot technologies of the day widely adopted by business, such as artificial intelligence, predictive analytics, and machine learning.

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.

We live in an incredible period in history. The computer revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.

In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally - hiring, driving, paying bills, even choosing romantic partners - that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology.

What to Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on artificial intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans, it raises profound questions on the future of work and how companies compete.

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.

Machines are able to interpret and understand human beings, and also interpret the data that is fed to them because of artificial intelligence. So, what is artificial intelligence? If you have been reading the basics, you will know that artificial intelligence is a human being’s attempt to make a machine smart enough to handle processes that a human being would normally do. It is not easy to do this, since you will need to understand the system and also learn the required programming languages to instruct the computer to behave in the required manner.

Big Data is everywhere. It shapes our lives in more ways than we know and understand. This comprehensive introduction unravels the complex terabytes that will continue to shape our lives in ways imagined and unimagined.

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.