The Human Face Of Big Data

The authors invited more than 100 journalists worldwide to use photographs, charts and essays to explore the world of big data and its growing influence on our lives and society.

The human suffering associated with mental illness is something that more than one in five Canadians face at some point in their life.

A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.

A pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for). Today’s decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the “digitalization” of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterprise vision of performance monitoring and optimization.

Lyle Hertzog and his friends Marilla and Dave are the Qwikpick Adventure Society, three kids who seek out adventure in their seemingly quiet hometown of Crickenburg. On the hunt for their next big adventure—something to top the Fountain of Poop, if that’s even possible—the kids overhear a construction worker telling his buddies about a rat with a human face he saw in the basement of an old research facility. The decision is unanimous: the next adventure for the Qwikpick Society is on! But when their trip to find the rat doesn’t go quite as expected, the trio gets in big trouble. Will the second adventure for the Qwikpick Society also be their last?

Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.

The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. 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. Organised 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 it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Intelligence gathering is in a state of flux. Enabled by massive computing power, new modes of communications analysis now touch the lives of citizens around the globe – not just those considered suspicious or threatening. Big Data Surveillance and Security Intelligence reveals the profound shift to “big data” practices that security agencies have made in recent years, as the increasing volume of information challenges traditional ways of gathering intelligence. In this astute collection, leading academics, civil society experts, and regulators debate the pressing questions this trend raises about civil liberties, human rights, and privacy protection in Canada.