Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conve...

Solving Equations with MATLAB provides a concise, practical introduction to solving algebraic equations using MATLAB. Taken from Peter I. Kattan's bestselling book MATLAB for Beginners: A Gentle Approach, this approximately twenty-page tutorial guides readers through the numerical and symbolic solution of linear, quadratic, and highly nonlinear equations, as well as systems of simultaneous linear and nonlinear equations. Using clear solved examples, the ebook show...

This concise article of twenty pages takes you on a short tour of MATLAB. The article covers briefly some selected MATLAB commands. The presentation is made in the form of solved examples showing the exact MATLAB commands used and the output. At the end of the article, there are about 19 unsolved exercises for students to practice. The solutions to all the exercises are also provided. This article is taken form the bestselling book "MATLAB for Beginners: A Gentle Approach."

Five or six years ago, analysts working with big datasets made queries and got the results back overnight. The data world was revolutionized a few years ago when Hadoop and other tools made it possible to getthe results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics.

Succeeding with data isn’t just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.You’ll not only learn examples of how Google, LinkedIn, and Fa...

In an age where everything is measurable, understanding big data is an essential. From creating new data-driven products through to increasing operational efficiency, big data has the potential to make your organization both more competitive and more innovative.As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven.Wr...

Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking.Base...

"Data is here, it's growing, and it's powerful." Author Cathy O'Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail. Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.

In the early days of the 20th century, department store magnate JohnWanamaker famously said, "I know that half of my advertising doesn'twork. The problem is that I don't know which half." That remainedbasically true until Google transformed advertising with AdSense basedon new uses of data and analysis. The same might be said about healthcare and it's poised to go through a similar transformation as newtools, techniques, and data sources come on line. Soon we'll makepolicy and resource dec...

Excel macros. Everybody wants to learn them. You're not a programmer though. How is a non technical user going to learn how to program? You do want to use macros to make your work easier but are you really going to sit down with a huge programming textbook and work your way through every. single. boring. page? Like most people, you'll start with great enthusiasm and vigor but after a few chapters, the novelty wears off. It gets boring.I'm going to try and change that and make learn...

Consumer networks have revolutionized the way companies understand and reach their customers, making possible intricate measurement and accurate prediction at every step of every transaction. The same revolution is underway in our infrastructure, where new generations of sensor-laden power plants, cars and medical devices will generate vast quantities of data that could bring about improvements in quality, reliability and cost. Big machines will enter the modern era of big data, where they...

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 databa...