This collection represents the full spectrum of data-related content we’ve published on O’Reilly Radar over the last year. Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas:
Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself.
The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research.
Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena.
The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.
Table of contents
- Big Data Now
1. Data Science and Data Tools
- What is data science?
The SMAQ stack for big data
- Scraping, cleaning, and selling big data
- Data hand tools
- Hadoop: What it is, how it works, and what it can do
- Four free data tools for journalists (and snoops)
- The quiet rise of machine learning
- Where the semantic web stumbled, linked data will succeed
- Social data is an oracle waiting for a question
- The challenges of streaming real-time data
2. Data Issues
- Why the term “data science” is flawed but useful
- Why you can’t really anonymize your data
- Big data and the semantic web
- Big data: Global good or zero-sum arms race?
- The truth about data: Once it’s out there, it’s hard to control
3. The Application of Data: Products and Processes
- How the Library of Congress is building the Twitter archive
- Data journalism, data tools, and the newsroom stack
- The data analysis path is built on curiosity, followed by action
- How data and analytics can improve education
- Data science is a pipeline between academic disciplines
- Big data and open source unlock genetic secrets
- Visualization deconstructed: Mapping Facebook’s friendships
- Data science democratized
4. The Business of Data
- There’s no such thing as big data
- Building data startups: Fast, big, and focused
- Data markets aren’t coming: They’re already here
- An iTunes model for data
- Data is a currency
- Big data: An opportunity in search of a metaphor
- Data and the human-machine connection
- Title: Big Data Now: Current Perspectives from O'Reilly Radar
- Release date: August 2011
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781449315184
You might also like
Tiny Python Projects
The projects are tiny, but the rewards are big: each chapter in Tiny Python Projects challenges …
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. …
Essential Algorithms, 2nd Edition
A friendly introduction to the most useful algorithms written in simple, intuitive English The revised and …
40 Algorithms Every Programmer Should Know
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …