Mining data requires a deep investment in people and time. How can you be sure you're building the right models? What tools help you connect with the customer's needs? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications. Agile Data shows you how to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library. You'll learn an iterative approach that allows you to quickly change the kind of analysis you're doing, as you discover what the data is telling you. All the example code in this book is available as working Heroku apps. Build an application to mine your own email inbox Use several data structures to extract multiple features from a single dataset, and learn how different perspectives can yield insight Rapidly boot your applications as simple front-ends to key/value stores Add features driven by descriptive and inferential statistics, machine learning, and data visualization Gather usage data and talk to real users to help guide your data-driven exploration You can provide constructive comments on the manuscript through O'Reilly's Open Feedback Publishing System (OFPS). Learn more at .
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About the Author
Russell Jurney cut his data teeth in casino gaming, building web apps to analyze the performance of slot machines in the US and Mexico. After dabbling in entrepreneurship, interactive media and journalism, he moved to silicon valley to build analytics applications at scale at Ning and LinkedIn. He lives on the ocean in Pacifica, California with his wife Kate and two fuzzy dogs.
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总结一下,当数据模式定义严谨,且SQL是唯一的工具时,我们就不会从挖掘数据的角度看待数据,因为视角会被优化过的数据处理工具所支配。严谨的数据格式抑制了我们在数据与直觉之间建立起联系的能力。另一方面,半结构化的数据可以让我们专注于数据本身,通过迭代地操作数据来抽取价值,并转化为产品。在敏捷大数据中选择NoSQL,是因为它让我们具备了上述能力。
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