埃雷兹·艾登  1980年，埃雷兹·艾登出生于美国布鲁克林，精通希伯来语和匈牙利语。本科就读于普林斯顿大学，主修数学、物理学和哲学专业，毕业后考入叶史瓦大学历史学专业，攻读硕士学位。  2009年，在哈佛-麻省理工博德研究所攻读博士学位的艾登被《麻省理工科技评论》提名为世界上前35位年龄小于35岁的创新者。  博士毕业后，艾登先是任职于哈佛大学科研学会，后任谷歌客座教授，随后成为贝勒医学院和莱斯大学的助理教授，领导基因组架构研究中心。2012年，他因和同事一起发明了探测基因3D折叠方式的技术，获得美国总统青年科技奖（PECASE），这是美国政府颁给青年科学家的最高荣誉。 让-巴蒂斯特·米歇尔  数据科学公司量化实验室（Quantified Labs）创始人，哈佛大学副研究员，曾任谷歌客座教授。2010年在哈佛获得博士学位。2012年入选TED...(展开全部)

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.

Learn everything you need to know to manage data as a product and shift toward a more modular and decentralized socio-technical data architecture to deliver business value in an incremental, measurable, and sustainable way Key Features Leverage data-as-product to unlock the modular platform potential and fix flaws in traditional monolithic architectures Learn how to identify, implement, and operate data products throughout their life cycle Design and

For readers of Ace and Belly of the Beast A Black queer feminist exploration of asexuality--and an incisive interrogation of the sex-obsessed culture that invisibilizes and ignores asexual and A-spec identity. Everything you know about sex and asexuality is (probably) wrong. The notion that everyone wants sex--and that we all have to have it--is false. It's intertwined with our...(展开全部)

For readers of Ace and Belly of the Beast A Black queer feminist exploration of asexuality--and an incisive interrogation of the sex-obsessed culture that invisibilizes and ignores asexual and A-spec identity. Everything you know about sex and asexuality is (probably) wrong. The notion that everyone wants sex--and that we all have to have it--is false. It's intertwined with our...(展开全部)

The Jamaican writer and cultural theorist Sylvia Wynter is best known for her diverse writings that pull together insights from theories in history, literature, science, and black studies, to explore race, the legacy of colonialism, and representations of humanness. Sylvia Wynter: On Being Human as Praxis is a critical genealogy of Wynter’s work, highlighting her insights on ho...(展开全部)

This book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations.

There's been a massive amount of innovation in data tools over the last few years, thanks to a few key trends: * *Learning from the web*. Techniques originally developed by website developers coping with scaling issues are increasingly being applied to other domains. * *CS+?=$$$*. Google have proven that research techniques from computer science can be effective at solving prob...(展开全部)

Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively.

Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively.