Big Data


Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Big Data: A Revolution That Will Transform How We Live, Work, and Think
Hadoop: The Definitive Guide
Designing Data-Intensive Applications
Big Data: Principles and best practices of scalable realtime data systems
Learning Spark: Lightning-Fast Big Data Analysis
Dataclysm: Who We Are (When We Think No One's Looking)
Big Data Now: Current Perspectives from O'Reilly Radar
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't
Spark: The Definitive Guide: Big Data Processing Made Simple
MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
New Space Capitalism by Rainer ZitelmannWeb Hacking Arsenal by Rafay  BalochAI Doctor by Ronald M. RazmiAI 2041 by Kai-Fu LeeA Brief History of Intelligence by Max Solomon Bennett
Future Technology (nonfiction)
172 books — 324 voters
Superintelligence by Nick BostromThe Data Garden And Other Data Allegories  by Paul Daniel JonesLeading Change by John P. KotterSwitch by Chip HeathMeasure What Matters by John Doerr
Data Consulting
27 books — 3 voters

Designing Data-Intensive Applications by Martin KleppmannDatabase Internals by Alex PetrovStreaming Systems by Tyler AkidauConcurrency by Dahlia MalkhiMaking Sense of Stream Processing by Martin Kleppmann
Data Engineering Group
24 books — 5 voters
Designing Data-Intensive Applications by Martin KleppmannData Science for Business by Foster ProvostNoSQL Distilled by Pramod J. SadalageBig Data by Nathan MarzDatabase Design for Mere Mortals by Hernandez Michael J.
All about Data
24 books — 6 voters


Science, once a triumph of human intelligence, now seems headed into a morass of rhetoric about the power of big data and new computational methods, where the scientists' role is now as a technician, essentially testing existing theories on IBM Blue Gene supercomputers.    But computers don't have insights. People do. And collaborative efforts are only effective when individuals are valued. Someone has to have an idea. Turing at Bletchley knew—or learned—this, but the lessons have been lost in t ...more
Erik J. Larson, The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do

A reminder that Goodreads is owned by Amazon, and everything you do here supports Big Data and corporate surveillance. You should be concerned, especially if you read books about liberation. A friend recommended StoryGraph, a Black-owned independent alternative. Download your data and GTFO.
Anonymous

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