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Data Jujitsu: The Art of Turning Data into Product

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Acclaimed data scientist DJ Patil details a new approach to solving problems in Data Jujitsu.Learn how to use a problem's "weight" against itself to:Break down seemingly complex data problems into simplified partsUse alternative data analysis techniques to examine themUse human input, such as Mechanical Turk, and design tricks that enlist the help of your users to take short cuts around tough ... Read more

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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
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Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data warehouses, and data lakes. There are cloud services, on-premises services, and embedded databases. What
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Oracle RMAN Pocket Reference is a handy guide for DBAs who intend to use Oracle Recovery Manager for database backup and recovery. Because Recovery Manager (RMAN) is a relatively new tool, many DBAs are just becoming familiar with it. They will welcome a timely book that explains clearly and concisely how to use RMAN for common backup and recovery tasks that are infrequent, yet extremely vital.The
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Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges
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If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis—from wrangling data and generating statistics to
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Bad Data Handbook

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What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems.From cranky storage to poor representation to misguided policy, there are many paths to
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Whether you have some experience with Tableau software or are just getting started, this manual goes beyond the basics to help you build compelling, interactive data visualization applications. Author Ryan Sleeper, one of the worldâ??s most qualified Tableau consultants, complements his web posts and instructional videos with this guide to give you a firm understanding of how to use Tableau to ... Read more

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Recommended For You

Data Modeling & Design eBooks

Data Jujitsu: The Art of Turning Data into Product

What Is Data Science?

Disruptive Possibilities: How Big Data Changes Everything

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Building Data Science Teams

Deep Learning for Finance

TinyML

Innovative Tableau

Unifying Business, Data, and Code

Stream Processing with Apache Spark

Machine Learning for Time-Series with Python

HBase: The Definitive Guide

Spark: The Definitive Guide

Hands-On Large Language Models

Oracle RMAN Pocket Reference

Deep Learning

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Mastering Apache Cassandra - Second Edition

Building Machine Learning Powered Applications

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Data Wrangling with Python

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Practical Tableau