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Beginning Power BI, 2nd Edition

Beginning Power BI, 2nd Edition

by Dan Clark
348 Pages · 2017 · 21.9 MB · 1,254 Downloads · New!
" You miss 100% of the shots you don’t take. ” ― Wayne Gretzky
Apache Kafka Cookbook
by Saurabh Minni
128 Pages · 2015 · 1.44 MB · 3,802 Downloads · New!
This book will give you details about how to manage and administer your Apache Kafka Cluster.
Architecting HBase Applications
by O'Dell
252 Pages · 2016 · 7.2 MB · 1,081 Downloads · New!
HBase is a remarkable tool for indexing mass volumes of data, but getting started with this distributed database and its ecosystem can be daunting. With this hands-on guide, you’ll learn how to architect, design, and deploy your own HBase applications by examining real-world solutions. Along with HBase principles and cluster deployment guidelines, this book includes in-depth case studies that demonstrate how large companies solved specific use cases with HBase.
Bazaar Version Control
by Janos Gyerik
402 Pages · 2013 · 6.19 MB · 2,159 Downloads · New!
Bazaar is a version control system that enables you to track your changes, browse the history of revisions, or revert to a previous state with ease. You can benefit greatly from the principles and practical uses of version control with Bazaar in any software project.
Beginning Neo4j
by Chris Kemper
153 Pages · 2015 · 2.36 MB · 1,158 Downloads · New!
Beginning Neo4j is your introduction in the world of graph databases, and the benefits they can bring to your applications. Neo4j is the most established graph database on the market, and it’s always improving to bring more of its benefits to you. This book will take you from the installation of Neo4j through to building a full application with Neo4j at its heart, and everything in between.
Beginning PostgreSQL on the Cloud
by Avinash Vallarapu
381 Pages · 2018 · 17 MB · 3,413 Downloads · New!
Bioinformatics with R Cookbook
by Paurush Praveen Sinha
300 Pages · 2014 · 12.4 MB · 2,680 Downloads · New!
Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing, and analyzing biological data. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics.