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Practical Data Science by Mario RojasНазвание: Practical Data Science
Автор: Mario Rojas
Издательство: Amazon.com Services LLC
Год: 2021
Страниц: 866
Язык: английский
Формат: pdf, azw3, epub
Размер: 12.4 MB

I will help you to recognize the basics of data science tools and their influence on modern data lake development. You will discover the techniques for transforming a data vault into a data warehouse bus matrix. I will explain the use of Spark, Mesos, Akka, Cassandra, and Kafka, to tame your data science requirements. I will guide you in the use of elastic search and MQTT (MQ Telemetry Transport), to enhance your data science solutions. I will help you to recognize the influence of R as a creative visualization solution. I will also introduce the impact and influence on the data science ecosystem of such programming languages as R, Python, and Scala.

This data science ecosystem has a series of tools that you use to build your solutions. This environment is undergoing a rapid advancement in capabilities, and new developments are occurring every day. I will explain the tools I use in my daily work to perform practical data science. Next, I will discuss the following basic data methodologies.

Apache Spark is an open source cluster computing framework. Originally developed at the AMP Lab of the University of California, Berkeley, the Spark code base was donated to the Apache Software Foundation, which now maintains it as an open source project. This tool is evolving at an incredible rate. SAP, Tableau, and Talend now support Spark as part of their core software stack. Cloudera, Hortonworks, and MapR distributions support Spark as a native interface. Spark offers an interface forprogramming distributed clusters with implicit data parallelism and fault-tolerance. Spark is a technology that is becoming a de-facto standard for numerous enterprise-scale processing applications.

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