Book Image

Practical Data Analysis - Second Edition

By : Hector Cuesta, Dr. Sampath Kumar
Book Image

Practical Data Analysis - Second Edition

By: Hector Cuesta, Dr. Sampath Kumar

Overview of this book

Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
Table of Contents (21 chapters)
Practical Data Analysis - Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Platform for data processing


A data processing architecture requires a lot of technologies and tools for jobs scheduling until data streaming. A few years ago, installing all the tools required for data processing. Now we may implement the entire environment in just one step. Data companies such as Cloudera, Hortonworks, and MapR provide us with a complete setup of data environment in a Virtual Machine for a single-node cluster and a Docker container (automates the deployment of Linux applications inside software containers) for multi-node cluster.

Many data analytics applications need to process large datasets in batch post-processing or live streaming. For a data scientist, the time to set up a complete environment is a priority, and installing a ready setup platform is the best way to get hands on into the action. One of the main advantages here is that if you are working with either a single-node cluster or a multi-node cluster, the programming of Apache Spark projects are independent...