Book Image

Hands-On Data Analysis with Scala

By : Rajesh Gupta
Book Image

Hands-On Data Analysis with Scala

By: Rajesh Gupta

Overview of this book

Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights
Table of Contents (14 chapters)
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Section 1: Scala and Data Analysis Life Cycle
Section 2: Advanced Data Analysis and Machine Learning
Section 3: Real-Time Data Analysis and Scalability

Data Analysis Life Cycle

Data is ubiquitous, and is increasingly playing a significant role in every aspect of our lives, from helping us to make informed decisions to building intelligent systems.

Data is created when a computer system captures and records some kind of observation or activity; this is true of any example of data being electronically recorded, from something as simple as an Internet of Things (IoT) device recording temperature at a given point in time at a specific location to something more complex, such as a human being completing an online purchase. In this context, we can think of data as a raw material consisting of information of value.

This raw data in itself could be extremely useful. Interesting insights can be obtained by processing this data and combining it with other types of data. Data processing helps turn this information into insights that can...