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)
Free Chapter
Section 1: Scala and Data Analysis Life Cycle
Section 2: Advanced Data Analysis and Machine Learning
Section 3: Real-Time Data Analysis and Scalability


This chapter provided a high-level overview of the Scala programming language. We looked at some of the object-oriented and functional programming aspects of Scala using applied examples. This chapter touched upon the array, list, and map functionalities of the Scala collection API. These data structures have numerous uses in the data analysis life cycle. The chapter also provided the necessary information to set up and install the Scala tools that are essential for understanding and applying the topics covered in subsequent chapters. Finally, a quick overview of the data-centric Scala libraries was provided. We will be making use of these libraries in the next few chapters to solve specific data life cycle problems.

In the next chapter, we will look at the data analysis life cycle and associated tasks.