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

Applying Statistics and Hypothesis Testing

This chapter provides an overview of statistical methods used in data analysis and covers techniques for deriving meaningful insights from data. We will first look at some basic statistical techniques used to gain a better understanding of data before moving on to more advanced methods that are used to compute statistics on vectorized data instead of simple scalar data.

This chapter also covers the various techniques for generating random numbers. Random numbers play a significant part in data analysis because they help us work with sample data in much smaller datasets. A good random sample selection ensures that smaller datasets can act as a good representative of the much bigger dataset.

We will also gain an understanding of hypothesis testing and look at some Scala tools readily available to make this task easier.

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