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

Understanding data

Data generally tells a story. However, this is not obvious just from looking at the data. To understand data, we need to be able to ask certain questions and get answers from the data. Asking the right questions in itself requires a great deal of domain knowledge and experience. Once the questions are framed, getting the answers from the data is the next crucial task. Data exploration is an iterative journey because getting answers to questions generally leads to more questions, and then one has to answer these new questions using data.

We will look at the following two important techniques for understanding and exploring data:

  • Statistical methods: Looking at the properties of data at an aggregate level
  • Visual methods: Looking at the properties of data using visual methods

In fact, in many real scenarios, both of these methods are used in conjunction with...