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

Data extraction

Data extraction or delivery is the act of making raw data available to an enterprise system for usage. This raw data could be originating from a system outside of the enterprise or could have been created by an internal system. There are two ways in which data can be delivered:

  • Pull: Data is fetched by the data consumer from the source system
  • Push: The data producer delivers the data to the consumer

Both of these mechanisms are used extensively in enterprises for exchanging data. The majority of legacy systems and applications use a pull-based approach for data delivery; however, with the growing need of near real-time availability of data, there is a shift toward push-based data delivery.

Let's look at both of these mechanisms in more detail.