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  • Hands-On Data Analysis with Scala
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Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala

By : Gupta
5 (3)
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Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala

5 (3)
By: 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
7
Section 2: Advanced Data Analysis and Machine Learning
10
Section 3: Real-Time Data Analysis and Scalability

Cost considerations

As the size of data grows, there are many factors to consider to manage costs effectively. Some of the costs associated with data are direct, while others are indirect. A clear and well-defined data strategy plays a central role in managing these costs and maximizing the value of data.

There are multiple points of view to consider when looking at the cost:

  • Data storage
  • Data governance

Data storage

Not at all data is created equal. Some types of data have more value than the others. The value of data might also be sensitive to its age and might start to decrease as the data ages. At the same time, some data is accessed more frequently than others. All of these factors, and many more, determine how the...

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