Book Image

Big Data Architect's Handbook

By : Syed Muhammad Fahad Akhtar
Book Image

Big Data Architect's Handbook

By: Syed Muhammad Fahad Akhtar

Overview of this book

The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not an easy task. The prime job for any big data architect is to build an end-to-end big data solution that integrates data from different sources and analyzes it to find useful, hidden insights. Big Data Architect’s Handbook takes you through developing a complete, end-to-end big data pipeline, which will lay the foundation for you and provide the necessary knowledge required to be an architect in big data. Right from understanding the design considerations to implementing a solid, efficient, and scalable data pipeline, this book walks you through all the essential aspects of big data. It also gives you an overview of how you can leverage the power of various big data tools such as Apache Hadoop and ElasticSearch in order to bring them together and build an efficient big data solution. By the end of this book, you will be able to build your own design system which integrates, maintains, visualizes, and monitors your data. In addition, you will have a smooth design flow in each process, putting insights in action.
Table of Contents (21 chapters)
Preface
Free Chapter
1
Why Big Data?
2
Big Data Environment Setup
3
Hadoop Ecosystem
4
NoSQL Database
5
Off-the-Shelf Commercial Tools
6
Containerization
7
Network Infrastructure
8
Cloud Infrastructure
9
Security and Monitoring
10
Frontend Architecture
11
Backend Architecture
12
Machine Learning
13
Artificial Intelligence
14
Elasticsearch
15
Structured Data
16
Unstructured Data
17
Data Visualization
18
Financial Trading System
19
Retail Recommendation System
20
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Data Visualization

Data is a very powerful weapon. If used properly, it can lead to many victories. In the business world, victory means a happy customer while company remain competitive in the market. Sometimes data presented is in numerical form or in tabular form, which makes it very difficult to find a pattern or to visually analyze it.

On the other hand, if the same data is presented to you in graphical form, such as in the form of different types of charts or an interactive dashboard, most of the time it becomes easy to visualize what to look for, and it may lead to meaningful discoveries to help in a better understanding and analysis of the data.

In this chapter, we will go through the following data visualization libraries, which will help to present data in the form of different types of visual elements, such as charts:

  • Matplotlib
  • D3.js

Let's start with the first...