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
Other Books You May Enjoy
Structured Data

Up until a few years ago, companies were only storing data that was important to them and directly linked either with their business or customers. These types of data are mostly structural in form, which means that each of the data records in the dataset available will have similar attributes. In most cases, they are also linked together and have different types of relationship between them.

There are many commercial and open source relational databases available in the market that help us to store and manipulate structural data. Example of these databases are MySQL, Microsoft SQL, and PostgreSQL. Some of them are free to use for both individual or commercial use, but some of them require licenses. The license cost varies from provider to provider based on the features they provide and support. The number of users and IoT devices is increasing rapidly, resulting...