Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
The Artificial Intelligence Infrastructure Workshop

You're reading from   The Artificial Intelligence Infrastructure Workshop Build your own highly scalable and robust data storage systems that can support a variety of cutting-edge AI applications

Arrow left icon
Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209848
Length 732 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (6):
Arrow left icon
Bas Geerdink Bas Geerdink
Author Profile Icon Bas Geerdink
Bas Geerdink
Chinmay Arankalle Chinmay Arankalle
Author Profile Icon Chinmay Arankalle
Chinmay Arankalle
Kunal Gera Kunal Gera
Author Profile Icon Kunal Gera
Kunal Gera
Kevin Liao Kevin Liao
Author Profile Icon Kevin Liao
Kevin Liao
Gareth Dwyer Gareth Dwyer
Author Profile Icon Gareth Dwyer
Gareth Dwyer
Anand N.S. Anand N.S.
Author Profile Icon Anand N.S.
Anand N.S.
+2 more Show less
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface
1. Data Storage Fundamentals 2. Artificial Intelligence Storage Requirements FREE CHAPTER 3. Data Preparation 4. The Ethics of AI Data Storage 5. Data Stores: SQL and NoSQL Databases 6. Big Data File Formats 7. Introduction to Analytics Engine (Spark) for Big Data 8. Data System Design Examples 9. Workflow Management for AI 10. Introduction to Data Storage on Cloud Services (AWS) 11. Building an Artificial Intelligence Algorithm 12. Productionizing Your AI Applications Appendix

Raw Data

The raw data layer contains the one-to-one copies of files from the source systems. The copies are stored to make sure that any data that arrives is preserved in its original form. After storing the raw data, some checks can be done to make sure that the data can be processed by the rest of the ETL pipeline, such as a checksum.

Security

We'll look at data security first. All modern software and data systems must be secure. By security requirements, we mean all aspects related to ensuring that the data in a system cannot be viewed or deleted by unauthorized people or systems. It entails identity and access management, role-based access, and data encryption.

Basic Protection

In any data project, security is a key requirement. The basic level of data protection is to require a username-password combination for anyone who can access the data: customers, developers, analysts, and so on. In all cases, the passwords should be evaluated against a strong password policy...

You have been reading a chapter from
The Artificial Intelligence Infrastructure Workshop
Published in: Aug 2020
Publisher: Packt
ISBN-13: 9781800209848
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime