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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

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800209848
Length 732 pages
Edition 1st Edition
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Authors (6):
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Bas Geerdink Bas Geerdink
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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.
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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

2. Artificial Intelligence Storage Requirements

Activity 2.01: Requirements Engineering for a Data-Driven Application

Solution

  1. Taxi data (GPS locations, current rides), HR system data (drivers), map data, phone calls, and email records with customer interaction, website, and app input (queries for rides, page visits).

    The layers for the solution are as follows:

    Figure 2.16: Layers in a data-driven application

  2. There are daily updates from source systems: raw -> historical -> analytics layer.

    There is a streaming data pipeline for events from taxis.

  3. The minimum set of metadata to capture is the source, owner, date, type, and the transformations that have been applied to the data records. This metadata can be used for auditing, security and consent management, and lineage reports.
  4. The solution will probably receive an AIC rating of 323 or higher since it contains sensitive and private data (personnel records, GPS locations, and so on). Therefore, security...
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