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Data Warehousing in the Age of Artificial Intelligence
book

Data Warehousing in the Age of Artificial Intelligence

by Gary Orenstein, Conor Doherty, Mike Boyarski, Eric Boutin
October 2017
Intermediate to advanced
91 pages
1h 48m
English
O'Reilly Media, Inc.
Content preview from Data Warehousing in the Age of Artificial Intelligence

Chapter 1. The Role of a Modern Data Warehouse in the Age of AI

Actors: Run Business, Collect Data

Applications might rule the world, but data gives them life. Nearly 7,000 new mobile applications are created every day, helping drive the world’s data growth and thirst for more efficient analysis techniques like machine learning (ML) and artificial intelligence (AI). According to IDC,1 AI spending will grow 55% over the next three years, reaching $47 billion by 2020.

Applications Producing Data

Application data is shaped by the interactions of users or actors, leaving fingerprints of insights that can be used to measure processes, identify new opportunities, or guide future decisions. Over time, each event, transaction, and log is collected into a corpus of data that represents the identity of the organization. The corpus is an organizational guide for operating procedures, and serves as the source for identifying optimizations or opportunities, resulting in saving money, making money, or managing risk.

Enterprise Applications

Most enterprise applications collect data in a structured format, embodied by the design of the application database schema. The schema is designed to efficiently deliver scalable, predictable transaction-processing performance. The transactional schema in a legacy database often limits the sophistication and performance of analytic queries. Actors have access to embedded views or reports of data within the application to support recurring or operational ...

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Publisher Resources

ISBN: 9781491997963