October 2017
Intermediate to advanced
91 pages
1h 48m
English
book
Data Warehousing in the Age of Artificial Intelligence
by Gary Orenstein, Conor Doherty, Mike Boyarski, Eric Boutin
Content preview from Data Warehousing in the Age of Artificial Intelligence
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Chapter 10. Real-Time Machine Learning Use Cases
Overview of Use Cases
Real-time data warehouses help companies take advantage of modern technology and are critical to the growth of machine learning (ML), big data, and artificial intelligence (AI). Companies looking to stay current need a data warehouse to support them.
Choosing the Correct Data Warehouse
If your company is looking to benefit from ML and needs data analytics in real time, choosing the correct data warehouse is critical to success. When deciding which data warehouse is best for your workload, here are a series of questions to ask yourself:
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Do you need to ingest data quickly?
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Do you need to run fast queries?
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Do you need to have concurrent workloads?
The use cases discussed in this chapter highlight how the combination of these needs lead to amazing business results.
Energy Sector
In this section, you will learn about two different companies in the energy sector and the work they’re doing to drive equipment efficiency and pass along savings to customers.
Goal: Anomaly Detection for the Internet of Things
At a leading independent energy company during its drilling explorations, drill operators are constantly making decisions for where, when, and in what direction to adjust, with the goal of decreasing the time it takes to drill a well.
Approach: Real-Time Sensor Data to Manage Risk
Each drill bit on a drilling rig can cost millions of dollars, and the entire operation can cost millions per day, operating ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.