Historically, the primary role of data in the industrial setting has been fault detection and diagnosis (FDD). Today, companies are increasingly looking to their datasets as valuable assets to influence their revenue and profit. The availability of always-on connectivity and low-cost sensing platforms, combined with new machine-learning and artificial intelligence capabilities, enables companies to transform previously low-valued records into a high-value resource. When combined with modern machine learning, these assets can immediately be combined to generate increased profits, higher savings, and new revenue sources.
Drawing on concepts from his recent report, Finding Profit in Your Organization’s Data, Cameron Royce Turner shares examples of companies that are transforming data exhaust into data products with a demonstrable lift in revenue, savings, and new revenue and outlines best practices and pitfalls in using historical industrial data with modern machine-learning techniques.
Combining an extensive background in product research, data analysis, program management, and software development, Cameron Turner cofounded the Data Guild in 2013. Previously, he founded ClickStream Technologies, which was acquired by Microsoft. While at Microsoft, Cameron managed the Windows Telemetry team, responsible for all inbound data for all Microsoft products and partners. He is an active member of and speaker at a number of Bay Area tech groups, including Churchill Club, SOFTECH, the Young CEOs Club, the CIO Roundtable, and BayCHI. Cameron holds a BA in architecture from Dartmouth College, an MBA from Oxford University, and an MS in statistics from Stanford University.
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