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Training versus Inference
by Paul Debeasi | February 14, 2019
Few data-driven technologies provide greater opportunity to derive value from Internet of Things (IoT) initiatives as machine learning. The accelerated growth of data captured from the sensors in IoT solutions...
Machine Learning Integration Options
by Paul Debeasi | January 30, 2019
Machine learning projects are inherently different from traditional IT projects in that they are significantly more heuristic and experimental, requiring skills spanning multiple domains, including statistical analysis, data analysis and...
Architect Machine Learning with IoT
by Paul Debeasi | January 25, 2019
Developers with no data science experience are now able to integrate Machine Learning (ML) with IoT. As the number of IoT endpoints proliferate, the need for organizations to understand how...
Gartner’s Cool Vendors in AI for Banking and Investment Services, 2018
by Moutusi Sau | May 2, 2018
The interest in AI among CIOs of banking and investment services is close to the peak of hype right now. The Cool Vendors in this document are applying AI-based technologies...
Personalized Marketing in the Age of Weaponized Data
by Andrew Frank | April 2, 2018
The pace of events unfolding in the volatile world of data-driven marketing and privacy has outstripped the market’s ability to process them. Last week’s Adobe Summit in Las Vegas, a...
Programmatic Advertising's Next Big Adventure
by Andrew Frank | March 8, 2018
We need a holiday, so let's celebrate the 10th birthday of programmatic advertising. We can call it 10 because 10 years ago, Google announced it was buying DoubleClick for $3.1 billion, effectively...
What Makes AI Business Cases So Different?
by Moutusi Sau | February 9, 2018
Moutusi Sau | February 9, 2018
Artificial Intelligence is everywhere right now. If you are the decision maker in your organization and have been told...
New Data and Analytics Research: Infonomics and Data Security, and Data Science/ML project Success
by Andrew White | December 1, 2017
Nigel Shen and colleagues just published Six Pitfalls to Avoid When Planning Data Science and Machine Learning Projects.
Organizational and process pitfalls in data science and machine learning projects could inadvertently...
New Data and Analytics Research: Data Mgt, Data Science, Analytics, and Self-Service Data Integration
by Andrew White | November 16, 2017
Adam Ronthal and colleagues just published: Toolkit: RFP Template for Data Management Solutions for Analytics.
This request for proposal template gives data and analytics leaders a starting point to define requirements and...
New Data and Analytics Research: Toolkit: RFP for Data Science and Machine-Learning Platforms
by Andrew White | August 24, 2017
Peter Krensky and colleagues just published Toolkit: RFP for Data Science and Machine-Learning Platforms.
This Toolkit contains request for proposal templates for data science and machine-learning platforms. These templates represent a...
