Analytic data pipelines have existed since businesses turned operational data into reports. Leading-edge big data and machine learning applications have evolved common design patterns in order to accommodate the ability to assemble the applications with mix and match flexibility.
George has led conference panels with prominent thought leaders in cloud infrastructure and big data.He has been profiled on the front page of the Wall Street Journal and published as a guest author in a major overview of the evolution of cloud computingin The Economist.
Previously, George was the lead enterprise software analyst for Credit Suisse First Boston, one of the top investment banks serving the technology sector.Prior to being an analyst, George was a product manager on Notes at Lotus Development.
George received his BA in economics from Harvard University.
Latest posts by George Gilbert (see all)
- Recipe for Machine Learning Applications: Getting Started - 17 Jan 2017
- Machine Learning Pipeline: Chinese Menu of Building Blocks - 30 Nov 2016
- 2017 Big Data & Machine Learning Predictions - 30 Nov 2016