Event: February 7-9, 2017

Spark Summit East 2017

Hear Alpine Data's VP of Engineering, Lawrence Spracklen, speak about Spark Autotuning.

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In the News
Spark gets automation: Analyzing code and tuning clusters in production
Spark gets automation: Analyzing code and tuning clusters in production
June 1, 2017
Alpine Data pointed to the fact that Spark is extremely sensitive to how jobs are configured and resourced, requiring data scientists to have a deep understanding of both Spark and the configuration and utilization of the Hadoop cluster being used...

The Self-Driving Enterprise: How AI Will Make Apps and Us Work Better
The Self-Driving Enterprise: How AI Will Make Apps and Us Work Better
March 9, 2017
AI has begun to take hold in the everyday, in the form of Siri, Alexa and autonomous vehicles. But if identifying the nearest Korean BBQ and driving me there is all that the future of AI promises, well that’s a damn shame...

“Above the Trend Line” – Machine Learning at Spark Summit
“Above the Trend Line” – Machine Learning at Spark Summit
February 28, 2017
The company presented details about technology they have developed for auto-tuning Spark jobs. Spark can deliver amazing performance allowing data scientists to apply complex machine learning algorithms on large data sets and quickly deliver actionable insights...

Artificial intelligence in the real world: What can it actually do?
Artificial intelligence in the real world: What can it actually do?
February 22, 2017
AI is mainstream these days. The attention it gets and the feelings it provokes cover the whole gamut: from hands-on technical to business, from social science to pop culture, and from pragmatism to awe and bewilderment...

From PMML to PFA: A Way Forward for Deploying Predictive Analytics
From PMML to PFA: A Way Forward for Deploying Predictive Analytics
February 3, 2017
Training models thrives on large batches of data and, while performance is very important to address processing needs, no one has expectations that the training is instantaneous. Models are often refined rapidly with a focus on experimentation...

Big50 2017 Tech Predictions – Part 2: Machine Learning and Automation
Big50 2017 Tech Predictions – Part 2: Machine Learning and Automation
January 12, 2017
A big problem with the Business Intelligence (BI) space has been how thoroughly information gets siloed within organizations. Data tends to get locked in specific applications accessible only by a handful of select employees in a single department...