Real-world patterns for continuously deployed advanced analytics
How can we drive more data pipelines, advanced analytics, and machine learning models into production? How can we do this both faster and more reliably? Graham Gear draws on real-world processes and systems to explain how it's possible to apply continuous delivery techniques to advanced analytics, realizing business value earlier and more safely.
|Talk Title||Real-world patterns for continuously deployed advanced analytics|
|Speakers||Graham Gear (Cloudera)|
|Conference||Strata + Hadoop World|
|Conf Tag||Make Data Work|
|Date||December 6-8, 2016|
The core drivers of a Hadoop deployment have traditionally been scale, flexibility and economics. Flexibility is often touted as the ability to add a new dimension, dataset, or complex line of questioning without investing in a expensive, difficult multimonth project. It is true that Hadoop’s flexibility gives us the ability to collapse these projects into tasks and shorten the window by which they can be deliverer, but how far can we push this? Graham Gear draws on real-world processes and systems to explain how it’s possible to apply continuous delivery techniques to advanced analytics, realizing business value earlier and more safely. Along the way Graham shows just how far we can push the flexibility of a modern advanced analytics platform. Topics include: