Analyzing Log Data with Spark and Looker

May 18, 2016
Machines are constantly generating data. Unlocking the value of log files has historically lived in the realm of batch processing. However, emerging technologies have dramatically reduced the latency of event pipelines and have improved interactive analysis and querying. In this webinar, Scott Hoover, Looker Data Scientist, and Daniel Mintz, Chief Data Evangelist at Looker, discuss the specifics of setting up a modern pipeline that collects, processes, and analyzes high-volume, machine-generated data. Topics covered include: - Popular collection mechanisms - Hands-on log-parsing example in Spark - How to utilize Looker to glean insights from event data See recorded webinar at https://info.looker.com/h/i/254518884-analyzing-log-data-with-spark-and-looker
Previous Video
Federating Data with Presto to Build an Enterprise Data Portal
Federating Data with Presto to Build an Enterprise Data Portal

In the struggle to meet diverse demands of their organization, large companies often store their data in mu...

Next Video
Analyzing Log Data with Spark and Looker
Analyzing Log Data with Spark and Looker

Machines are constantly generating data. Unlocking the value of log files has historically lived in the rea...