A deeper look into SparkSQL, DataFrames, and Data Sources w/IBM and Galvanize

*Note: Expedite check in at Galvanize,

register here in advance (https://www.eventbrite.com/e/a-deeper-look-into-of-sparksql-dataframes-and-data-sources-wibm-galvanize-tickets-20817418459)

Agenda:
6:00 pm to 6:40 pm - Food, Drink, Networking
6:40 pm to 7:30 pm - TBA
7:30 pm to 8:20 pm - A deeper look into SparkSQL, DataFrames, and Data Sources
8:20 pm to 9 pm - Networking
9:00 pm - Closing Time

A deeper look into SparkSQL, DataFrames, and Data Sources

See how SparkSQL makes it easier to aggregate and analyze all your data, and do it faster (both develop and run). Agenda Basics of SparkSQL and DataFrames So whats a Data Source Demo - Creating a dataframe Write less code with SparkSQL - joins, aggregations The variety of sources with Data Sources Whats next

Meet your speaker:

Consulting architect at IBM, working in development and implementation of data and information management systems. Current focus is on integrating "big data" with existing enterprise data management systems.

Prerequisites:

Assumes understanding of Spark and SQL basic concepts.

Why should someone attend this talk?

If you're hoping to get a better understanding of SparkSQL and role it plays in analytics and information management.