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

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

Details

*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-20817488669)

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.

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