Amazon Redshift: Ingestion to Insights in Under 30 Minutes with Treasure Data

Amazon Redshift puts the power of a petabyte-scale analytics database in your hands for pennies on the dollar. If you can get your data into it, that is. In order to maximize its efficiency, Redshift imposes strict requirements on schema that can be challenging meet - especially with real-world data streaming in from thousands of web sessions and mobile apps. Getting your data cleaned, enriched, and loaded into Redshift can take multiple MapReduce jobs and several custom scripts that need to be updated each time your input schema changes.

In this webinar, we’ll show you how Treasure Data’s schemaless analytics pipeline cuts through all this red-tape and makes it easy to capture both streaming and bulk event data, clean it with simple SQL processing, and export straight into your Redshift cluster. No MapReduce jobs or S3 buckets required! We’ll also talk about Redshift’s various data types, and how to optimize your clusters for performant queries at scale. Come find out how Treasure Data can get you from Ingestion to Insights on Amazon Redshift in under 30 minutes.

You’ll learn about:

• Various data ingestion methods for Amazon Redshift
• The need for ELT and data enrichment, as opposed to traditional ETL
• How to optimize your Redshift instance for specific queries
• How to transform, enrich, and load mobile and web event data into Redshift with Treasure Data