There’s no question that Andy Jassy’s presentation at the AWS re:Invent 2015’s first keynote address covered a lot of ground across the spectrum of cloud technology. But his introduction of Amazon’s new cloud-based business intelligence solution, Amazon QuickSight, captured a lot of attention.
Part of the trick is capitalizing on the sheer volume of raw data your AWS-based operation might already have available. There’s a good chance that you’re already at least reasonably invested in storage (S3), data warehousing (DynamoDB, Redshift), streaming data (EMR, Kinesis), and big data analytics (Amazon Machine Learning): why not bring them all together to see what extra value you can access?
What might really help QuickSight take off, though, is the fact that Amazon has placed business intelligence squarely in the hands of the people who need the answers the most. You’ll get full functionality right from the browser interface without the need for data professionals (in fact, at this point there isn’t even a native API). Or, in Amazon’s own words:
Just log in, point to a data source, and create your first visualization in minutes
Slide stacks of visualizations – or “stories” as AWS calls them – can be saved and shared among colleagues, adding to the value of the insights.
QuickSight’s in-memory calculation engine (called SPICE, for “Super-fast Parallel In-memory Computation Engine“) can easily scale to smoothly deliver visualizations to hundreds of thousands of users in a particular organization.
Here are some notes based on the Q&A session:
Still to come: support for streaming datasets for real-time and for GEO data, and ODBC/JDBC and Salesforce external data connections.
Explore the Analytics tools provided by AWS, including QuickSight, Elastic Map Reduce (EMR), Data Pipeline, Elasticsearch, Kinesis, Amazon Machine Learning in the Cloud Academy’s Analytics Fundamentals for AWS course.
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