The amount of data generated by IoT, smart devices, cloud applications, and social is growing exponentially. You need ways to easily and cost-effectively analyze all of this data with minimal time-to-insight, regardless of the data source. Join Orit as she dives deep into the basics of data lake and lake house patterns.
What is a Data Lake: https://aws.amazon.com/big-data/datalakes-and-analytics/what-is-a-data-lake/?nc=sn&loc=2
Lake house architecture blogpost: https://aws.amazon.com/blogs/big-data/build-a-lake-house-architecture-on-aws/
Amazon Kinesis Data Firehose: https://docs.aws.amazon.com/firehose/latest/dev/what-is-this-service.html
AWS Glue: https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html
Amazon Athena: https://docs.aws.amazon.com/athena/latest/ug/what-is.html
Amazon QuickSight: https://docs.aws.amazon.com/quicksight/latest/user/welcome.html
Amazon Redshift: https://docs.aws.amazon.com/redshift/latest/mgmt/welcome.html
Check out more resources for architecting in the #AWS cloud:
#AWS #AmazonWebServices #CloudComputing #BackToBasics
Publisher: Amazon Web Services
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