Back to Basics: Building an Efficient Data Lake
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Опубликовано 29 сентября 2021, 17:40
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.
Additional Resources:
What is a Data Lake: aws.amazon.com/big-data/datala...
Lake house architecture blogpost: aws.amazon.com/blogs/big-data/...
Amazon Kinesis Data Firehose: docs.aws.amazon.com/firehose/l...
AWS Glue: docs.aws.amazon.com/glue/lates...
Amazon Athena: docs.aws.amazon.com/athena/lat...
Amazon QuickSight: docs.aws.amazon.com/quicksight...
Amazon Redshift: docs.aws.amazon.com/redshift/l...
Check out more resources for architecting in the #AWS cloud:
amzn.to/3qXIsWN
#AWS #AmazonWebServices #CloudComputing #BackToBasics #DataLake
Additional Resources:
What is a Data Lake: aws.amazon.com/big-data/datala...
Lake house architecture blogpost: aws.amazon.com/blogs/big-data/...
Amazon Kinesis Data Firehose: docs.aws.amazon.com/firehose/l...
AWS Glue: docs.aws.amazon.com/glue/lates...
Amazon Athena: docs.aws.amazon.com/athena/lat...
Amazon QuickSight: docs.aws.amazon.com/quicksight...
Amazon Redshift: docs.aws.amazon.com/redshift/l...
Check out more resources for architecting in the #AWS cloud:
amzn.to/3qXIsWN
#AWS #AmazonWebServices #CloudComputing #BackToBasics #DataLake
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