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Create an Apache Hudi-based near-real-time transactional data lake using AWS DMS, Amazon Kinesis, AWS Glue streaming ETL, and data visualization using Amazon QuickSight

AWS Big Data

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

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Extend your data mesh with Amazon Athena and federated views

AWS Big Data

Clean up To clean up the resources created for this post, complete the following steps: On the Amazon S3 console, empty the bucket athena-federation-workshop-. If you’re using the AWS CLI, delete the objects in the athena-federation-workshop- bucket with the following code. Big Data Architect on Amazon Athena.

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Automate the archive and purge data process for Amazon RDS for PostgreSQL using pg_partman, Amazon S3, and AWS Glue

AWS Big Data

Gain a high-level understanding of AWS Glue and its components by using the following hands-on workshop. Vivek Shrivastava is a Principal Data Architect, Data Lake in AWS Professional Services. He is a big data enthusiast and holds 14 AWS Certifications.

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Innovate What’s Next: How Living Labs Brings Ideas to Life

CIO Business Intelligence

We are centered around co-creating with customers and promoting a systematic and scalable innovation approach to solve real-world customers problems—similar to Toyota leveraging Infosys Cobalt to modernize its vehicle data warehouse into a next-generation data lake on AWS. .

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Introducing Amazon EMR on EKS job submission with Spark Operator and spark-submit

AWS Big Data

In the following code, replace the EKS endpoint as well as the S3 bucket then run the script: /bin/spark-submit --class ValueZones --master k8s://EKS-ENDPOINT --conf spark.kubernetes.namespace=data-team-a --conf spark.kubernetes.container.image=608033475327.dkr.ecr.us-west-1.amazonaws.com/spark/emr-6.10.0:latest amazonaws.com/spark/emr-6.10.0:latest

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Week in the Life of an Analyst at Gartner US IT Symposium (virtual) 2021

Andrew White

Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Specific Vendor Questions 5.

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