AWS Big Data

OCTOBER 14, 2024

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes.

Metadata 96

Metadata Data Lake Modeling Data Warehouse 96

AWS Big Data

OCTOBER 12, 2023

The integration between AWS Step Functions and Amazon EMR Serverless makes it easier to manage and orchestrate big data workflows. Karthik Prabhakar is a Senior Big Data Solutions Architect for Amazon EMR at AWS. Now, with the support for “Run a Job (.sync)” Summarized output is then written to Amazon S3 bucket.

Big Data 124

Big Data Data-driven Management Visualization 124

AWS Big Data

APRIL 12, 2023

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). To learn more and get started with EMR on EKS, try out the EMR on EKS Workshop and visit the EMR on EKS Best Practices Guide page. Amazon EMR 6.10

Testing 92

Testing Big Data Metadata Optimization 92

AWS Big Data

APRIL 11, 2023

ElastiCache manages the real-time application data caching, allowing your customers to experience microsecond response times while supporting high-throughput handling of hundreds of millions of operations per second. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

Forecasting 90

Forecasting Management IoT Data-driven 90

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. This ensures that the data is suitable for training purposes.

Data Lake 97

Data Lake Analytics Snapshot Data Quality 97

AWS Big Data

FEBRUARY 6, 2023

To run the scripts, refer to the Amazon MWAA analytics workshop. format(S3_BUCKET_NAME), 's3://{}/data/aggregated/green'.format(S3_BUCKET_NAME), To learn more and get hands-on experience, start with the Amazon MWAA analytics workshop and then use the scripts in the GitHub repo to gain more observability of your DAG run.

Management 96

Management Interactive Publishing Metadata 96

AWS Big Data

JULY 6, 2023

It has not been specifically designed for heavy data transformation tasks. It’s scalable and cost-effective, and can be adapted to other ETL and data processing use cases. You can find hands-on labs to improve your knowledge with AWS Workshops. You also use AWS Glue to consolidate the files produced by the parallel tasks.

Machine Learning 142

Machine Learning Visualization IoT Digital Transformation 142