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Amazon Kinesis Data Streams lets you ingest streaming data (like IoT, app logs, clickstreams) in real time. You can write applications with Kinesis Client Library or use managed integrations to process the data with AWS Lambda or Kinesis Data Analytics. It’s built for high-throughput, low-latency processing.
Amazon Redshift is a fully managed, petabyte-scale data warehouse. It’s optimized for OLAP (analytical) queries. You load structured data from sources like S3, RDS, or DynamoDB, then run complex SQL queries quickly using columnar storage, massively parallel processing (MPP), and result caching.
AWS Glue is a serverless ETL service. You use it to:
Amazon Kinesis Data Firehose is a fully managed way to capture, transform, and deliver streaming data to targets like S3, Redshift, OpenSearch, or Splunk. You don’t write custom consumers or worry about scaling; Firehose handles batching, compression, encryption, and automatic delivery.
Amazon S3 has multiple storage classes:
You can use Lifecycle policies to move data automatically between classes, reducing cost as data ages.
AWS Data Pipeline and AWS Glue Workflows let you orchestrate and automate data movement and transformations. You define data sources, destinations, and processing steps, and AWS handles scheduling, retries, and dependencies. (Newer designs often use Step Functions or Managed Airflow as well.)
Amazon Elastic MapReduce (EMR) is a managed cluster platform for big data frameworks such as Apache Hadoop, Spark, Hive, Presto, and others. It provides flexible compute (EC2 or Spot) and storage options (S3, EBS, or HDFS). It reduces the operational burden of installing, configuring, and scaling these clusters.
AWS Lake Formation simplifies creating secure data lakes on top of S3. It lets you:
Amazon Athena is a serverless interactive query service. You define schemas pointing to files in S3 (often using Glue Data Catalog), then run SQL queries on structured, semi-structured, or unstructured data. You pay per query, based on the amount of data scanned, and there’s no infrastructure to manage.
Amazon CloudWatch monitors metrics, logs, and events across data services. For cost and performance insights, you can also use AWS Cost Explorer, Redshift Console (query performance), Kinesis Monitoring, or Glue Job metrics. Together they help identify bottlenecks, errors, and cost-saving opportunities.
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We’ve received your request for an AI Readiness, Safety, and Security Assessment.
A member of our advisory team will review your submission and reach out within 1–2 business days to discuss next steps. This initial conversation is exploratory and focused on understanding your context, not selling services.