AI / Analytics

7 AWS AI / Analytics terms and services covered in certification exams, with exam-focused explanations.

Amazon Bedrock

A fully managed service for accessing foundation models from multiple providers (Claude, Titan, etc.) through a unified API without hosting models yourself. Build text generation, chatbots, and RAG applications. Appears in recent exam questions as the choice for integrating generative AI into applications.

Amazon SageMaker

A managed service covering the full ML workflow: data preparation, model training, and deployment. Handles everything from preprocessing to publishing inference endpoints. Tested as the complete platform for building and operating custom ML models.

Amazon Kinesis

A streaming data service for real-time collection and processing of logs, IoT data, and clickstreams. Includes Data Streams and Data Firehose. The answer when continuous real-time data processing is required rather than batch processing.

AWS Glue

A serverless ETL (Extract, Transform, Load) service with a Data Catalog for automatic schema discovery. Streamlines pre-analysis data preparation. Tested as a component of data lake ingestion and transformation pipelines.

Amazon Athena

A serverless analytics service that runs standard SQL queries directly against data in S3 — no server provisioning, billed per data scanned. Frequently tested for 'analyze S3 data directly with minimal setup' scenarios.

Amazon QuickSight

A cloud-native BI (Business Intelligence) service that visualizes data as interactive dashboards and charts. Connects to various data sources. Appears as the visualization tool for presenting analysis results to stakeholders.

Amazon Comprehend

An NLP machine learning service that automatically extracts sentiment, language, key phrases, and named entities from text via API — no model building required. Tested for text analytics use cases such as review sentiment analysis and document classification.

Last updated: 2026-06-24

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