Tag: aws-data-analytics

Amazon QuickSight can replace expensive BI tools or become a costly mistake — depending on how you use it. Here is the production guide that covers SPICE, multi-tenancy, cost control, and the cases where QuickSight is the wrong choice.

Virtual data modeling on AWS creates a read-only semantic layer over your data lake or warehouse — without copying data. Here is a practical guide to when it works, when it backfires, and how to implement it correctly with Athena, Redshift, Glue, and Lake Formation.

Kinesis Data Streams and Amazon MSK both handle real-time streaming on AWS, but they serve different architectures. Here is how to choose between them for your workload.

Redshift Serverless removes cluster management but is not always cheaper. Here is exactly when to choose Serverless, when to stay Provisioned, and how to calculate the cost difference.

Amazon OpenSearch Service powers search, log analytics, and time-series workloads on AWS. Here are the architecture patterns and cost levers that matter most in production.

Kinesis Data Streams combined with Lambda and DynamoDB is the simplest path to a real-time data pipeline on AWS. Here is the complete architecture, code patterns, and operational guidance.

AWS EMR has three deployment modes — Serverless, EC2, and EKS — and the right choice depends on your job patterns, team expertise, and cost constraints. Here is how to decide.

AWS Glue 5.1 brings Apache Iceberg 1.10.0, Spark 3.5.6, and Delta Lake 3.3.2. Here is how to use these together to build a production lakehouse on AWS — with time travel, ACID transactions, and schema evolution.

AWS Glue and dbt solve different transformation problems. Glue runs Spark for large-scale ETL across any data source. dbt runs SQL transforms inside your data warehouse. Here is how to choose — and when to use both.

Athena charges per TB of data scanned. The right partitioning, compression, and table format can cut your Athena bill by 90%. Here is exactly how to do it.

Embedding QuickSight dashboards in your SaaS product gives every customer analytics without building a BI layer from scratch. Here is the complete implementation guide — embedding types, authentication, row-level security, and cost.

Amazon Managed Service for Apache Flink (formerly Kinesis Data Analytics) is the fully managed way to run stateful stream processing on AWS. Here is everything you need to know to use it in production.