Category: Learning Levels

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service that makes it easy to connect to your data, create interactive dashboards and reports, and share these with tens of thousands of users, either within QuickSight or embedded in your application or website. QuickSight recently launched a new major version of its Embedding SDK […]

Thousands of customers rely on Amazon Redshift to build data warehouses to accelerate time to insights with fast, simple, and secure analytics at scale and analyze data from terabytes to petabytes by running complex analytical queries. Organizations create data marts, which are subsets of the data warehouse and usually oriented for gaining analytical insights specific […]

The value of data is time sensitive. Real-time processing makes data-driven decisions accurate and actionable in seconds or minutes instead of hours or days. Change data capture (CDC) refers to the process of identifying and capturing changes made to data in a database and then delivering those changes in real time to a downstream system. […]

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. This post […]

Amazon Athena is a serverless, interactive analytics service built on open-source frameworks, supporting open-table and file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and over 25 data sources, including on-premises […]

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. A solution to this problem is to use AWS Database Migration Service (AWS DMS) for migrating historical and real-time transactional data into the data lake. You can then […]

In this post, we present a solution that can integrate with your front-end application to query data from Amazon S3 using an Athena synchronous API invocation. With this solution, you can add a layer of abstraction to your application on direct Athena API calls and promote the access using the WebSocket API developed with Amazon API Gateway. The query results are returned back to the application as Amazon S3 presigned URLs.

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. It adds tables to compute engines including Spark, Trino, PrestoDB, Flink, and Hive using a high-performance table format that works just like a SQL table. Iceberg has […]

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data. As more users start querying data in a data warehouse, access control is paramount to protect valuable organizational […]

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. The inability to accurately find and analyze data from disparate sources represents a potential efficiency killer for everyone from data scientists, medical researchers, academics, to financial and government analysts. Conventional […]