AWS Big Data Blog

Category: *Post Types

bdb-3883-image001

Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

Our zero-ETL integration with Amazon Redshift facilitates point-to-point data movement to get it ready for analytics, artificial intelligence (AI) and machine learning (ML) using Amazon Redshift on petabytes of data. In this post, we provide step-by-step guidance on how to get started with near real time operational analytics using the Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift.

Amazon DataZone announces integration with AWS Lake Formation hybrid access mode for the AWS Glue Data Catalog

Last week, we announced the general availability of the integration between Amazon DataZone and AWS Lake Formation hybrid access mode. In this post, we share how this new feature helps you simplify the way you use Amazon DataZone to enable secure and governed sharing of your data in the AWS Glue Data Catalog. We also […]

Aura new architecture

How Aura from Unity revolutionized their big data pipeline with Amazon Redshift Serverless

Aura from Unity (formerly known as ironSource) is the market standard for creating rich device experiences that engage and retain customers. In this post, we describe Aura’s successful and swift adoption of Redshift Serverless, which allowed them to optimize their overall bidding advertisement campaigns’ time to market from 24 hours to 2 hours. We explore why Aura chose this solution and what technological challenges it helped solve.

Architecture_Diagram

Automate large-scale data validation using Amazon EMR and Apache Griffin

Many enterprises are migrating their on-premises data stores to the AWS Cloud. During data migration, a key requirement is to validate all the data that has been moved from source to target. This data validation is a critical step, and if not done correctly, may result in the failure of the entire project. However, developing […]

Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. This information empowers end-users to make informed decisions as to whether or not to use specific assets. In this post, we discuss the latest features of Amazon DataZone for data quality, the integration between Amazon DataZone and AWS Glue Data Quality and how you can import data quality scores produced by external systems into Amazon DataZone via API.

Simplify your query management with search templates in Amazon OpenSearch Service

Amazon OpenSearch Service is an Apache-2.0-licensed distributed search and analytics suite offered by AWS. This fully managed service allows organizations to secure data, perform keyword and semantic search, analyze logs, alert on anomalies, explore interactive log analytics, implement real-time application monitoring, and gain a more profound understanding of their information landscape. OpenSearch Service provides the […]

Nexthink scales to trillions of events per day with Amazon MSK

Real-time data streaming and event processing present scalability and management challenges. AWS offers a broad selection of managed real-time data streaming services to effortlessly run these workloads at any scale. In this post, Nexthink shares how Amazon Managed Streaming for Apache Kafka (Amazon MSK) empowered them to achieve massive scale in event processing. Experiencing business […]

Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

In Part 2 of this series, we discussed how to enable AWS Glue job observability metrics and integrate them with Grafana for real-time monitoring. Grafana provides powerful customizable dashboards to view pipeline health. However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool […]

Architecture Diagram for Krones Production Line Monitoring

Krones real-time production line monitoring with Amazon Managed Service for Apache Flink

Krones provides breweries, beverage bottlers, and food producers all over the world with individual machines and complete production lines. This post shows how Krones built a streaming solution to monitor their lines, based on Amazon Kinesis and Amazon Managed Service for Apache Flink. These fully managed services reduce the complexity of building streaming applications with Apache Flink. Managed Service for Apache Flink manages the underlying Apache Flink components that provide durable application state, metrics, logs, and more, and Kinesis enables you to cost-effectively process streaming data at any scale.

How Amazon optimized its high-volume financial reconciliation process with Amazon EMR for higher scalability and performance

Account reconciliation is an important step to ensure the completeness and accuracy of financial statements. Specifically, companies must reconcile balance sheet accounts that could contain significant or material misstatements. Accountants go through each account in the general ledger of accounts and verify that the balance listed is complete and accurate. When discrepancies are found, accountants […]