AWS Big Data Blog

Category: Analytics

Using Random Cut Forests for real-time anomaly detection in Amazon OpenSearch Service

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Anomaly detection is a rich field of machine learning. Many mathematical and statistical techniques have been used to discover outliers in data, and as a result, many algorithms have been developed for performing anomaly detection in a computational setting. In […]

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Moving to managed: The case for Amazon OpenSearch Service

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Prior to joining AWS, I led a development team that built mobile advertising solutions with Elasticsearch. Elasticsearch is a popular open-source search and analytics engine for log analytics, real-time application monitoring, clickstream analysis, and (of course) search. The platform I […]

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Monitor and control the storage space of a schema with quotas with Amazon Redshift

Many organizations are moving toward self-service analytics, where different personas create their own insights on the evolved volume, variety, and velocity of data to keep up with the acceleration of business. This data democratization creates the need to enforce data governance, control cost, and prevent data mismanagement. Controlling the storage quota of different personas is a significant challenge for data governance and data storage operation. This post shows you how to set up Amazon Redshift storage quotas by different personas.

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How Goldman Sachs builds cross-account connectivity to their Amazon MSK clusters with AWS PrivateLink

This guest post presents patterns for accessing an Amazon Managed Streaming for Apache Kafka cluster across your AWS account or Amazon Virtual Private Cloud (Amazon VPC) boundaries using AWS PrivateLink. In addition, the post discusses the pattern that the Transaction Banking team at Goldman Sachs (TxB) chose for their cross-account access, the reasons behind their […]

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Best practices for configuring your Amazon OpenSearch Service domain

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Amazon OpenSearch Service is a fully managed service that makes it easy to deploy, secure, scale, and monitor your OpenSearch cluster in the AWS Cloud. Elasticsearch and OpenSearch is a distributed database solution, which can be difficult to plan for […]

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Build an end to end, automated inventory forecasting capability with AWS Lake Formation and Amazon Forecast

This post demonstrates how you can automate the data extraction, transformation, and use of Forecast for the use case of a retailer that requires recurring replenishment of inventory. You achieve this by using AWS Lake Formation to build a secure data lake and ingest data into it, orchestrate the data transformation using an AWS Glue workflow, and visualize the forecast results in Amazon QuickSight.

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Build an AWS Well-Architected environment with the Analytics Lens

Building a modern data platform on AWS enables you to collect data of all types, store it in a central, secure repository, and analyze it with purpose-built tools. Yet you may be unsure of how to get started and the impact of certain design decisions. To address the need to provide advice tailored to specific technology and application domains, AWS added the concept of well-architected lenses 2017. AWS now is happy to announce the Analytics Lens for the AWS Well-Architected Framework. This post provides an introduction of its purpose, topics covered, common scenarios, and services included.

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Optimize memory management in AWS Glue

In this post, we discuss a number of techniques to enable efficient memory management for Apache Spark applications when reading data from Amazon S3 and compatible databases using a JDBC connector. We describe how Glue ETL jobs can utilize the partitioning information available from AWS Glue Data Catalog to prune large datasets, manage large number of small files, and use JDBC optimizations for partitioned reads and batch record fetch from databases.  You can use some or all of these techniques to help ensure your ETL jobs perform well.

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