Category: Learning Levels

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse. You can run […]

Unsupervised machine learning analytics has emerged as a powerful tool for anomaly detection in today’s data-rich landscape, especially with the growing volume of machine-generated data. In-stream anomaly detection offers real-time insights into data anomalies, enabling proactive response. Amazon OpenSearch Serverless focuses on delivering seamless scalability and management of search workloads; Amazon OpenSearch Ingestion complements this […]

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, […]

Part 1 of this two-part series described how to build a pseudonymization service that converts plain text data attributes into a pseudonym or vice versa. A centralized pseudonymization service provides a unique and universally recognized architecture for generating pseudonyms. Consequently, an organization can achieve a standard process to handle sensitive data across all platforms. Additionally, […]

Customers today may struggle to implement proper access controls and auditing at the user level when multiple applications are involved in data access workflows. The key challenge is to implement proper least-privilege access controls based on user identity when one application accesses data on behalf of the user in another application. It forces you to […]

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. However, altering schema and table partitions in traditional data lakes can be a disruptive and time-consuming task, requiring renaming or recreating entire tables and reprocessing large datasets. […]

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with […]

Amazon OpenSearch Serverless is an on-demand auto scaling configuration for Amazon OpenSearch Service. Since its release, the interest for OpenSearch Serverless had been steadily growing. Customers prefer to let the service manage its capacity automatically rather than having to manually provision capacity. Until now, customers have had to rely on using custom code or third-party […]

In this post, we explore the process of integrating Amazon Keyspaces and Amazon OpenSearch Service using AWS Lambda and Amazon OpenSearch Ingestion to enable advanced search capabilities. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

Towards the end of 2022, AWS announced the general availability of real-time streaming ingestion to Amazon Redshift for Amazon Kinesis Data Streams and Amazon Managed Streaming for Apache Kafka (Amazon MSK), eliminating the need to stage streaming data in Amazon Simple Storage Service (Amazon S3) before ingesting it into Amazon Redshift. Streaming ingestion from Amazon […]