AWS Big Data Blog

AWS Big Data Blog Official Big Data Blog of Amazon Web Services

  • Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics
    by Saeed Barghi on March 27, 2024 at 4:21 pm

    Healthcare providers have an opportunity to improve the patient experience by collecting and analyzing broader and more diverse datasets. This includes patient medical history, allergies, immunizations, family disease history, and individuals’ lifestyle data such as workout habits. Having access to those datasets and forming a 360-degree view of patients allows healthcare providers such as claim

  • Successfully conduct a proof of concept in Amazon Redshift
    by Ziad Wali on March 27, 2024 at 4:09 pm

    Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. In this post, we discuss how to successfully conduct a proof of concept in Amazon Redshift by going through the main stages of the process, available tools that accelerate implementation, and common use cases.

  • Create an end-to-end data strategy for Customer 360 on AWS
    by Ismail Makhlouf on March 26, 2024 at 3:27 pm

    Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. For example, you can use C360 to segment and create marketing campaigns that are

  • Announcing the AWS Well-Architected Data Analytics Lens
    by Russell Jackson on March 26, 2024 at 3:00 pm

    We are delighted to announce the latest version of the Data Analytics Lens, an AWS Well-Architected whitepaper. AWS Well-Architected provides a consistent approach to evaluate architectures and implement scalable designs. The AWS Well-Architected Framework is based on six pillars—operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. With the framework, cloud architects, system architects, engineers, and developers can build secure, high-performance, resilient, and efficient infrastructure for their applications and workloads.

  • Exploring real-time streaming for generative AI Applications
    by Ali Alemi on March 25, 2024 at 5:21 pm

    Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. FMs, as the name suggests, provide the foundation to build more specialized downstream applications, and are unique in their adaptability. They can perform a wide range of different tasks, such as natural language processing, classifying images,

  • Introducing enhanced functionality for worker configuration management in Amazon MSK Connect
    by Chinmayi Narasimhadevara on March 25, 2024 at 5:18 pm

    Amazon MSK Connect is a fully managed service for Apache Kafka Connect. With a few clicks, MSK Connect allows you to deploy connectors that move data between Apache Kafka and external systems. MSK Connect now supports the ability to delete MSK Connect worker configurations, tag resources, and manage worker configurations and custom plugins using AWS

  • Run Trino queries 2.7 times faster with Amazon EMR 6.15.0
    by Bhargavi Sagi on March 22, 2024 at 6:03 pm

    In this blog, we compare Amazon EMR 6.15.0 with open source Trino 426 and show that TPC-DS queries ran up to 2.7 times faster on Amazon EMR 6.15.0 Trino 426 compared to open source Trino 426. Later, we explain a few of the AWS-developed performance optimizations that contribute to these results.

  • Build an end-to-end serverless streaming pipeline with Apache Kafka on Amazon MSK using Python
    by Masudur Rahaman Sayem on March 21, 2024 at 3:03 pm

    The volume of data generated globally continues to surge, from gaming, retail, and finance, to manufacturing, healthcare, and travel. Organizations are looking for more ways to quickly use the constant inflow of data to innovate for their businesses and customers. They have to reliably capture, process, analyze, and load the data into a myriad of

  • Unlock insights on Amazon RDS for MySQL data with zero-ETL integration to Amazon Redshift
    by Milind Oke on March 21, 2024 at 2:58 pm

    Amazon Relational Database Service (Amazon RDS) for MySQL zero-ETL integration with Amazon Redshift was announced in preview at AWS re:Invent 2023 for Amazon RDS for MySQL version 8.0.28 or higher. In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation

  • Announcing data filtering for Amazon Aurora MySQL zero-ETL integration with Amazon Redshift
    by Jyoti Aggarwal on March 20, 2024 at 4:08 pm

    AWS is now announcing data filtering on zero-ETL integrations, enabling you to bring in selective data from the database instance on zero-ETL integrations between Amazon Aurora MySQL and Amazon Redshift. This feature allows you to select individual databases and tables to be replicated to your Redshift data warehouse for analytics use cases. In this post, we provide an overview of use cases where you can use this feature, and provide step-by-step guidance on how to get started with near real time operational analytics using this feature.

  • Invoke AWS Lambda functions from cross-account Amazon Kinesis Data Streams
    by Amar Surjit on March 20, 2024 at 3:58 pm

    A multi-account architecture on AWS is essential for enhancing security, compliance, and resource management by isolating workloads, enabling granular cost allocation, and facilitating collaboration across distinct environments. It also mitigates risks, improves scalability, and allows for advanced networking configurations. In a streaming architecture, you may have event producers, stream storage, and event consumers in a

  • Hybrid Search with Amazon OpenSearch Service
    by Hajer Bouafif on March 19, 2024 at 4:33 pm

    This post explains the internals of hybrid search and how to build a hybrid search solution using OpenSearch Service. We experiment with sample queries to explore and compare lexical, semantic, and hybrid search. All the code used in this post is publicly available in the GitHub repository.

  • Scale AWS Glue jobs by optimizing IP address consumption and expanding network capacity using a private NAT gateway
    by Sushanth Kothapally on March 19, 2024 at 3:39 pm

    As businesses expand, the demand for IP addresses within the corporate network often exceeds the supply. An organization’s network is often designed with some anticipation of future requirements, but as enterprises evolve, their information technology (IT) needs surpass the previously designed network. Companies may find themselves challenged to manage the limited pool of IP addresses.

  • Amazon Managed Service for Apache Flink now supports Apache Flink version 1.18
    by Lorenzo Nicora on March 18, 2024 at 9:03 pm

    Apache Flink is an open source distributed processing engine, offering powerful programming interfaces for both stream and batch processing, with first-class support for stateful processing and event time semantics. Apache Flink supports multiple programming languages, Java, Python, Scala, SQL, and multiple APIs with different level of abstraction, which can be used interchangeably in the same

  • Enrich your customer data with geospatial insights using Amazon Redshift, AWS Data Exchange, and Amazon QuickSight
    by Tony Stricker on March 18, 2024 at 4:07 pm

    It always pays to know more about your customers, and AWS Data Exchange makes it straightforward to use publicly available census data to enrich your customer dataset. The United States Census Bureau conducts the US census every 10 years and gathers household survey data. This data is anonymized, aggregated, and made available for public use.

  • Multicloud data lake analytics with Amazon Athena
    by Shoukat Ghouse on March 18, 2024 at 4:03 pm

    Many organizations operate data lakes spanning multiple cloud data stores. This could be for various reasons, such as business expansions, mergers, or specific cloud provider preferences for different business units. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics

  • Amazon OpenSearch H2 2023 in review
    by Jon Handler on March 15, 2024 at 4:57 pm

    2023 was been a busy year for Amazon OpenSearch Service! Learn more about the releases that OpenSearch Service launched in the first half of 2023. In the second half of 2023, OpenSearch Service added the support of two new OpenSearch versions: 2.9 and 2.11 These two versions introduce new features in the search space, machine

  • How VMware Tanzu CloudHealth migrated from self-managed Kafka to Amazon MSK
    by Rivlin Pereira on March 14, 2024 at 5:21 pm

    This is a post co-written with Rivlin Pereira & Vaibhav Pandey from Tanzu CloudHealth (VMware by Broadcom). VMware Tanzu CloudHealth is the cloud cost management platform of choice for more than 20,000 organizations worldwide, who rely on it to optimize and govern their largest and most complex multi-cloud environments. In this post, we discuss how

  • Gain insights from historical location data using Amazon Location Service and AWS analytics services
    by Alan Peaty on March 13, 2024 at 4:56 pm

    Many organizations around the world rely on the use of physical assets, such as vehicles, to deliver a service to their end-customers. By tracking these assets in real time and storing the results, asset owners can derive valuable insights on how their assets are being used to continuously deliver business improvements and plan for future

  • Build a RAG data ingestion pipeline for large-scale ML workloads
    by Randy DeFauw on March 13, 2024 at 4:49 pm

    For building any generative AI application, enriching the large language models (LLMs) with new data is imperative. This is where the Retrieval Augmented Generation (RAG) technique comes in. RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. For ingesting these

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