AWS Partner Network (APN) Blog
Discover, Prepare, and Integrate Data at Scale with AWS Glue Delivery Partners
We are pleased to announce the AWS Glue Delivery specialization to help customers find validated AWS Partners with expertise and proven success delivering AWS Glue for data integration, data pipeline, and data catalog use cases. The AWS Glue Delivery specialization recognizes AWS Partners who offer consulting services to help customers modernize their use of data and accelerate digital transformation.
Operational Analytics with MongoDB Atlas and Amazon Redshift
Enterprises are building data analysis capabilities to extract information captured in data, develop an understanding of their business, and channel efforts towards customer centricity. This post explains the need for operational analytics and how it can be achieved with MongoDB Atlas and Amazon Redshift. MongoDB is an AWS Data and Analytics Competency Partner and developer data platform company empowering innovators to unleash the power of software and data.
Accelerate FinTech Innovation and Streamline CloudOps with AWS and ChaosSearch
To stay ahead in a highly competitive market, FinTechs face multiple challenges, especially around maintaining development agility, operational excellence, and a strong security posture. This post explores how the ChaosSearch data platform combines the industry-leading scalability, data availability, security, and performance provided by Amazon S3 with revolutionary technology to help FinTechs address critical pain points and overcome core operational challenges.
Dremio Cloud is a Lakehouse Platform on AWS That Democratizes Data
Dremio Cloud is a cloud lakehouse platform on AWS that democratizes data and provides self-service access to data consumers by connecting business intelligence users and analysts directly to data on Amazon S3 and beyond. Learn about the benefits of Dremio Cloud, how to set it up, and start using Dremio’s high-performance lakehouse platform in less than 15 minutes. Review Dremio Cloud’s key features and explore a getting started tutorial with sample datasets.
How to Integrate VMware Cloud on AWS Datastores with AWS Analytics Services
Running virtual machines with databases or datastores on VMware Cloud on AWS lets you use the same management tools and VMs as on your on-premises VMware vSphere environment. You can easily extend these workloads to the cloud and take advantage of AWS on-demand delivery, global footprint, elasticity, and scalability. Learn how VMware Cloud on AWS brings these datasets closer to AWS Analytics Services, making it easier to use services to draw meaningful insights from business data.
Leveraging Serverless Architecture to Build an Enterprise Data Repository Platform for Customer Insights and Analytics
Moving data between multiple data stores requires an extract, transform, load (ETL) process using various data analysis approaches. ETL operations form the backbone of any modern enterprise data and analytics platform. AWS provides a broad range of services to deploy enterprise-grade applications in the cloud. This post explores a strategic collaboration between Tech Mahindra and a customer to build and deploy an enterprise data repository on AWS and create ETL workflows using a serverless architecture.
How Etleap Integrates with Amazon Redshift Data Sharing to Provide Isolation of ETL and BI Workloads
Tens of thousands of customers use Amazon Redshift to process exabytes of data per day and power analytics workloads such as business intelligence, predictive analytics, and real-time streaming analytics. Learn how Etleap integrates with new data sharing and cross-database querying capabilities in Amazon Redshift to enable workload isolation for diverse analytics use cases in customer environments. Etleap integrates with any data source and runs either as a hosted solution (SaaS) or inside your VPC.
How Matillion Multiplies the Performance of Complex ETL Jobs with Amazon Redshift Materialized Views
Amazon Redshift recently announced support for materialized views, which lead to significantly faster query performance on repeatable query workloads. That, in turn, reduces the time to deliver the datasets you need to produce your business insights. Matillion ETL for Amazon Redshift provides comprehensive enterprise-grade features to simplify and speed up building and maintaining these pipelines.
Quickly Visualize Marketing Analytics and Ads Data with Matillion, Amazon Redshift, and Amazon QuickSight
Google Analytics and Google Ads are popular platforms for customers who need to make data-driven decisions about the performance of their web assets. For prediction, testing, and optimization scenarios, however, customers need a broader and more complete set of analytics. Matillion is an ideal tool to combine the power and convenience of Amazon Redshift and Amazon QuickSight, providing cloud-native data integration tools that make loading and transforming data fast, easy, and affordable.
Migrating ETL Operations from SSIS Packages to AWS Lambda Functions
Many Windows solutions have used Microsoft SQL Server Integration Services (SSIS) as a method for performing ETL operations. Legacy SSIS packages that have been handed down to different developers over the years can be complex, cumbersome, and difficult to support. See an architecture and several techniques Cognizant uses to help clients with ETL operations based on legacy SSIS packaging move their applications to the AWS Cloud.