AWS Big Data Blog
Author: Igor Alekseev
Igor Alekseev is a Senior Partner Solution Architect at AWS in Data and Analytics domain. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation. Igor's projects were in variety of industries including communications, finance, public safety, manufacturing, and healthcare. Earlier, Igor worked as full stack software engineer/tech lead.
Compose your ETL jobs for MongoDB Atlas with AWS Glue
In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data. This is driven by the need to centralize and integrate data coming from disparate sources. At the same […]
Introducing MongoDB Atlas metadata collection with AWS Glue crawlers
For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. Many customers also have data in managed operational databases such as MongoDB Atlas and need to […]
Build a serverless streaming pipeline with Amazon MSK Serverless, Amazon MSK Connect, and MongoDB Atlas
This post was cowritten with Babu Srinivasan and Robert Walters from MongoDB. Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed, highly available Apache Kafka service. Amazon MSK makes it easy to ingest and process streaming data in real time and use that data easily within the AWS ecosystem. With Amazon MSK […]