AWS Big Data Blog

Category: Learning Levels

Simplify data analysis and collaboration with SQL Notebooks in Amazon Redshift Query Editor V2.0

Amazon Redshift Query Editor V2.0 is a web-based analyst workbench that you can use to author and run queries on your Amazon Redshift data warehouse. You can visualize query results with charts, and explore, share, and collaborate on data with your teams in SQL through a common interface. With SQL Notebooks, Amazon Redshift Query Editor […]

How The Mill Adventure enabled data-driven decision-making in iGaming using Amazon QuickSight

This post is co-written with Darren Demicoli from The Mill Adventure. The Mill Adventure is an iGaming industry enabler offering customizable turnkey solutions to B2B partners and custom branding enablement for its B2C partners. They provide a complete gaming platform, including licenses and operations, for rapid deployment and success in iGaming, and are committed to […]

Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 2

In the first post of this series, we discussed the need of a metadata management solution for organizations. We used DataHub as an open-source metadata platform for metadata management and deployed it using AWS managed services with the AWS Cloud Development Kit (AWS CDK). In this post, we focus on how to populate technical metadata […]

Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 1

Many organizations are establishing enterprise data warehouses, data lakes, or a modern data architecture on AWS to build data-driven products. As the organization grows, the number of publishers and subscribers to data and the volume of data keeps increasing. Additionally, different varieties of datasets are introduced (structured, semistructured, and unstructured). This can lead to metadata […]

How a blockchain startup built a prototype solution to solve the need of analytics for decentralized applications with AWS Data Lab

This post is co-written with Dr. Quan Hoang Nguyen, CTO at Fantom Foundation. Here at Fantom Foundation (Fantom), we have developed a high performance, highly scalable, and secure smart contract platform. It’s designed to overcome limitations of the previous generation of blockchain platforms. The Fantom platform is permissionless, decentralized, and open source. The majority of […]

Use MSK Connect for managed MirrorMaker 2 deployment with IAM authentication

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. In this post, we show how to use MSK Connect for MirrorMaker 2 deployment with AWS Identity and Access Management (IAM) authentication. We create an MSK Connect […]

Simplify semi-structured nested JSON data analysis with AWS Glue DataBrew and Amazon QuickSight

As the industry grows with more data volume, big data analytics is becoming a common requirement in data analytics and machine learning (ML) use cases. Data comes from many different sources in structured, semi-structured, and unstructured formats. For semi-structured data, one of the most common lightweight file formats is JSON. However, due to the complex […]

Automate Amazon Redshift Serverless data warehouse management using AWS CloudFormation and the AWS CLI

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage the instance type, instance size, lifecycle management, pausing, resuming, and so on. It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what […]

Ingest VPC flow logs into Splunk using Amazon Kinesis Data Firehose

In September 2017, during the annual Splunk.conf, Splunk and AWS jointly announced Amazon Kinesis Data Firehose integration to support Splunk Enterprise and Splunk Cloud as a delivery destination. This native integration between Splunk Enterprise, Splunk Cloud, and Kinesis Data Firehose is designed to make AWS data ingestion setup seamless, while offering a secure and fault-tolerant […]

Introducing runtime roles for Amazon EMR steps: Use IAM roles and AWS Lake Formation for access control with Amazon EMR

You can use the Amazon EMR Steps API to submit Apache Hive, Apache Spark, and others types of applications to an EMR cluster. You can invoke the Steps API using Apache Airflow, AWS Steps Functions, the AWS Command Line Interface (AWS CLI), all the AWS SDKs, and the AWS Management Console. Jobs submitted with the […]