Measure the Impact of Your Amazon QuickSight Dashboards and View Your BI Portfolio in One Unified Interface
Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service. For organizations looking to implement enterprise-grade QuickSight dashboards, tracking user adoption and usage trends is essential for maximizing your BI investment. Understanding how users engage with your dashboards—such as their geographical location, department, and job functions—can provide valuable insights to refine your dashboards effectively. For further details, you can check out this blog post that explores similar concepts.
Enhance Data Analysis and Team Collaboration with SQL Notebooks in Amazon Redshift Query Editor V2.0
By Michael Tran, Olivia Patel, and Jamal Roberts
Published on 26 OCT 2022
Categories: Advanced (300), Amazon Redshift, Analytics, AWS Big Data, Serverless
The Amazon Redshift Query Editor V2.0 serves as a web-based analyst workbench that allows users to write and execute queries on their Amazon Redshift data warehouse. Users can visualize query results through charts and engage in data exploration and collaboration with their teams using SQL in a unified interface. The introduction of SQL Notebooks enhances this experience, enabling teams to work together more efficiently.
How The Mill Adventure Promoted Data-Driven Decision-Making in iGaming with Amazon QuickSight
By Emma Carter, Lucas White, and Priya Sharma
Published on 26 OCT 2022
Categories: Amazon QuickSight, Analytics, AWS Big Data, Customer Solutions, Foundational (100), Serverless
This article is co-authored with Lucas White from The Mill Adventure. The Mill Adventure specializes in providing customizable turnkey solutions for the iGaming industry, catering to both B2B and B2C partners. They offer a comprehensive gaming platform, including necessary licenses and operations, to facilitate quick deployment and success in the competitive iGaming landscape. They are also dedicated to using analytics to drive informed decisions. For more insights, you can read this authoritative resource on the subject.
Deploying DataHub with AWS Managed Services and Ingesting Metadata from AWS Glue and Amazon Redshift – Part 2
By Ethan Brooks, Maya Roberts, and Alex Chen
Published on 25 OCT 2022
Categories: Analytics, AWS Big Data, Intermediate (200), Serverless, Technical How-to
In the initial installment of this series, we discussed the importance of a metadata management solution for organizations. Utilizing DataHub as an open-source platform for metadata management, we demonstrated how to deploy it using AWS managed services via the AWS Cloud Development Kit (AWS CDK). Here, we dive into methods for populating technical metadata and further enhancing your data management strategy.
Deploying DataHub with AWS Managed Services and Ingesting Metadata from AWS Glue and Amazon Redshift – Part 1
By Maya Roberts, Ethan Brooks, and Alex Chen
Published on 25 OCT 2022
Categories: Analytics, AWS Big Data, Intermediate (200), Serverless, Technical How-to
As enterprises move towards establishing data warehouses, data lakes, or modern data architectures on AWS, they encounter challenges with increasing data volume and variety. This trend necessitates efficient metadata management solutions to handle structured, semi-structured, and unstructured datasets.
How a Blockchain Startup Developed a Prototype Solution for Analytics in Decentralized Applications Using AWS Data Lab
By Dr. Carlos Ramirez and Aysha Patel
Published on 24 OCT 2022
Categories: Amazon API Gateway, Amazon Data Firehose, Amazon DynamoDB, Amazon S3, Analytics, AWS Big Data, AWS Data Lab, AWS Lambda, Customer Solutions, Intermediate (200), Kinesis Data Streams, Serverless
This post is co-authored with Dr. Carlos Ramirez, CTO at BlockTech Innovations. At BlockTech, we have engineered a high-performance, scalable, and secure smart contract platform. Our goal is to create solutions that meet the growing demand for analytics in decentralized applications, leveraging the capabilities of AWS.
Using MSK Connect for Managed MirrorMaker 2 Deployment with IAM Authentication
By Aiden Scott, Zoe Patel, and Liam Johnson
Published on 20 OCT 2022
Categories: Advanced (300), Amazon Managed Service for Apache Flink, Amazon Managed Streaming for Apache Kafka (Amazon MSK), Analytics, AWS Big Data, How-To, Serverless
In this article, we demonstrate how to deploy MirrorMaker 2 using MSK Connect with AWS Identity and Access Management (IAM) authentication. This approach simplifies the setup for cross-Region and same-Region replication without the complexities of running MirrorMaker 2 directly.
Simplifying Analysis of Semi-Structured Nested JSON Data with AWS Glue DataBrew and Amazon QuickSight
By Riya Kumar, Jason Lee, and Tara Smith
Published on 20 OCT 2022
Categories: Advanced (300), Amazon QuickSight, Analytics, AWS Big Data, AWS Glue, AWS Glue DataBrew, Serverless
As data volumes continue to surge, big data analytics has become increasingly important for various analytics and machine learning (ML) applications. Data originates from numerous sources, often in structured, semi-structured, and unstructured formats. Semi-structured data, particularly in JSON format, presents unique challenges due to its complexity.
Automating Amazon Redshift Serverless Data Warehouse Management Using AWS CloudFormation and the AWS CLI
By David Thompson, Jessica Lee, and Harriet Green
Published on 19 OCT 2022
Categories: Advanced (300), Amazon Redshift, Analytics, AWS Big Data, AWS CloudFormation, AWS Command Line Interface, Best Practices, Customer Solutions
This article explores how to automate the management of Amazon Redshift Serverless data warehouses through AWS CloudFormation and the AWS CLI, providing organizations with best practices for efficient data management.
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