Category: Learning Levels

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. AWS Glue Data Quality generates a substantial amount of operational runtime information during […]

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. By establishing and configuring alerts and notifications, you can actively monitor data quality and receive timely alerts when data quality issues are identified. This proactive approach […]

Data is the lifeblood of modern businesses. In today’s data-driven world, companies rely on data to make informed decisions, gain a competitive edge, and provide exceptional customer experiences. However, not all data is created equal. Poor-quality data can lead to incorrect insights, bad decisions, and lost opportunities. AWS Glue Data Quality measures and monitors the […]

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of […]

In the first post of the series, we described some core concepts of Apache Kafka cluster sizing, the best practices for optimizing the performance, and the cost of your Kafka workload. This post explains how the underlying infrastructure affects Kafka performance when you use Amazon Managed Streaming for Apache Kafka (Amazon MSK) tiered storage. We […]

Today, AWS is announcing the availability of in-place version upgrades for Amazon Managed Workflow for Apache Airflow (Amazon MWAA). This enhancement allows you to seamlessly upgrade your existing Apache Airflow version 2.x environments to newer available versions while retaining the workflow run history and environment configurations. You can now take advantage of the latest capabilities […]

September 2023: This post was reviewed and updated with a new dataset and related code blocks and images. AWS SDK for pandas is a popular Python library among data scientists, data engineers, and developers. It simplifies interaction between AWS data and analytics services and pandas DataFrames. It allows easy integration and data movement between 22 […]

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service that makes it easy to connect to your data, create interactive dashboards, and share these with tens of thousands of users, both within QuickSight and embedded in your software as a service (SaaS) applications. QuickSight Enterprise edition started supporting nested conditions within row-level security […]

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. Customers are looking for tools that make it easier to migrate from other data warehouses, such as Google BigQuery, to Amazon Redshift to […]

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. Apache Flink is a framework and distributed processing engine for stateful computations over data streams. Amazon Managed Service for Apache Flink is a fully managed service that […]