Category: AWS Glue

HCLTech’s Intelligent Ingestion solution provides automated low-code to no-code approach, simplifying ETL build efforts for both batch and real-time data ingestion workloads. It is built using rich set of AWS services like AWS Step Functions, AWS Glue, AWS Glue DataBrew, AWS Lambda, AWS Lake Formation, Amazon Kinesis, Amazon S3, Amazon Simple Notification Service (SNS), etc., among other services to achieve seamless data integration, transformation and quality assurance. This solution entirely automates ETL ingestion upon a single click (event trigger) and provides reusable ETL workflows for rapid ETL development. It also brings quick actionable insights and decision making into business.

By Israel Mendes, Data Engineering leader – Caylent By Washim Nawaz, Analytics Specialist – AWS By Isaac Owusu-Hemeng, Customer Solutions Manager – AWS By Muz Syed, Sr. Partner Solutions Architect – AWS Caylent  In this post, we will discuss how APN Premier partner Caylent leveraged a 3-Day Experience Based Acceleration (EBA) workshop to finalize and […]

The Amazon Athena web-based query editor enables data consumers to author and run SQL queries on data sources that are registered with the AWS Glue Data Catalog and other data sources such as Amazon S3. This post describes the setup to provide federated access with OneLogin as the identity provider to securely access, author, and run queries in the Athena web-based editor via the AWS console, without the need for users to install a JDBC driver or run a SQL client on their machines.

It can be challenging for companies to consolidate data from multiple sources into one system, which is why many use AWS Glue to build ETL workflows to load their data into data lakes. Learn how AWS has collaborated with Protegrity to enable organizations with strict security requirements to protect their data while being able to obtain the powerful insights. We’ll demonstrate how data tokenization for data in transit is performed using Protegrity’s Cloud API and AWS Glue.

To sustain innovation and drive business value, organizations are realizing the importance of decentralization of data products using a data mesh architectural design approach. Experts from AWS and IBM explain how to set the right balance of business ownership using data mesh to modernize data platform and accelerate innovation. We’ll also describe referenceable techniques to build data mesh solutions using AWS native services including Amazon DataZone, AWS Lake Formation, and AWS Glue.

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.

Data quality is traditionally inconsistent and slow across teams and functions. Custom solutions are purpose-built, of varying quality, and rarely maintained. Elula developed a proprietary Data Quality Checker (DQC) powered by AWS Glue, and an Automated Data Assessment (ADA) user interface to accelerate the identification and prioritization of issues. Elula is an AWS Partner and leading provider of artificial intelligence (AI) software to the financial services sector.

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.

Big datasets have traditionally been locked on-premises because of data gravity, making it difficult to leverage cloud-native, serverless, and cutting-edge technologies provided by AWS and its community of partners. Modernizing an on-premises analytics platform takes time, effort, and careful planning. Explore the challenges of migrating large, complex, actively-used structured datasets to AWS and how the combination of WANdisco LiveData Migrator, Amazon S3, and AWS Glue Data Catalog overcome those challenges.

Environmental, social, and governance (ESG) factors are increasingly important for financial institutions as they look to assess portfolio risk, meet investment mandates, align with customer values, and report on the sustainability of their portfolios. Working closely with CSRHub, a data provider on AWS Data Exchange, learn how AWS has produced a demonstration to illustrate how customers can analyze company-level ESG scoring data with Amazon QuickSight.