Tag: AWS Partner Success Stories

The 3-2-1 backup strategy ensures data protection by maintaining multiple copies across different storage media, with at least one copy offsite. As companies adopt SaaS applications, they need strategies to backup critical SaaS data. Own Company (formerly OwnBackup) enables SaaS data backups to Amazon S3, providing data autonomy, meeting recovery objectives, and allowing data analysis.

Organizations face increasing demands for transparency around environmental, social, and governance (ESG) matters. PwC’s Unified Sustainability Hub helps access and manage ESG data, providing automated data ingestion, a centralized view of sustainability performance, intelligent data extraction, carbon accounting, reporting/analytics, forecasting capabilities, and a generative AI assistant. It accelerates sustainability transitions by integrating stakeholders, processes, and standards.

Business intelligence (BI) teams aim to automate Amazon QuickSight asset deployment across environments. CyberCX developed a solution using AWS Step Functions to orchestrate exporting QuickSight analyses from one environment and importing them to another, simplifying migration. This reusable module integrates with CyberCX’s broader serverless data platform but can standalone. The entire solution is designed with security in mind and follows the principles of least privilege access.

As organizations migrate applications to the cloud, they need tools to assess application portfolios for cloud readiness. CAST Highlight provides automated analysis of custom applications, identifying issues like outdated code, cloud migration blockers, and opportunities for cloud-native services. By integrating with AWS Migration Hub Journeys, CAST offers a template to orchestrate analysis of large portfolios across teams to accelerate cloud migration and modernization initiatives.

TextRay is an information extraction solution that automatically extracts data from scanned documents using deep learning models. It leverages AWS services to provide a scalable and cost-effective way to process documents while reducing errors and turnaround time. An AWS CloudFormation template simplifies deployment, while a pre-trained base model demonstrates TextRay’s precision in extracting tabular and form data into structured CSV outputs.

Amazon Q and generative BI are transforming business operations, and AWS Partners like ZS Associates, Tiger Analytics, and Compass UOL are pioneering use cases leveraging these technologies to build industry-tailored solutions that improve decision making, operations, fraud detection, software development lifecycles, and more. AWS provides resources to help partners develop and deploy such transformative generative AI offerings.

The Amazon Athena Teradata Connector enables Athena to query data in Teradata Vantage using SQL, and comprises two AWS Lambda functions for metadata and record reading. This post describes deploying the connector, creating a Lambda layer for the Teradata JDBC driver, and running queries on Teradata from Athena, including a federated query joining Teradata and S3 data. This provides a scalable, serverless way to analyze data across different data stores without data duplication.

Connecting IoT devices securely to the cloud can be complex, but AWS IoT ExpressLink simplifies this by providing connectivity modules with built-in security from AWS Partners. Cardinal Peak used these modules to accelerate IoT product prototyping, avoiding hardware redesigns, simplifying firmware, using pre-installed certificates, streamlining manufacturing, and enabling efficient cloud onboarding. Overall, AWS IoT ExpressLink helped Cardinal Peak save over 6 months of engineering time.

NextBillion.ai provides mapping solutions for enterprises, aiming to deliver precise estimated time of arrival (ETA). It developed ENZYME, a system leveraging AWS services like Amazon SageMaker to evaluate map quality and improve ETA accuracy through machine learning. By feeding industry data into custom models, ENZYME reduces the mean absolute percentage error between estimated and actual arrival times by 10-20% compared to regular maps.

nOps Compute Copilot extends the capabilities of the open-source Karpenter Kubernetes cluster autoscaler, adding awareness of your AWS compute commitments like Reserved Instances and Savings Plans. It also analyzes Amazon EC2 Spot pricing data and termination risk to intelligently select the most cost-effective and stable Spot Instances for workloads. nOps automatically manages your Karpenter configurations, updating NodePools based on its cost optimization analysis and recommendations.