Tag: AWS Partner Spotlight

There are multiple use cases where applications running on AWS may require a Lambda function to process the file stored in Box storage before it’s sent to the next stage for further processing. This post explains how a Lambda function can be invoked on the upload of a file in a Box folder using a webhook. With the help of a Box webhook and Amazon API Gateway, users can invoke a Lambda function on file upload operation and download the file to Amazon S3.

Verisk provides data analytic insights to customers in insurance, energy and specialized markets, and financial services. Learn how a joint team from AWS and Verisk Argus migrated petabytes of SQL Server data from on-premises to Amazon S3 and Amazon S3 Glacier using AWS Snowball Edge and the Amazon EMR custom Spark ingestion framework. Through this migration framework, Verisk Argus is positioned to save millions of dollars by moving to AWS from their data center.

A serverless architecture strategy reduces complexity and provides more flexibility in adopting the features and non-functional requirements needed to support market agility. In this post, walk through an example of an IoT use case and build a serverless scalable platform using Amazon Kinesis Data Firehose, Amazon Managed Service for Apache Flink, and MongoDB Realm. You’ll learn how easy it is to develop mobile and desktop applications on top of the data platform for different personas.

Customer onboarding remains a challenging and time-consuming process for most banks. Both digital and traditional processes are often overly complex, resulting in lower conversion rates and higher cost of acquisition. To overcome these challenges, numerous financial institutions have started customer onboarding online. In this post, walk through the use case of one of the largest financial institutes of Europe for whom Infostretch provided a substantial breakthrough to onboard the customers digitally.

Enterprise data warehouses are complex and consist of database objects that need to be modified to reflect the changing needs of business, data analytics, and machine learning teams. In this post, learn about an approach to managing the evolution of enterprise-scale data warehouses based on the experience of Deloitte’s Data and AI global practice teams. The declarative tool developed by Deloitte that can automatically generate DDL statements to align Amazon Redshift’s state to an approved baseline configuration.

As a multi-cloud network security platform, Valtix enables teams to meet the most stringent security requirements in a cloud-first and simple way. Learn about the transformation of network security use case leveraging Valtix for segmentation of workloads and to help meet compliance requirements. We’ll also walk through an example of how to enforce consistent security across tens and hundreds of VPCs spanning multiple regions and AWS accounts.

With the proliferation of different, constantly changing applications, it’s become a challenge to innovate quickly while having a strategy in place to prevent ballooning storage costs. Legacy archival and analytic tools often restrict developers and diminish the benefits of NoSQL’s handling of modern, rich data sources. Learn how MongoDB is committed to making it easier for customers to scale and transform their data management solutions to make developers’ lives easier.

Dataiku orchestrates the entire machine learning lifecycle and makes it accessible to data scientists and analysts alike. With deep integration with AWS AI tools, Dataiku enables users to augment their analytics workflow with pretrained NLP and computer vision models. Learn how you can use Amazon Comprehend and Amazon Rekognition plugins on Dataiku Data Science Studio (DSS) to build a simple workflow of NLP and computer vision use cases, respectively.

Building effective machine learning models requires storing and managing historical data, but conventional databases can quickly become a nightmare to regulate. Queries start taking too long, for example, slowing down business decisions. Learn how to use Amazon Redshift ML and Query Editor V2 to create, train, and apply ML models to predict diabetes cases for a sample diabetes dataset. You can follow a similar approach to address other use cases such as customer churn prediction and fraud detection.

For a business to effectively prepare for unforeseen circumstances and unpredictability, it requires a healthy and robust data culture inside the organization. Alation provides artificial intelligence-driven data search and discovery, governance, and analytics capabilities to help organizations foster a data culture. Learn how Alation makes data users more effective and productive, and how Alation on AWS can be used to govern data to ensure its proper usage.