Tag: Amazon S3

Shift-Left is increasingly being employed within DevOps organizations to ensure companies minimize risk early in their infrastructure as code (IaC) deployment cycle. This post explains how to combine two of the technologies that make Shift-Left possible. The first is AWS CloudFormation, which represents IaC, and the second is Trend Micro’s Template Scanner, which checks your IaC to make sure it conforms to the AWS Well-Architected Framework.

Change Data Capture (CDC) is the technique of systematically tracking incremental change in data at the source, and subsequently applying these changes at the target to maintain synchronization. You can implement CDC in diverse scenarios using a variety of tools and technologies. Here, Cognizant uses a hypothetical retailer with a customer loyalty program to demonstrate how CDC can synchronize incremental changes in customer activity with the main body of data already stored about a customer.

TIBCO Software has launched an analytics app to track the spread and impact of the COVID-19 pandemic in real-time, over local regions worldwide. The goal of this analytics app is to enable organizations to assess the potential impact of the COVID-19 pandemic on their business fabric, using sound data science and data management principles, in the context of real-time operations. Learn some of key capabilities of the app and how it was developed on AWS.

DroneAnalytics offers hardware and software solutions for drones and connected objects. The consulting services from Swisscom, based on the AWS Well-Architected Framework, enabled them to more properly monitor their consumption of AWS services. By leveraging Well-Architected best practices and working with Swisscom, DroneAnalytics saved 60 percent on their AWS spend, whilst maintaining the same or better levels of operational efficiency, reliability, and performance.

Effective and economical use of data is critical to your success. As data volumes increase exponentially, managing and extracting value from data becomes increasingly difficult. By adopting best practices that Onica has developed over years of using Amazon Redshift, you can improve the performance of your AWS data warehouse implementation. Onica has completed multiple projects ranging from assessing the current state of an Amazon Redshift cluster to helping tune, optimize, and deploy new clusters.

Fragmented supply-chain management systems can impair an enterprise’s ability to make informed, timely decisions. Accenture’s Intelligent Revenue and Supply Chain (IRAS) platform integrates insights generated by machine learning models into an enterprise’s technical and business ecosystems. This post explains how Accenture’s IRAS solution is architected, how it can coexist with other ML forecasting models or statistical packages, and how you can consume its insights in an integrated way.

Spark is a distributed computing framework that added new features like Pandas UDF by using PyArrow. You can leverage Spark for distributed and advanced machine learning model lifecycle capabilities to build massive-scale products with a bunch of models in production. Learn how Perion Network implemented a model lifecycle capability to distribute the training and testing stages with few lines of PySpark code. This capability improved the performance and accuracy of Perion’s ML models.

To help everyone visualize COVID-19 data confidently and responsibly, we brought together APN Partners Salesforce, Tableau, and MuleSoft to create a centralized repository of trusted data from open source COVID-19 data providers. Anyone can work with the public data, blend it with their own data, or subscribe to the source datasets directly through AWS Data Exchange, and then use Amazon Redshift together with Tableau to better understand the impact on their organization.

With rapid advancements in machine learning techniques over the past decade, intelligent decision-making and prediction systems are poised to transform productivity and lead to significant economic gains. KNIME provides visual data science tools to help data science teams rapidly build and deploy data-driven solutions that integrate with AWS decision support tools and services. Learn about the barriers to adoption of AI and the ways in which the KNIME tools remove those barriers.

Explore several common AWS services and architectural patterns used by SaaS vendors to interact with their customers’ cloud accounts. Examples of SaaS products requiring some level of account interaction often fall into the categories of logging and monitoring, security, compliance, data analytics, DevOps, workflow management, and resource optimization. SaaS products, such as the ones in these categories, regularly interact with resources in the subscribing customer’s AWS account.