AWS Partner Network (APN) Blog

Tag: Amazon S3

Swisscom-AWS-Partners

How Swisscom Saved DroneAnalytics 60% on AWS Services by Using the AWS Well-Architected Framework

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.

Read More
Onica-AWS-Partners

Best Practices from Onica for Optimizing Query Performance on Amazon Redshift

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.

Read More
Accenture-AWS-Partners

Optimizing Supply Chains Through Intelligent Revenue and Supply Chain (IRAS) Management

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.

Read More

Training Multiple Machine Learning Models Simultaneously Using Spark and Apache Arrow

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.

Read More
Tableau-AWS-Partners

Analyzing COVID-19 Data with AWS Data Exchange, Amazon Redshift, and Tableau 

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.

Read More
KNIME-AWS-Partners

Boosting the Assembly and Deployment of Artificial Intelligence Solutions with KNIME Visual Data Science Tools

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.

Read More
Cloud Anything-9

Architecting Successful SaaS: Interacting with Your SaaS Customer’s Cloud Accounts

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.

Read More

Reducing the Cost of Managing Multiple AWS Accounts Using AWS Control Tower

As larger and more complex workloads are deployed on AWS, multi-account solutions are an increasingly common architectural blueprint. Often referred to as cloud “landing zones,” these blueprints enable simple administrative boundaries. However, using multiple accounts increases the complexity of security tooling, access control and authorization, and cross-account networking. AWS Control Tower simplifies the process of setting up multi-account environments with predefined security baseline templates.

Read More
Mactores-AWS-Partners

How Mactores Tripled Performance by Migrating from Oracle to Amazon Redshift with Zero Downtime

Mactores used a five-step approach to migrate, with zero downtime, a large manufacturing company from an Oracle on-premises data warehouse to Amazon Redshift. The result was lower total cost of ownership and triple the performance for dependent business processes and reports. The migration tripled the customer’s performance of reports, dashboards, and business processes, and lowered TCO by 30 percent. Data refresh rates dropped from 48 hours to three hours.

Read More
Digital-Workplace-Program

How APN Partners Can Help You Build a Digital Workplace on AWS

The Digital Workplace program at AWS identifies APN Partners and AWS solutions that can help you build a digital workplace. All the partners and AWS solutions that we showcase have passed a Technical Baseline Review with AWS, and some of our APN Partners have also created AWS Quick Starts. These accelerators that reduce hundreds of manual procedures into just a few steps, so you can build your production environment quickly and start using it immediately.

Read More