AWS Partner Network (APN) Blog

Tag: APN Partner Guest Post

Machine Learning-3

Gathering Market Intelligence from the Web Using Cloud-Based AI and ML Techniques

Many organizations face the challenge of gathering market intelligence on new product and platform announcements made by their partners and competitors—and doing so in a timely fashion. Harnessing these insights quickly can help businesses react to specific industry trends and fuel innovative products and offerings inside their own company.Learn how Accenture helped a customer use AWS to gather critical insights along with key signals and trends from the web using AI and ML techniques.

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Building a Business Case for SAP on AWS to Unlock New Value for the Enterprise

Many organizations will find the migration to S/4HANA in the cloud to be as transformative as their initial adoption of enterprise resource planning (ERP) software. Choosing trusted providers that understand both your business needs and technology environment is the shortest path to value. Deloitte’s collaboration with AWS helps clients accelerate their ability to achieve digital transformation and powerful insights-based outcomes with SAP S/4HANA and the SAP HANA platform.

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Transforming the Customer Experience at Speed and Scale with AWS and Braze

Braze is a comprehensive customer engagement platform built on AWS that helps brands bring modern, stream processing, and data-science frameworks to their engagement strategies. When a minute can make or break a customer experience, brands need a tool that allows them to make virtually instantaneous and meaningful connections with every one of their customers. Learn about recent campaigns from Burger King, Overstock, and BlaBlaCar and the technology that made them possible.

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How to Visualize and Monitor Your AWS Container Fleet with Datadog

To fully leverage the versatility and scalability of containers, you need a monitoring solution capable of providing clarity into a highly dynamic environment comprising thousands (or even tens of thousands) of ephemeral containers. Learn how Datadog provides visibility into dynamic, ephemeral container workloads running on Amazon EKS, a service that makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters.

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Improving the Performance of Distributed Atlassian Applications with Amazon CloudFront

Atlassian users who run Jira, Confluence, or Bitbucket applications across distributed teams find that, due to slower network connectivity, content sometimes loads much slower for team members in geographically distant regions. A new feature in Atlassian’s Jira, Confluence, and Bitbucket Data Center versions allows the use of Amazon CloudFront to improve the user experience and overall performance of applications hosted in other global regions.

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Monitoring Microservice-Based Cloud Applications Using Distributed Tracing

As application complexity increases, the debugging process in production environments gets more complicated as well. AWS understands this challenge and includes tracing tools in its cloud services. For instance, AWS X-Ray helps developers analyze and debug distributed applications, such as those built using a microservices architecture. Epsagon specializes in automated tracing for cloud microservices, providing automated end-to-end tracing across not distributed AWS services.

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Enabling Customer Attribution Models on AWS with Automated Data Integration

Attribution models allow companies to guide marketing, sales, and support efforts using data, and then custom tailor every customer’s experience for maximum effect. Combined together, cloud-based data pipeline tools like Fivetran and data warehouses like Amazon Redshift form the infrastructure for integrating and centralizing data from across a company’s operations and activities, enabling business intelligence and analytics activities.

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Managing Red Hat Enterprise Linux Systems on AWS with Red Hat Insights

Red Hat Insights helps you manage Red Hat Enterprise Linux (RHEL) Systems on AWS by analyzing physical, virtual, container, and hybrid private and public cloud environments, comparing them to more than 1,000 rules. These rules identify potential threats that could lead to business disruptions. Insights scans your environments daily, summarizes any identified risks in its dashboard, and provides remediation steps for those risks.

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How Sisense Simplifies Complex Data Analytics for Analysts and Developers

Organizations these days are inundated with data. Learn how engineers and analysts can handle the critical challenges of gaining insights from large and complex data sources while also democratizing data for improved adoption across the organization. The Sisense platform simplifies end-to-end data and analytics, reducing time-to-insights by empowering data and IT teams to build advanced data models and perform advanced analysis for their needs.

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How to Use Xplenty with AWS KMS to Provide Field-Level Encryption in ETL Data Processing

Enterprises often choose to mask, remove, or encrypt sensitive data in the ETL step to minimize the risk of sensitive data becoming stored, logged, accessible, or breached from their data lake or data warehouse. Xplenty’s ETL and ELT platform allows customers to quickly and easily prepare their data for analytics using a simple-to-use data integration cloud service. Xplenty’s global service uses AWS KMS to create and control the keys used to encrypt or digitally sign your data.

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