AWS Partner Network (APN) Blog

Category: Analytics

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How Oncoshot Built a Federated Data Platform on AWS to Accelerate Clinical Trials

While healthcare organizations understand the importance of patient data, there’s no efficient framework for secure sharing. Many retain data rather than risk exposure, resulting in siloed, inaccessible information. Oncoshot built a federated AWS platform on AWS that enables secure data exchange, connects experts with real-time patient insights to accelerate trial enrollment, and expedites potentially life-saving therapies without exposing patient data.

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How Wavicle’s QuickSight Migration Solution Accelerates Adoption of Amazon QuickSight

Many organizations want to migrate from legacy BI tools to Amazon QuickSight, but manual migration cab be costly. Wavicle’s QuickSight Migration Solution (QMS) automates and optimizes this process, analyzing existing dashboards, identifying duplication, automating conversion, and facilitating a seamless rollout. This reduces migration effort, costs, and risks so organizations can rapidly realize QuickSight’s self-service analytics, flexibility, and cost savings.

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How to Analyze Fastly Content Delivery Network Logs with Amazon QuickSight Powered by Generative BI

A content delivery network (CDN) caches content closer to users and reduces load times. Monitoring CDN performance is crucial for optimizing user experience, and this post demonstrates building an Amazon QuickSight dashboard with generative AI capabilities to gain insights from Fastly CDN logs in Amazon S3. It covers configuring real-time log streaming, using AWS Glue to catalog data, accelerating dashboard creation using natural language, and creating rich data stories for stakeholders.

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Revolutionizing the Aftermarket: Building Data Products and Unlocking Insights with AWS Analytics

Designing an ecommerce data analytics service poses challenges like data integration, quality, scalability, real-time processing, security/privacy, and visualization. Thoughtworks leverages AWS services to build data products that acquire, clean, transform, model, and visualize ecommerce data for analytics. Its systematic approach identifies sources, acquires data, cleans/stores it, models products, deploys with CI/CD, and visualizes insights in dashboards.

Building a Water-Secure Future with True Elements Water Intelligence Platform on AWS

The True Elements Water Intelligence Platform on AWS transforms complex data into clear insights on local watershed conditions. It provides color-coded scores for water quality and availability to support decisions around capital planning, supply chains, policy, reporting, forecasting, risk management, and innovation. Real-world examples show how the platform guides collective action on pollution, reveals supply chain vulnerabilities, and identifies opportunities for water resilience through targeted investments.

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The Composable CDP: Activating Data from Amazon Redshift to 200+ Tools Using Hightouch

Customer data is critical for modern digital organizations, but is often scattered across tools which can render it useless. Historically, customer data platforms (CDPs) aimed to consolidate data for insights and activation, but organizations now prefer a composable CDP architecture on AWS to sync data from Amazon Redshift and Amazon S3 into downstream tools. Hightouch facilitates this composable CDP approach, making it easy to activate AWS data across channels without engineering work.

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Data Tokenization with Amazon Redshift Dynamic Data Masking and Protegrity

As data becomes increasingly valuable, robust security measures are critical. This post reviews how Protegrity’s tokenization integration with Amazon Redshift Dynamic Data Masking enables organizations to effectively protect sensitive data. It provides an overview of key concepts like Protegrity Vaultless Tokenization and Redshift Dynamic Data Masking, including code examples to better safeguard sensitive information within their Redshift data warehouse both at rest and in use.

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Enabling ESG Compliance with the KewSustain AI-Powered Sustainability Platform

KewSustain is an AI platform by KewMann built on AWS that addresses gaps in sustainability compliance. It efficiently gathers ESG data from multiple sources, analyzes it, and generates sustainability reports adhering to major frameworks. Key features include automated data collection, collaboration tools, recommendations based on various risk factors, real-time insights via dashboards, and a virtual assistant providing guidance on reporting requirements.

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Fusing Business Data with an Enterprise Data Solution for a Unified Data Strategy

As companies grow, data can become fragmented across business units, hindering insights. PwC built an enterprise data solution on AWS to centralize data and streamline ingestion from diverse sources into a consolidated data lake using native AWS services and configurations. This reduces bespoke data collection, freeing up time for analysis and innovation with consistent, up-to-date data sets. The expandable solution accelerates stand up and bridges silos to unlock operational insights across the business.

How to Use Amazon SageMaker Pipelines MLOps with Gretel Synthetic Data

Generating high-quality synthetic data protects privacy and augments scarce real-world data for training machine learning models. This post shows how to integrate the Gretel synthetic data platform with Amazon SageMaker Pipelines for a full ML workflow. Gretel’s integration with SageMaker Pipelines in a hybrid or fully managed cloud environment enables responsible and robust adoption of AI while optimizing model accuracy. With Gretel, data scientists can overcome data scarcity without compromising individuals’ privacy.