Category: Analytics

Nonprofit organizations focus on a specific mission to impact their members, communities, and the world. In the nonprofit space, where resources are limited, it’s important to optimize the impact of your efforts. Learn how you can apply machine learning with Amazon Redshift ML on public datasets to support data-driven decisions optimizing your impact. This walkthrough focuses on the use case for how to use open data to support food security programming, but this solution can be applied to many other initiatives in the nonprofit space.

Public sector organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. Data-driven decisions lead to more effective responses to unexpected events. For government organizations, a more detailed understanding of citizen ambitions and requirements creates a better citizen experience.

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. Through this program, customers are making over 100PB of high-value, cloud-optimized data available for public use. As April 22 is Earth Day, the AWS Open Data team wanted to highlight some new datasets from our geospatial and environmental communities of practice, as well as the other new or updated datasets available now on the Registry of Open Data on AWS and also discoverable on AWS Data Exchange.

In 2020, Meta introduced the Daylight Map Distribution, which combines OpenStreetMap (OSM) data with quality and consistency checks from Daylight mapping partners to create a no-cost, stable, and simple-to-use global map. This blog post provides a brief overview of OSM and Daylight followed by a step-by-step tutorial using five real-world examples. We combine the powerful query capabilities of Amazon Athena from with the feature-rich Daylight OSM data to demonstrate a typical OSM data analysis workflow.

Satellite communications (satcom) networks typically offer a rich set of performance metrics, such as signal-to-noise ratio (SNR) and bandwidth delivered by remote terminals on land, sea, or air. Customers can use performance metrics to detect network and terminal anomalies and identify trends to impact business outcomes. This walkthrough presents an approach using serverless resources from AWS to build satcom control plane analytics pipelines. The presented architecture transforms the data to extract key performance indicators (KPIs) of interest, renders them in business intelligence tools, and applies machine learning (ML) to flag unexpected SNR deviations.

Data spaces can help break down these silos between industries and sectors. Data spaces facilitate a decentralized and secure data exchange across organizations and industries that come together to pool, access, process, and share data. They enable simple, secure, open standards-based, and interoperable data-sharing, while allowing for organizations to maintain full control over their data. Learn how data spaces support simple and secure data-sharing between organizations and sectors, current data space initiatives in Europe and beyond, and how to leverage a data space with AWS.

In the public sector, civic leaders must make sure that a wide variety of citizen services are delivered efficiently, responsibly, and successfully. To identify high performing operations and support those in need of improvement, decision-makers need real-time data in formats that are simple to interpret and understand. In my 25 years of experience serving the public sector, I’ve found that there are four foundational considerations for implementing a comprehensive public sector data analytics and performance management strategy.

At AWS, many public sector customers operate fleets of vehicles (e.g. emergency response, public transportation) that generate location data, which is ultimately stored in a data lake. These customers frequently ask how they can quickly visualize this data and extract insights that can help them optimize how they operate their vehicle fleets. In this post, learn how to use Amazon Athena and Amazon Location Service to perform ad hoc reverse geocoding on a notional dataset of vehicle location history, and visualize the results on an Amazon QuickSight map.

Higher education institutions are turning to data to solve challenges, improve efficiency, and create a better student experience. But to obtain the answers institutions need to thrive and better serve students, they often need new technologies. Many universities are upgrading IT systems and investing in state-of-the-art analytics solutions. Case Western Reserve University (CWRU) is one such institution that has taken steps to innovate by creating opportunities for evolution with AWS.

AMILI is a healthcare technology (HealthTech) company based in Singapore that seeks to advance precision medicine and personalized health and nutrition by harnessing the potential of the microbiome. AMILI uses artificial intelligence (AI) and machine learning (ML) on AWS to comprehensively quantify and characterize gut microbiomes. AMILI aims to build and curate the world’s largest multi-ethnic Asia microbiome database.