March 2021 Summaries

CARTO for React aims to accelerate spatial application development by providing a faster, more productive platform for building Location Intelligence applications. By leveraging the popular React framework and Redux, CARTO for React offers pre-built templates, a well-designed library with packages for user interface components, state management, and API connections, allowing developers to build apps twice as fast. The solution includes a code generator based on Hygen, beautiful themes for Material-UI, and demo showcases from partnerships with key players in the industry. CARTO for React is part of an open-source ecosystem, with its templates and library available for free, and a growing developer community is encouraged to contribute and share their experiences.

WXY, an architecture urban design and planning firm, collaborated with Montgomery County Public Schools (MCPS) to create the Interactive Boundary Explorer (IBE), an interactive tool that utilizes CARTO to visualize school data and allow community engagement. The IBE provides a comprehensive analysis of school boundaries, utilization rates, diversity, and distances traveled, enabling users to explore the data through multiple lenses. By leveraging CARTOframes and CARTO.js, WXY created dynamic visualizations with interactive layers, allowing residents to toggle between analysis views, select specific school clusters, overlay traffic data, and make custom comparisons. The platform's key benefits include transparency, inclusivity, and community involvement, empowering residents to conduct their own analysis, share feedback, and engage in dialogue with MCPS based on real-time data and facts.

Indigo Ag, a company focused on sustainable agriculture, leverages digital technologies and natural microbiology to promote environmental sustainability. They utilize CARTO's automation solutions to aggregate, analyze, and visualize disparate datasets stored within Snowflake databases. The Indigo analytics team uses the Snowflake connector to import data from various sources, including Salesforce CRM data, and create maps that display current sampling status of each field, drive time areas, and meteorological variables. This enables managers to assign and optimize sampling deployment, and updates are refreshed daily using CARTO's Snowflake connector. The company has simplified their data management process by utilizing the CARTOframes Python package and Snowflake connector, which provide ultimate flexibility in creating customized automated workflows.

The Spatial Data Science in Financial Services Summit, part of #SDSC21, is a free virtual conference taking place on March 24th and 25th, featuring a lineup of data science and geospatial leaders from top financial institutions. The summit will cover various topics such as location data analytics, big data projects, machine learning, and fraud prevention, with speakers including experts from Goldman Sachs, Bank of America Merrill Lynch, and JP Morgan. The event also highlights the role of Google Cloud and Safegraph in transforming business with secure infrastructure, developer tools, and data analytics. Registration for the summit is now available on the website.

Google Cloud and CARTO have partnered to provide a powerful tool for geospatial analysis at scale, called BigQuery Tiler. This tool allows users to visualize and analyze massive datasets in real-time, eliminating the need for complex batch data updates and reducing user downtime. With the support of Google Cloud's BigQuery, users can ingest, store, compute, and visualize their geospatial data seamlessly, making it easier to drive more efficient business decisions. The CARTO Spatial Extension for BigQuery enables users to create tilesets from large datasets, which can be visualized using the Map Viewer tool. This tool provides a range of features, including color ramps for data-driven visualizations and integration with web mapping libraries. By leveraging Google Cloud's BigQuery Tiler, organizations can gain insights into complex analytical use cases such as cellular network deployment, IoT analytics, or mobility analysis.

The COVID-19 vaccine rollout is ongoing globally, with over 224 million doses administered worldwide, and various organizations using location data to optimize vaccine distribution and ensure equitable access. Location intelligence plays a crucial role in the optimization of cold chain transportation and spatial aspects of vaccine distribution. Public and private organizations are utilizing publicly available information and data science to build interactive maps showcasing vaccination rates, demographics, and supply chain logistics. These efforts aim to address disparities in vaccine distribution, such as those found in Philadelphia's wealthy suburbs versus city neighborhoods, and provide insights into vaccination rates in regions like Catalonia and Texas, ultimately enabling authorities to respond and ensure more equitable access to vaccines.

The analysis leverages multiple types of spatial data to analyze and predict CPG (Consumer Packaged Goods) sales performance. The study focuses on the Iowa liquor market, using publicly available data from 2012 to 2019. By analyzing sales variations across different locations within the state, the research aims to identify factors driving consumption and variation patterns. The approach involves building spatial models that incorporate various features, such as population demographics, points of interest, and geographic insights. These models are trained on a dataset of SKUs (stock-keeping units) and are validated using metrics like R-squared and mean absolute error. The results show strong modeling capabilities, with the model performing only slightly worse when including additional features. The analysis also reveals that larger volume products tend to perform better than smaller ones, likely due to commercial dynamics involving wholesalers and businesses. By extrapolating the results to the state of Nebraska, the study provides insights into areas with high sales potential for specific SKUs.