November 2022 Summaries

CARTO for CPG is a cloud-native spatial analytics platform designed to help Consumer Packaged Goods (CPG) brands make data-driven decisions about their trade channels and promotional activities. The platform leverages first-party consumer data, external spatial data, and advanced analytics capabilities to provide insights on points of sale, merchant segmentation, and targeted market expansion strategies. With its native integration with leading cloud data platforms and a set of out-of-the-box analyzes, CARTO for CPG enables CPG brands to accelerate their transition to a more data-driven approach, unlocking powerful spatial insights that drive better decision-making. The platform offers a range of features, including data enrichment analytics, ready-to-use CPG apps, an analytics toolbox, and developer resources, making it an essential tool for CPG companies looking to navigate the challenges of rising inflation and changing consumer demand.

CARTO has been named as a G-Cloud supplier in the Crown Commercial Service Digital Marketplace, enabling government agencies to access its cloud-native Location Intelligence platform. This platform provides extensive experience in the public sector and enables government agencies across the globe to use spatial data and analysis for various applications such as city infrastructure, climate resilience, emergency response, traffic management, and more. Several UK public sector organizations have already adopted CARTO's platform, including West Sussex County Council, Hawaii Department of Transportation, Harris County TX, Zoe Health, and Network Rail. These organizations are using CARTO to improve their operations, make data-driven decisions, and better prepare for extreme weather events and other challenges. With its cloud-native solution now available in G-Cloud UK, governments can take full advantage of the power of Location Intelligence to improve public sector operations and advance urban planning, emergency services, and more.

Tableau and Power BI are widely used business intelligence tools that have revolutionized data analysis for many companies. However, they often struggle with spatial analysis, which involves working with location-based data such as addresses, states, or coordinates. These tools can handle simple map visualizations but may hit roadblocks when dealing with large volumes of geospatial data, custom formats, or complex geometries. The main limitation is that these tools store and analyze spatial data in memory, leading to performance issues when rendering large amounts of data. To overcome these limitations, it's essential to use a system that leverages the power of a database or data warehouse where the data is hosted. This requires two systems: one for data warehousing and another for application layer functionality. Modern data stacks with cloud-native Location Intelligence platforms can handle geospatial data more efficiently, enabling faster insights and business value.

The Ultimate Guide to OpenStreetMap & BigQuery` is a comprehensive resource that explores the advantages and limitations of using OpenStreetMap (OSM) data for spatial analysis. OSM is a crowdsourced effort to map the world, offering a cost-effective, seamless, and comprehensive dataset. However, it also has its downsides, including uneven completeness, inconsistencies in tagging, and sizeable datasets that can incur storage and analysis costs. The guide provides an overview of how to access OSM data via Google's public BigQuery project, explaining the structure of the data, how to extract and use it, and some best practices for navigating the free-tagging system. It also highlights why Google Cloud Platform is a great solution for accessing OSM data, keeping everything cloud-native and avoiding painful ETL processes. The guide aims to empower users with the knowledge they need to make informed decisions about using OSM data in their Location Intelligence projects.

A popular relational database system, PostgreSQL, is being migrated to Snowflake due to limitations in traditional database approaches for spatial analytics. Cloud data warehouses offer benefits such as performance, scalability, and security, making it an ideal choice for teams looking for performant location-based analysis at scale. Snowflake provides a unified platform that powers the Data Cloud, connecting businesses globally across any type or scale of data and many different workloads. The platform offers unmatched levels of scalability, performance, and security, with features such as serverless architectures, cost-effective cloud storage and computation, and seamless data collaboration. Additionally, Snowflake's native support for geospatial analytics, combined with the CARTO Spatial Extension, provides a wealth of spatial functionality, making it an attractive choice for migrating PostgreSQL spatial workflows to the cloud. The migration process involves setting up a spatial infrastructure in Snowflake, importing data from PostgreSQL, accelerating queries using Search Optimization Service and spatial indexes, sharing data with other users, and enriching spatial analysis and visualization using CARTO's Data Observatory and Analytics Toolbox.

The Climate Data Factory has partnered with CARTO to provide access to high-quality, ready-to-use climate change data for forward-looking physical risk assessment and impact modeling. The partnership includes the inclusion of their climate change data in CARTO's Data Observatory, which will enable users to access standardized and coherent climate information, reducing time spent on processing and transforming data. The Climate Data Factory's expert team has provided a solid track record in climate data management, processing, and is trusted by international organizations such as the European Environmental Agency. The partnership aims to provide sectors including finance, energy, water management, agriculture, and others with greater visibility of climate-related physical risk, helping them to become more resilient and better prepare for upcoming changes.