January 2021 Summaries

**Human mobility data offers a significant boost to the accuracy of catchment areas compared to conventional drive time trade areas, allowing retailers to better understand their customers and competitors. By analyzing and visualizing SafeGraph mobility data, companies can generate more accurate trade area maps that account for travel time differences and provide valuable insights into customer demographics and behavior. This approach has been successfully applied in the retail industry, with one example using Costco in the Bay Area to demonstrate the power of human mobility data in generating accurate trade areas.

Spatial data science is evolving rapidly due to global changes such as climate change and COVID-19, requiring real-time analysis and new solutions. Cloud-native spatial data infrastructures are emerging, enabling faster and more efficient analysis with less "plumbing" worries. Next-gen data warehouses like BigQuery and Snowflake provide scalable processing power through SQL or Python notebooks, while next-generation data warehouses add spatial support to their products. Data democratization is key, allowing access to high-quality location data and simplifying the licensing process through data marketplaces. These trends can help industries recover from 2020's events, with increasing adoption predicted in CPG & Retail, Financial Services, and Logistics.

The study aims to identify areas in Spain most likely to suffer recession post-pandemic by analyzing sociodemographic, economic, and employment factors. The researchers used datasets from Unica360 to build a risk index, which was calculated using Principal Component Analysis (PCA). The analysis revealed that areas with higher risks of economic recession are those within the M30 orbital motorway and in neighborhoods towards the south and south-west, particularly those with more hostelry, retail, and tourism activities. In contrast, areas with lower risks are located in the north and north-west, such as Aravaca and Chamartin, which have fewer office buildings, commercial properties, and tourist attractions. The study's findings provide insights into the characteristics of areas that may be affected by the upcoming economic recession, highlighting the importance of considering sociodemographic, economic, and employment factors when predicting economic downturns.