FEATURE : ANALYTICS
Key benefits of CARTO AI Agents include :
Spatial Data Science ’ s footprint keeps getting bigger
This year ’ s survey painted a completely different picture about the state of Spatial Data Science today compared to what been seen in the past .
What used to be a rather uniform and niche practice within organizations has transformedinto an incredibly diverse and well-integrated branch of data science that is being used in increasingly innovative ways to fuel business strategies and drive smarter decisions .
These key themes stood out :
• No coding or geospatial skills required : AI not only eliminates the need for code , but it also eliminates the need for specialist geospatial knowledge , allowing users to “ ask the map ” without needing to understand every detail of the geospatial application .
• Enhanced user and stakeholder engagement : Analysis never needs to feel static and everyone in the organization can pose questions .
• Instant and insightful responses : Users can rapidly provide understandable , actionable insights .
• Adaptive reasoning : Access insights adapted to user queries and dynamic reasoning about map data , offering tailored and precise responses .
• Increased diversity across the board : Spatial Data Science is expanding well beyond its core , not only in terms of its application , but also around who is actually doing spatial data work . The report shows survey respondents came from all walks of data science life to provide new perspectives that hint at what the future of the industry truly holds .
• Multidisciplinary at its core : There ’ s no one-size-fits-all to Spatial Data Science anymore . Today , it reaches into practically every industry and sector imaginable via a wide array of applications and use cases . This has further propelled its mainstreaming within organizations by enabling greater cross-functional communication and collaboration across data science teams .
• A growing need for interoperability : The Spatial Data Science landscape is characterized by a dizzying array of platforms , tools and technologies – some that don ’ t necessarily ‘ speak ’ the same language . To break down silos , improve efficiency , and accelerate innovation , the industry as a whole must work towards fostering interoperability across data , tools , solutions , and principles and platforms .
As businesses continue to uncover the benefits of spatial analysis , CARTO ’ s latest report provides further insights into the Spatial Data Science landscape , including :
• On-prem data silos are breaking down : Nearly 70 % of respondents confirm doing spatial analysis on the cloud , an increase of 15 percentage points from 2022 .
• GIS is no longer the leading profession for those in Spatial Data Science : Over half ( 52 %) of all respondents have data analysts doing spatial data science , followed by data scientists ( 45 %) and GIS professionals ranking third ( 44 %).
• Organizations that leverage spatial data have matured : Only 25 % of organizations use spatial data for simple analysis and visualizations , while close to half of the organizations surveyed have matured to using the technology to run localized , one-off analysis ( 22 %) or build more complex and iterative pipelines ( 22 %).
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