How to use this data in CARTO?
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Discover datasets to enrich your analysis, by category, country or provider.
Bring new datasets into your analysis using our Data Observatory, augmenting the data you're already using in CARTO.
Example of Housing Data Analysis
Residential Real Estate Developers
Residential Real Estate developers use multiple housing datasets to predict price fluctuations by location, looking at different variables to understand key drivers in the valuation process. In this example, we can see price predictions in the Los Angeles area.
Example of Housing Data Analysis
Real Estate Investment Trusts
Real Estate Investment Trusts (REITs) carry out their investment analysis using housing market data to identify potential locations for shared workspaces and retail developments. By looking at data relating to rental price evolution, among other data sets, they can understand where up and coming locations are emerging in cities.
Example of Housing Data Analysis
Retailers
Retailers rely on housing data to educate their site selection decisions. By using real estate market data, they can get a better picture of which retail format may work best - driving merchandising decisions to ensure products match the needs of the area.
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DISCOVER OTHER SPATIAL DATA CATEGORIES
Property statistics, prices, and history to drive decisions and investment.
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The most recent census data including: age, income, household types, and more.
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Consumer Spending, Purchasing Power and Wealth indicators.
Data from routing apps and GPS to analyze traffic patterns and commuters.
Mobile device and GPS data provide insight into human movement patterns.
Location data for business establishments, restaurants, schools, attractions, …
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Climate and weather data, including exposure to weather-based hazards.
Browsing habits, app usage, feelings and experiences shared over social media platforms, ...
Digital boundaries for data aggregation and display on a map.
