Real Estate Big Data
What is Big Data Real Estate and how does it work?
Rich Data Access and Advanced Indicators. The Backbone of Real Estate Analytics.
Real Estate Big Data refers to the collection and analysis of large volumes of data related to the real estate market. This data comes from various sources such as organizational data, public records, real estate portals, cadastral information, demographic data, environmental information, social networks, and much more. Once collected, this data undergoes advanced analysis using statistical techniques, machine learning algorithms, and trend analysis to extract valuable insights.
Real Estate Big Data is an essential tool for a constantly evolving sector. Data is the engine that drives informed decision-making in a highly competitive market. For tech companies in the real estate sector in Spain, Big Data is an opportunity to provide a more complete and efficient service to clients as well as to gain a competitive edge. In summary, real estate Big Data is not just a trend but a necessity for success in an ever-changing sector. Information is power, and in the Spanish real estate market, Big Data is the key to unlocking that power.
Benefits of Big Data in the Real Estate Sector
Accuracy, Predictability and Limitless Opportunities
- Precise Pricing: One of the main benefits of Big Data in the real estate sector is its ability to provide more accurate pricing. By analyzing comparable sales data, local market trends, previous appraisals, and other factors, real estate professionals can determine fair and competitive prices for properties.
- Market Trend Analysis: Large-scale data analysis allows real estate market players to identify emerging trends in real-time. This can include changes in demand by location, buyer preferences, and the impact of economic and political events on the local market.
- Investment Optimization: Investors can use data to identify opportunities in high-demand and growth-potential areas. This includes identifying up-and-coming neighborhoods, infrastructure projects, and future demand forecasts.
- Enhanced Customer Experience: Real estate companies can use data to personalize the customer experience, including providing buyers with recommendations based on their specific preferences and needs.
- Risk Reduction: Data analysis can also help mitigate risks by assessing market stability, likelihood of property value appreciation, and potential threats.
Gloval Analytics stands out as a pioneering entity in real estate analytical solutions that has effectively integrated Big Data capabilities into its services, providing clients with advanced tools for risk assessment, precise property valuation, and investment opportunity identification. This data-centered approach not only enhances decision-making but also drives innovation in a sector traditionally rooted in conventional practices.
Gloval Analytics case studies
Real estate analysis that adds value
We have created automated valuation models for properties, various price prediction models, and over 50 industry indicators, enabling our clients to make well-informed decisions.
What data do we analyse through Big Data Real Estate?
Data Diversity with the broadest geographic coverage
Real estate typologies
Residential housing, offices, commercial premises, hotels, industrial buildings, residential and commercial buildings, among others.
Geographic coverage
We cover data from census tract to national level, including district, municipality, postal code and province.
Examples of Available Data:
Cadastre
Enriched Cadastre data (parcel, property and element level), including data from specific regions such as the Basque Country and Navarra.
Sociodemographic and Economic Data
Aggregate data from census section on population, income, unemployment, level of education, etc.
Real Estate Figures
Sales and rental value of homes, offices, commercial premises, hotels, industrial buildings, residential and commercial buildings.
Energy Certificates
Energy certificates for properties in Spain, Portugal and the United Kingdom.
Physical and Environmental Risks
Physical and environmental risks in different locations, with an analysis at the macroeconomic level.
Tourism and Macroeconomic Indicators
Tourism and macroeconomic indicators at the national level, by zone and tourist attractions, among others.
Analysis Indicators
Real Estate Bubble Index
Calculated by Analytics. It evaluates the stability of the real estate market, considering multiple variables such as sales prices, historical appraisals, demand and supply, among other key factors. It also measures the sensitivity of the access to the sale and purchase market to economic changes, at the macro and sector level, determining the vulnerability of the access to the sale and purchase market.
Q1 2024 vs. Q4 2023
Q1 2024 vs. Q4 2023
Rental Market Stress Index
Calculated by Analytics. It evaluates the sensitivity of the effort to access the rental market to economic changes, at the macro and sectoral levels. This indicator determines the economic stability and households’ ability to access the rental market, considering the impact of external changes on the household economy.
Energy Efficiency and Physical and Environmental Risk Indicators
Using geospatial data and energy efficiency analysis along with physical and environmental risks, we develop indicators that highlight the opportunities and risks associated with different geographic locations. This is crucial for investors, developers and developers seeking to maximize the return on their investments while managing potential risks.
S1 2024 vs S1 2023
Profitability Indicators
We develop profitability indicators for different real estate typologies such as residential housing or commercial premises. These consider acquisition costs, maintenance, occupancy rates, average rents and market trends to calculate real profitability. This helps investors make informed decisions about their investments.
Price and Demand Trend Indices
We closely monitor price and demand trends in different segments of the real estate market. Our indices provide insights on how prices, property demand and buyer and tenant preferences are evolving. This allows our clients to anticipate changes in the market and proactively adjust their strategies.
Who needs Big Data Real Estate?
Our customers' needs
Access to Reliable Data
Clients face difficulties in accessing reliable, up-to-date and relevant real estate market data, making it difficult to make strategic and accurate decisions.
In-Depth Analysis
The lack of tools and resources to perform in-depth analysis of the real estate market limits the ability to identify opportunities, assess risks and optimize operations.
Transparency and Efficiency
The need for transparent and efficient processes in data management and real estate operations that generate trust and optimize results.
¿How do we do Big Data Real Estate?
THE VALUE OF HAVING THE HISTORY OF THE REAL ESTATE MARKET AND COMBINING IT WITH THE LATEST TECHNOLOGY
01
We analyze your needs
We meet to thoroughly analyze your business and define the best way to access the indicators.
02
We identify the indicators
After analyzing your needs, we identify and create the best indicators to solve the problem.
03
Delivery of indicators
Indicators are tested and shared with the selected interface: api, widget, files, etc.
Frequently Asked Questions
This depends on the type and amount of properties to be appraised.
For single deliveries, you will get the appraisal on the same day, and through the platform, you will get the appraisal in about 2 seconds.
Let’s have a chat
Share your concerns with us by filling in our form and we will contact you so that you can tell us all about your requirements.
