Doorda's UK Commercial Real Estate Data provides a comprehensive database of over 6 million commercial locations sourced from 20 data sources, offering unparalleled insights for business intelligence and analytics purposes.

Volume and stats: - 6M Commercial locations with internals - 1.7M Named Commercial Occupants - 1.4M Non-Domestic Energy Performance Inspections

Our Commercial Real Estate Data offers a multitude of use cases: - Market Analysis - Competitor Analysis - Lead Generation - Risk Management - Location Planning

The key benefits of leveraging our Commercial Real Estate Property Data include: - Data Accuracy - Informed Decision-Making - Competitive Advantage - Efficiency - Single Source

Covering a wide range of industries and sectors, our data empowers organisations to make informed decisions, uncover market trends, and gain a competitive edge in the UK market.

Success.ai’s Commercial Real Estate Data for Commercial Real Estate Professionals in Europe provides a highly detailed dataset tailored for businesses looking to engage with key decision-makers in the European commercial real estate market. Covering developers, property managers, brokers, and investors, this dataset includes verified contact data, decision-maker insights, and firmographic details to empower your outreach and strategic initiatives.

With access to over 700 million verified global profiles and data from 70 million businesses, Success.ai ensures your marketing, sales, and partnership efforts are powered by accurate, continuously updated, and AI-validated data. Supported by our Best Price Guarantee, this solution is indispensable for navigating Europe’s thriving commercial real estate sector.

Why Choose Success.ai’s Commercial Real Estate Data?

1. Verified Contact Data for Targeted Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of property developers, brokers, asset managers, and investment leads.
   • AI-driven validation ensures 99% accuracy, reducing communication errors and improving outreach effectiveness.

2. Comprehensive Coverage Across Europe’s Real Estate Sector

   • Includes profiles from major European real estate markets such as the UK, Germany, France, Italy, and the Netherlands.
   • Gain insights into regional market dynamics, investment opportunities, and commercial real estate trends.

3. Continuously Updated Datasets

   • Real-time updates capture leadership changes, market expansions, and emerging property developments.
   • Stay aligned with the fast-evolving commercial real estate market and seize opportunities effectively.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible use of data and compliance with legal standards.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with decision-makers, property managers, and brokers in Europe’s commercial real estate sector.
• 70M Business Profiles: Access detailed firmographic data, including company sizes, revenue ranges, and geographic footprints.
• Leadership Insights: Engage with CEOs, asset managers, and real estate directors driving strategic decisions.
• Market Intelligence: Gain visibility into property development projects, investment trends, and regional opportunities.

Key Features of the Dataset:

1. Decision-Maker Profiles in Real Estate

   • Identify and connect with executives, brokers, and property managers overseeing transactions, asset management, and investment strategies.
   • Target professionals responsible for property acquisitions, leasing, and development.

2. Firmographic and Geographic Insights

   • Access detailed business information, including company structures, geographic locations, and market specializations.
   • Pinpoint key players in specific regions and align outreach with localized market needs.

3. Advanced Filters for Precision Campaigns

   • Filter companies by industry focus (commercial properties, retail, industrial), revenue size, or project scope.
   • Tailor your campaigns to address specific challenges, such as tenant retention, sustainability initiatives, or market expansion.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes with real estate professionals.

Strategic Use Cases:

1. Sales and Lead Generation

   • Present property management tools, software solutions, or investment opportunities to real estate firms and property managers.
   • Build relationships with brokers and developers seeking innovative solutions to streamline operations or enhance profitability.

2. Market Research and Competitive Analysis

   • Analyze trends in Europe’s commercial real estate market to guide product development and marketing strategies.
   • Benchmark against competitors to identify growth opportunities, underserved segments, and high-value properties.

3. Partnership Development and Investment Insights

   • Engage with property developers, asset managers, and brokers exploring strategic partnerships or new investment opportunities.
   • Foster alliances that expand market reach, improve property performance, or drive higher returns.

4. Recruitment and Workforce Solutions

   • Target HR professionals and hiring managers recruiting for roles in property management, real estate finance, or asset development.
   • Provide workforce optimization tools, training platforms, or recruitment services tailored to the commercial real estate sector.

Why Choose Success.ai?

1. Best Price Guarantee
   • Access premium-quality commercial real estate data at competitive prices, ensuring strong ROI for your marketing, sales, and business development efforts. ...

Commercial valuation data collected and maintained by the Cook County Assessor's Office, from 2021 to present. The office uses this data primarily for valuation and reporting. This dataset consolidates the individual Excel workbooks available on the Assessor's website into a single shared format. Properties are valued using similar valuation methods within each model group, per township, per year (in the year the township is reassessed). This dataset has been cleaned minimally, only enough to fit the source Excel workbooks together - because models are updated for each township in the year it is reassessed, users should expect inconsistencies within columns across time and townships. When working with Parcel Index Numbers (PINs) make sure to zero-pad them to 14 digits. Some datasets may lose leading zeros for PINs when downloaded. This data is property-level. Each 14-digit key PIN represents one commercial property. Commercial properties can and often do encompass multiple PINs. Additional notes: Current property class codes, their levels of assessment, and descriptions can be found on the Assessor's website. Note that class codes details can change across time. Data will be updated yearly, once the Assessor has finished mailing first pass values. If users need more up-to-date information they can access it through the Assessor's website. The Assessor's Office reassesses roughly one third of the county (a triad) each year. For commercial valuations, this means each year of data only contain the triad that was reassessed that year. Which triads and their constituent townships have been reassessed recently as well the year of their reassessment can be found in the Assessor's assessment calendar. One KeyPIN is one Commercial Entity. Each KeyPIN (entity) can be comprised of one single PIN (parcel), or multiple PINs as designated in the pins column. Additionally, each KeyPIN might have multiple rows if it is associated with different class codes or model groups. This can occur because many of Cook County's parcels have multiple class codes associated with them if they have multiple uses (such as residential and commercial). Users should not expect this data to be unique by any combination of available columns. Commercial properties are calculated by first determining a property’s use (office, retail, apartments, industrial, etc.), then the property is grouped with similar or like-kind property types. Next, income generated by the property such as rent or incidental income streams like parking or advertising signage is examined. Next, market-level vacancy based on location and property type is examined. In addition, new construction that has not yet been leased is also considered. Finally, expenses such as property taxes, insurance, repair and maintenance costs, property management fees, and service expenditures for professional services are examined. Once a snapshot of a property’s income statement is captured based on market data, a standard valuation metric called a “capitalization rate” to convert income to value is applied. This data was used to produce initial valuations mailed to property owners. It does not incorporate any subsequent changes to a property’s class, characteristics, valuation, or assessed value from appeals.Township codes can be found in the legend of this map. For more information on the sourcing of attached data and the preparation of this datase

Success.ai’s Commercial Real Estate Data and B2B Contact Data for Global Real Estate Professionals is a comprehensive dataset designed to connect businesses with industry leaders in real estate worldwide. With over 170M verified profiles, including work emails and direct phone numbers, this solution ensures precise outreach to agents, brokers, property developers, and key decision-makers in the real estate sector.

Utilizing advanced AI-driven validation, our data is continuously updated to maintain 99% accuracy, offering actionable insights that empower targeted marketing, streamlined sales strategies, and efficient recruitment efforts. Whether you’re engaging with top real estate executives or sourcing local property experts, Success.ai provides reliable and compliant data tailored to your needs.

Key Features of Success.ai’s Real Estate Professional Contact Data

• Comprehensive Industry Coverage Gain direct access to verified profiles of real estate professionals across the globe, including:

1. Real Estate Agents: Professionals facilitating property sales and purchases.
2. Brokers: Key intermediaries managing transactions between buyers and sellers.
3. Property Developers: Decision-makers shaping residential, commercial, and industrial projects.
4. Real Estate Executives: Leaders overseeing multi-regional operations and business strategies.
5. Architects & Consultants: Experts driving design and project feasibility.

• Verified and Continuously Updated Data

AI-Powered Validation: All profiles are verified using cutting-edge AI to ensure up-to-date accuracy. Real-Time Updates: Our database is refreshed continuously to reflect the most current information. Global Compliance: Fully aligned with GDPR, CCPA, and other regional regulations for ethical data use.

• Customizable Data Delivery Tailor your data access to align with your operational goals:

API Integration: Directly integrate data into your CRM or project management systems for seamless workflows. Custom Flat Files: Receive detailed datasets customized to your specifications, ready for immediate application.

Why Choose Success.ai for Real Estate Contact Data?

• Best Price Guarantee Enjoy competitive pricing that delivers exceptional value for verified, comprehensive contact data.

• Precision Targeting for Real Estate Professionals Our dataset equips you to connect directly with real estate decision-makers, minimizing misdirected efforts and improving ROI.

• Strategic Use Cases

  Lead Generation: Target qualified real estate agents and brokers to expand your network. Sales Outreach: Engage with property developers and executives to close high-value deals. Marketing Campaigns: Drive targeted campaigns tailored to real estate markets and demographics. Recruitment: Identify and attract top talent in real estate for your growing team. Market Research: Access firmographic and demographic data for in-depth industry analysis.

• Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 30M Company Profiles 700M Global Professional Profiles

• Powerful APIs for Enhanced Functionality

  Enrichment API Ensure your contact database remains relevant and up-to-date with real-time enrichment. Ideal for businesses seeking to maintain competitive agility in dynamic markets.

Lead Generation API Boost your lead generation with verified contact details for real estate professionals, supporting up to 860,000 API calls per day for robust scalability.

• Use Cases for Real Estate Contact Data

1. Targeted Outreach for New Projects Connect with property developers and brokers to pitch your services or collaborate on upcoming projects.

2. Real Estate Marketing Campaigns Execute personalized marketing campaigns targeting agents and clients in residential, commercial, or industrial sectors.

3. Enhanced Sales Strategies Shorten sales cycles by directly engaging with decision-makers and key stakeholders.

4. Recruitment and Talent Acquisition Access profiles of highly skilled professionals to strengthen your real estate team.

5. Market Analysis and Intelligence Leverage firmographic and demographic insights to identify trends and optimize business strategies.

• What Makes Us Stand Out? >> Unmatched Data Accuracy: Our AI-driven validation ensures 99% accuracy for all contact details. >> Comprehensive Global Reach: Covering professionals across diverse real estate markets worldwide. >> Flexible Delivery Options: Access data in formats that seamlessly fit your existing systems. >> Ethical and Compliant Data Practices: Adherence to global standards for secure and responsible data use.

Success.ai’s B2B Contact Data for Global Real Estate Professionals delivers the tools you need to connect with the right people at the right time, driving efficiency and success in your business operations. From agents and brokers to property developers and executiv...

Graph and download economic data for Commercial Real Estate Prices for United States (COMREPUSQ159N) from Q1 2005 to Q3 2024 about real estate, commercial, rate, and USA.

Dataset Overview

This dataset provides a detailed snapshot of real estate properties listed in Dubai, UAE, as of August 2024. The dataset includes over 5,000 listings scraped using the Apify API from Propertyfinder and various other real estate websites in the UAE. The data includes key details such as the number of bedrooms and bathrooms, price, location, size, and whether the listing is verified. All personal identifiers, such as agent names and contact details, have been ethically removed.

Data Science Applications

Given the size and structure of this dataset, it is ideal for the following data science applications:

• Price Prediction Models: Predicting the price of properties based on features like location, size, and furnishing status.
• Market Analysis: Understanding trends in the Dubai real estate market by analyzing price distributions, property types, and locations.
• Recommendation Systems: Developing systems to recommend properties based on user preferences (e.g., number of bedrooms, budget).
• Sentiment Analysis: Extracting and analyzing sentiments from the property descriptions to gauge the market's tone.

This dataset provides a practical foundation for both beginners and experts in data science, allowing for the exploration of real estate trends, development of predictive models, and implementation of machine learning algorithms.

# Column Descriptors

• title: The listing's title, summarizing the key selling points of the property.
• displayAddress: The public address of the property, including the community and city.
• bathrooms: The number of bathrooms available in the property.
• bedrooms: The number of bedrooms available in the property.
• addedOn: The timestamp indicating when the property was added to the listing platform.
• type: Specifies whether the property is residential, commercial, etc.
• price: The listed price of the property in AED.
• verified: A boolean value indicating whether the listing has been verified by the platform.
• priceDuration: Indicates if the property is listed for sale or rent.
• sizeMin: The minimum size of the property in square feet.
• furnishing: Describes whether the property is furnished, unfurnished, or partially furnished.
• description: A more detailed narrative about the property, including additional features and selling points.

# Ethically Mined Data

This dataset was ethically scraped using the Apify API, ensuring compliance with data privacy standards. All personal data such as agent names, phone numbers, and any other sensitive information have been omitted from this dataset to ensure privacy and ethical use. The data is intended solely for educational purposes and should not be used for commercial activities.

# Acknowledgements

This dataset was made possible thanks to the following:

• Apify: For providing the API to ethically scrape the data.
• Propertyfinder and various other real estate websites in the UAE for the original listings.
• Kaggle: For providing the platform to share and analyze this dataset.

-**Photo by** : Francesca Tosolini on Unsplash

Use the Data Responsibly

Please ensure that this dataset is used responsibly, with respect to privacy and data ethics. This data is provided for educational purposes.

Xverum’s Urban Planning Data is a comprehensive dataset of 230M+ verified locations, offering insights into commercial real estate, property trends, and urban development. Covering 5000 categories, our dataset supports real estate investors, urban planners, and policymakers in making data-driven decisions for infrastructure development, property market analysis, and zoning regulations.

With regular updates and continuous POI discovery, Xverum ensures your real estate and urban planning models have the latest property and commercial development data. Delivered in bulk via S3 Bucket or cloud storage, our dataset is ideal for GIS applications, market research, and smart city development.

🔥 Key Features:

Extensive Coverage for Urban Planning & Real Estate: ✅ 230M+ locations worldwide, spanning 5000 categories. ✅ Covers retail, office, industrial, hospitality, and mixed-use properties.

Geographic & Property Market Data: ✅ Latitude & longitude coordinates for precise mapping & real estate valuation. ✅ Property classifications, including commercial & mixed-use assets. ✅ Country, state, city, and postal code classifications for regional analysis.

Comprehensive Real Estate & Property Data: ✅ Property metadata, including location type, size, and market value insights. ✅ Business & commercial property listings for competitive analysis. ✅ Zoning data & regulatory insights for urban expansion & infrastructure planning.

Optimized for Real Estate & Urban Development: ✅ Supports market research, investment analysis & infrastructure development. ✅ Enhances real estate forecasting & planning applications. ✅ Provides in-depth insights for land use and smart city initiatives.

Bulk Data Delivery (NO API): ✅ Delivered in bulk via S3 Bucket or cloud storage. ✅ Available in a structured format (.json) for seamless integration.

🏆 Primary Use Cases:

Urban Planning & Infrastructure Development 🔹 Optimize land use planning, zoning, and city expansion projects. 🔹 Enhance GIS mapping with real estate & infrastructure data.

Real Estate Market Analysis & Investment Research: 🔹 Track commercial property trends & investment opportunities.

Smart City & Economic Growth Planning: 🔹 Identify high-growth regions for real estate & commercial expansion.

💡 Why Choose Xverum’s Urban Planning Data? - 230M+ Verified Locations – One of the largest & most structured real estate datasets available. - Global Coverage – Spanning 249+ countries, covering all real estate & property sectors. - Regular Updates & New Property Discoveries – Ensuring the highest accuracy. - Comprehensive Geographic & Market Metadata – Coordinates, zoning insights & property classifications. - Bulk Dataset Delivery – Direct access via S3 Bucket or cloud storage. - 100% Compliant – Ethically sourced & legally compliant.

Comprehensive dataset of 31,241 Commercial real estate agencies in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

South Carolina Real Estate Dataset 2025

Dataset Overview

This comprehensive real estate dataset contains over 5,000 property listings from South Carolina, collected in 2025 from Realtor.com using apify api. The dataset captures diverse property types including single-family homes, condominiums, land parcels, townhomes, and other residential properties. This dataset provides a rich snapshot of South Carolina's real estate market suitable for predictive modeling, market analysis, and investment research.

Data Science Applications

• Price Prediction Models: Build regression models (Random Forest, XGBoost, Neural Networks) to predict property values based on size, location, bedrooms, and age
• Property Type Classification: Develop multi-class classifiers to categorize properties based on physical characteristics
• Market Segmentation: Apply clustering algorithms (K-means, DBSCAN) to identify distinct property segments and price brackets
• Time Series Analysis: Analyze construction trends and property age distributions to forecast future development patterns
• Investment Opportunity Detection: Create anomaly detection models to identify undervalued properties or outliers
• Feature Engineering: Generate derived features like price per square foot, bathroom-to-bedroom ratios for enhanced model performance

Column Descriptors

• type: Primary property category (single_family, condos, land, townhomes, multi_family, farm)
• sub_type: Detailed property classification (condo, townhouse, co_op)
• sqft: Property size in square feet
• baths: Number of bathrooms (decimal values indicate half baths)
• beds: Number of bedrooms
• stories: Number of floors/stories in the property
• year_built: Construction year of the property
• listPrice: Property listing price in USD

Ethically Obtained Data

This dataset was ethically scraped from publicly available listings on Realtor.com and is provided strictly for educational and learning purposes only. The data collection complied with ethical web scraping practices and contains only publicly accessible information. Users should utilize this dataset exclusively for academic research, educational projects, and learning data science techniques. Any commercial use is strictly prohibited.

Discover the power of McGRAW’s comprehensive data solutions, the industry's largest and most complete property and ownership database in the nation. Additionally, the mortgage industry's most sought-after analytics solutions for loan quality, risk management, compliance, and collateral valuation. These data sets are built to empower businesses with reliable, accurate, and actionable insights across the mortgage, real estate, and title sectors. With access to over 150 million records and 200 attributes, our expansive data repository enables you to streamline decision-making, optimize marketing, and enhance customer targeting across industries. Take a look at the comprehensive data sets below:

Mortgage Data Our mortgage data encompasses loan origination, borrower profiles, mortgage terms, and payment statuses, providing a complete view of borrowers and mortgage landscapes. We deliver details on active and historical mortgages, including lender information, loan types, interest rates, and mortgage maturity. This empowers financial institutions and analysts to predict market trends, assess creditworthiness, and personalize customer outreach with accuracy.

Property Data McGRAW’s property data includes detailed attributes on residential and commercial properties, spanning property characteristics, square footage, zoning information, construction dates, and much more. Our data empowers real estate professionals, property appraisers, and investors to make well-informed decisions based on current and historical property details.

Title Data Our title data service provides a clear view of ownership history and title status, ensuring comprehensive information on property chain-of-title, lien positions, encumbrances, and transaction history. This invaluable data assists title companies, legal professionals, and financial institutions in validating title claims, mitigating risks, and reducing time-to-close.

Ownership Data McGRAW ownership data supplies in-depth insights into individual and corporate property ownership, offering information on property owners, purchase prices, and ownership duration. This dataset is crucial for due diligence, investment planning, and market analysis, giving businesses the competitive edge to identify opportunities and assess ownership patterns in the marketplace.

Unmatched Data Quality & Coverage Our data covers the full spectrum of residential and commercial properties in the United States, with attributes verified for accuracy and updated regularly. From state-of-the-art technology to rigorous data validation practices, McGRAW’s data quality stands out, providing the confidence that businesses need to make strategic decisions.

Why Choose McGRAW Data?

Extensive Reach: Over 150 million records provide unparalleled depth and breadth of data coverage across all 50 states.

Diverse Attributes: With 200 attributes across mortgage, property, title, and ownership data, businesses can customize data views for specific needs.

Actionable Insights: Our data analytics tools and customizable reports translate raw data into valuable insights, helping you stay ahead in the competitive landscape.

Leverage McGRAW’s data solutions to unlock a holistic view of the mortgage, property, title, and ownership landscapes. For real estate professionals, lenders, and investors seeking data-driven growth, McGRAW provides the tools to elevate decision-making, enhance operational efficiency, and drive business success in today’s data-centric market.

Extract detailed property data points — address, URL, prices, floor space, overview, parking, agents, and more — from any real estate listings. The Rankings data contains the ranking of properties as they come in the SERPs of different property listing sites. Furthermore, with our real estate agents' data, you can directly get in touch with the real estate agents/brokers via email or phone numbers.

A. Usecase/Applications possible with the data:

1. Property pricing - accurate property data for real estate valuation. Gather information about properties and their valuations from Federal, State, or County level websites. Monitor the real estate market across the country and decide the best time to buy or sell based on data

2. Secure your real estate investment - Monitor foreclosures and auctions to identify investment opportunities. Identify areas within special economic and opportunity zones such as QOZs - cross-map that with commercial or residential listings to identify leads. Ensure the safety of your investments, property, and personnel by analyzing crime data prior to investing.

3. Identify hot, emerging markets - Gather data about rent, demographic, and population data to expand retail and e-commerce businesses. Helps you drive better investment decisions.

4. Profile a building’s retrofit history - a building permit is required before the start of any construction activity of a building, such as changing the building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Use building permits to profile a city’s building retrofit history.

5. Study market changes - New construction data helps measure and evaluate the size, composition, and changes occurring within the housing and construction sectors.

6. Finding leads - Property records can reveal a wealth of information, such as how long an owner has currently lived in a home. US Census Bureau data and City-Data.com provide profiles of towns and city neighborhoods as well as demographic statistics. This data is available for free and can help agents increase their expertise in their communities and get a feel for the local market.

7. Searching for Targeted Leads - Focusing on small, niche areas of the real estate market can sometimes be the most efficient method of finding leads. For example, targeting high-end home sellers may take longer to develop a lead, but the payoff could be greater. Or, you may have a special interest or background in a certain type of home that would improve your chances of connecting with potential sellers. In these cases, focused data searches may help you find the best leads and develop relationships with future sellers.

How does it work?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

Dataset of commercial real estate delinquency rates, maturity wall projections, and Chicago market indicators for Q1 2025.

The dataset shows the real estate price for the second half of 2023, recorded through the Observatory of the Real Estate Market (OMI) managed by the Revenue Agency, which specifically processes and analyses all the technical and economic data and information concerning the value of a property and the rental market recorded in the Municipality of Milan.

The data shown in the Dataset are divided into:

The conservative state indicated by capital letters refers to the most frequent one of ZONE The Market Value is expressed in Euro/sqm referring to the Net Area (N) or Gross Area (L) The presence of the asterisk (*) next to the typology indicates that the relative Market or Rental Values have been corrected. For the Box, Parking spaces and Garage types, the different appreciation of the market according to the conservation status is not significant For the Shops type, the O/ N /S judgment is to be understood as referring to the commercial position and not to the conservation status of the real estate unit The IMO is to be considered as a full-fledged tool, through which the Revenue Agency ensures the transparency of the real estate market. The information provided shall be the sole property of the Agency. The customer is not allowed to sell, rent, rent, transfer, transfer the contents of the Database or assume some other obligations to third parties.

The information contained in the database can be used by the customer, also for the purpose of their processing provided that, in the case of publication, the relevant source is cited. For any further contractual conditions and use it is possible to connect to the link https://www.agenziaentrate.gov.it/portale/web/guest/fiche/fabbricatiterreni/omi/banche-data/quotas-real estate/conditions-contractual-qi.

Comprehensive dataset of 12 Commercial real estate inspectors in State of Rio Grande do Sul, Brazil as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 17 Commercial real estate agencies in Jeollabuk-do, South Korea as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Cash-and-Equivalents Time Series for CoStar Group Inc. CoStar Group, Inc. provides information, analytics, and online marketplace services in the United States, Canada, Europe, the Asia Pacific, and Latin America. It offers CoStar Property that provides inventory of office, industrial, retail, multifamily, hospitality, and student housing properties and land; CoStar Leasing, a data on lease transactions and tools to manage user-entered lease data; CoStar Sales, a database of commercial real estate sales transactions; CoStar Owners provides detailed portfolio information; CoStar Markets to view and report on market and submarket trends; and CoStar Tenant that provides tenant information. The company also provides CoStar Benchmarking allows hotels to measure performance against competitors; CoStar Lender, a tool for lenders to manage loan portfolios and risk; and real estate and lease management technology solutions, such as lease administration, lease accounting, and abstraction services. In addition, it offers Apartamentos.com, an apartment marketing sites; LoopNet.com, a commercial property marketing sites; Homes.com, a homes for sale listings site; Ten-X, an online auction platform for commercial real estate; Land.com, a marketplace for rural land sales; and BizBuySell.com, a marketplace for operating businesses and franchises for sale. It serves sales, leasing, and mortgage brokers; property, real estate investment trust, insurance companies, and asset managers; and government agencies, property owners, mortgage-backed security issuers, appraisers, design and construction professionals, pension fund managers, real estate developers, reporters tenant vendors, bankers, building services vendors, mortgage bankers, communications providers, retailers, institutional advisors, hospitality owners, investors, and real estate agents. The company was founded in 1987 and is headquartered in Arlington, Virginia.

Brazil Loans: Real Estate Financing: Units: Commercial Building: Market Rate data was reported at 176.000 Unit in Nov 2018. This records a decrease from the previous number of 481.000 Unit for Oct 2018. Brazil Loans: Real Estate Financing: Units: Commercial Building: Market Rate data is updated monthly, averaging 923.000 Unit from Dec 2009 (Median) to Nov 2018, with 108 observations. The data reached an all-time high of 4,389.000 Unit in Feb 2014 and a record low of 143.000 Unit in Apr 2011. Brazil Loans: Real Estate Financing: Units: Commercial Building: Market Rate data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Monetary – Table BR.KAB069: Loans: Real Estate Financing: Units: by Region: Commercial Building: Market Rate. The SFH uses the following features to provide credit to citizens: the Guarantee Fund for Time of Service - FGTS (eligible users are allowed the withdraw from FGTS for payment of Real Estate financing under SFH), the current account savings and loans raised in the country or abroad for the implementation of housing projects and mortgage bonds (debt securities) issued by financial agents. Under this scheme, funding can go up to 90% of property value, and cost effective maximum (which includes all charges and expenses incidental to the credit contracted or offered to individuals) may not exceed 12% per year, including interest, fees and other charges. O SFH utiliza os seguintes recursos para fornecer crédito aos cidadãos: o Fundo de Garantia por Tempo de Serviço - FGTS (é permitido o retirar do FGTS para o pagamento de financiamento imobiliário sob SFH), a poupança em conta corrente e empréstimos captados no país ou no exterior para a implementação de projetos de habitação e obrigações hipotecárias (títulos de dívida) emitidas pelos agentes financeiros. Ao abrigo deste regime, o financiamento pode ir até 90% do valor do imóvel, e o custo máximo efetivo (que inclui todos os encargos e despesas acessórias ao crédito contratado ou oferecido a pessoas físicas) não pode exceder 12% por ano, incluindo os juros, taxas e outras encargos.

This dataset outlines the percent changes in median Estimated Market Values and Parcel counts of commercial properties from 2019 to 2020

The dataset shows the real estate price for the first half of 2005, recorded through the Real Estate Market Observatory (OMI) managed by the Revenue Agency, which specifically processes and analyses all the technical and economic data and information concerning the value of a property and the rental market recorded in the Municipality of Milan. The data shown in the Dataset are divided into: * The conservative state indicated by capital letters refers to the most frequent one of ZONE * The Market Value is expressed in Euro/sqm referring to the Net Area (N) or Gross Area (L) * The presence of the asterisk (*) next to the typology indicates that the relative Market or Rental Values have been corrected. * For the Box, Parking spaces and Garage types, the different appreciation of the market according to the conservation status is not significant * For the type Shops the judgment O / N / S is to be understood as referring to the commercial position and not to the conservation status of the real estate unit The IMO is to be considered as a full-fledged tool, through which the Revenue Agency ensures the transparency of the real estate market. The information provided shall be the sole property of the Agency. The customer is not allowed to sell, rent, rent, transfer, transfer the contents of the Database or assume some other obligations to third parties. The information contained in the database can be used by the customer, also for the purpose of their processing provided that, in the case of publication, the relevant source is cited. For any further contractual conditions and use it is possible to connect to the link https://www.agenziaentrate.gov.it/portale/web/guest/fiche/fabbricatiterreni/omi/banche-data/quotas-real estate/conditions-contractual-qi.

Comprehensive dataset of 29 Commercial real estate agencies in Chungcheongnam-do, South Korea as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.