Data includes House data of Mumbai, maharashtra area, you can find out different analysis with the help of above data

Data includes these are the columns : SR. AREA_TYPE
LOCATION
SIZE
TOTAL_SQFT BATH
BALCONY PRICE IN LAKHS

Hello my fellow data enthusiasts! I'm back!

My journey into the world of real estate data has been nothing short of exciting, and I’m thrilled to share the fruits of that adventure with you all. After spending a few weeks tinkering with APIs, parsing responses, and structuring data into something meaningful, I'm excited to present the CLEANEST Zillow Dataset you've every seen!

Analysts will be able to get actionable insights and a structured view into the fascinating world of property data.

Here’s the story behind the dataset: Zillow’s data provides a treasure trove of information, but raw responses can be messy with nested structures, and scattered details. So, I rolled up my sleeves and built a robust pipeline to extract key data points from each response. From property details to price history, every piece of information was carefully categorized and mapped into logical fields. My goal was to create a dataset that feels as polished and user-friendly as the apps we rely on daily.

What Makes This Dataset Special?

• Structured & Clean Data: Every property in the dataset has been meticulously processed, cleaned, and formatted to make analysis seamless.
• Comprehensive Coverage: Whether you're analyzing trends in property values or studying features that drive price differences, this dataset has you covered.
• Accessible Layout: Tables are structured logically, with relationships that make sense for analysts at every level. This dataset is more than just numbers – it’s a toolkit for anyone looking to dive into real estate analysis, build predictive models, or simply explore trends in the housing market.

If you have any questions, feedback, or just want to geek out about data, don’t hesitate to connect with me on LinkedIn or here on Kaggle. Let’s build something awesome together!

NOTES: I use Google's Cloud Composer to request this data and due to costs, I'm only grabbing data for properties that were recently put up for sale or sold within the day of execution. If you're looking for historical data, please reach out!

Disclaimer: This dataset is intended for non-commercial, academic purposes and does not infringe upon Zillow's intellectual property rights. For full details on Zillow's terms, please visit Zillow's Terms of Use.

Dive in, explore, and let me know what you think. Happy analyzing!

Other Datasets: - Spotify

Like other Assessor and Recorder data sets from First American, BlackKnight, ATTOM or HouseCanary, we provide both residential real estate and commercial restate data on homes, properties and pracels nationally.

Over 250M parcels, updated daily.

Access detailed property and tax assessment records with our extensive nationwide database. This robust dataset provides comprehensive information about residential and commercial properties, including detailed ownership, valuation, and transaction history. Core Data Elements:

Complete property identification (APNs, Tax IDs) Full property addresses with geocoding Precise latitude/longitude coordinates FIPS codes and Census tract information School district assignments

Property Characteristics:

Detailed lot dimensions and size Building square footage breakdowns Living area measurements Basement and attic specifications Garage and parking information Year built and effective year Number of bedrooms and bathrooms Room counts and configurations Building class and condition codes Construction details and materials Property amenities and features

Valuation Information:

Current AVM (Automated Valuation Model) values Confidence scores and value ranges Market valuations with dates Assessed values (land and improvements) Tax amounts and years Tax rate codes and districts Various tax exemption statuses

Transaction History:

Current and previous sale details Recording dates and document numbers Sale prices and price codes Buyer and seller information Multiple mortgage records including:

Loan amounts and terms Lender information Recording dates Interest rates Due dates Loan types and positions

Ownership Details:

Current owner information Corporate ownership indicators Owner-occupied status Mailing addresses Care of names Foreign address indicators

Legal Information:

Complete legal descriptions Subdivision details Lot and block numbers Zoning information Land use codes HOA information and fees

Property Status Indicators:

Vacancy flags Pre-foreclosure status Current listing status Price ranges Market position

Perfect For:

Real Estate Professionals

Property researchers Title companies Real estate attorneys Appraisers Market analysts

Financial Services

Mortgage lenders Insurance companies Investment firms Risk assessment teams Portfolio managers

Government & Planning

Urban planners Tax assessors Economic developers Policy researchers Municipal agencies

Data Analytics

Market researchers Data scientists Economic analysts GIS specialists Demographics experts

Data Delivery Features:

Multiple format options Regular updates Bulk download capability Custom field selection Geographic filtering API access available Standardized formatting Quality assured data

Quality Assurance:

Verified against public records Regular updates Standardized formatting Address verification Geocoding validation Duplicate removal Data normalization Quality control processes

This comprehensive property database provides unprecedented access to detailed property information, perfect for industry professionals requiring in-depth property data for analysis, research, or business development. Our data undergoes rigorous quality control processes to ensure accuracy and completeness, making it an invaluable resource for real estate professionals, financial institutions, and government agencies. Updated continuously from authoritative sources, this dataset offers the most current and accurate property information available in the market. Custom data extracts and specific geographic coverage options are available to meet your exact needs.

Weekly/Quarterly/Annual and One-time options are available for sale.

See our sample

This comprehensive housing data set provides valuable insights into the real estate market, encompassing various attributes of residential properties. The data includes the following key features:

• Apartment Type: Specifies the type of apartment, such as 3bhk,2bhk etc.
• Prices: The listed prices of the apartments, providing information on the cost of purchasing each property.
• Rate per Square Feet: The cost per square foot, offering a detailed understanding of property value relative to its size.
• Area: The total area of the apartment in square feet, helping to gauge the spaciousness of each property.
• Location: Geographic details of the property, including city and neighborhood, to analyze market trends in different areas.
• Status: The current status of the property, indicating whether it is ready for sale, under construction, resale or new, to track market availability and demand. This data set is ideal for real estate analysis, market trend studies, and decision-making processes related to property investments and housing market strategies.

Property Data Analytics for Mortgage Market Outlook

According to our latest research, the global property data analytics for mortgage market size reached USD 5.4 billion in 2024, reflecting robust demand for advanced data-driven solutions in the mortgage sector. The market is advancing at a noteworthy CAGR of 13.2% and is projected to achieve USD 15.5 billion by 2033. This growth is primarily driven by the increasing adoption of artificial intelligence (AI) and machine learning (ML) in property valuation and risk management, as well as the growing need for streamlined, efficient mortgage processes across the globe.

A primary growth factor fueling the expansion of the property data analytics for mortgage market is the increasing digitization of the real estate and financial sectors. As mortgage providers strive for operational efficiency, data analytics solutions are being leveraged to automate and optimize critical processes such as risk assessment, property valuation, and loan origination. The integration of big data, AI, and predictive analytics enables institutions to assess borrower risk more accurately, detect fraud, and enhance portfolio management. The surge in digital mortgage applications and the need for real-time insights have further accelerated the adoption of property data analytics, ensuring faster decision-making and improved customer experiences.

Another significant factor contributing to market growth is the stringent regulatory environment surrounding mortgage lending. Regulatory bodies worldwide are mandating higher standards for transparency, data accuracy, and risk mitigation in mortgage transactions. Property data analytics solutions help financial institutions comply with these regulations by providing comprehensive audit trails, automated compliance checks, and detailed reporting capabilities. This ability to ensure regulatory adherence while minimizing operational risks has become a crucial driver for market adoption, particularly among banks, mortgage lenders, and credit unions seeking to navigate complex regulatory landscapes efficiently.

Additionally, the proliferation of cloud computing and the emergence of advanced analytics platforms have lowered the barrier to entry for small and medium-sized enterprises (SMEs) in the mortgage sector. Cloud-based deployment models offer scalability, cost-effectiveness, and remote accessibility, making sophisticated property data analytics tools available to a wider range of end-users. This democratization of technology is fostering innovation and competition, leading to the development of more tailored, user-friendly solutions that address the unique needs of diverse market participants—from large banks to niche real estate agencies. As a result, the overall market is experiencing accelerated growth, with increasing adoption across various segments and regions.

In recent years, the integration of Mortgage Fraud Analytics AI has become increasingly crucial in the mortgage industry. This advanced technology leverages artificial intelligence to detect patterns and anomalies that may indicate fraudulent activities, providing a robust layer of security for financial institutions. By analyzing vast datasets, AI-driven analytics can identify inconsistencies in borrower information, unusual transaction patterns, and other red flags that traditional methods might overlook. This proactive approach not only helps in safeguarding assets but also ensures compliance with stringent regulatory requirements. As mortgage fraud becomes more sophisticated, the role of AI in fraud detection is expected to grow, offering a significant advantage to lenders who prioritize technological innovation.

From a regional perspective, North America currently dominates the property data analytics for mortgage market, accounting for the largest share in 2024. This leadership is attributed to the presence of major technology providers, a highly digitized mortgage ecosystem, and early adoption of advanced analytics solutions. Europe follows closely, driven by regulatory initiatives and the modernization of financial services. Meanwhile, the Asia Pacific region is witnessing the fastest growth, supported by rapid urbanization, expanding real estate markets, and increasing investments in digital transformation. Latin America and the Middle East & Africa are also emerging as promis

The Analyst Pro is a leading analysis and marketing platform for commercial real estate professionals, providing a comprehensive suite of tools for investment modeling, demographic analysis, and property marketing. With The Analyst Pro, users can easily create sophisticated reports, offering memorandums, flyers, and brochures, as well as analyze properties and make informed investment decisions.

The company offers a range of innovative features, including investment analysis, demographic analysis, location risk analysis, and more. These features enable commercial real estate professionals to gain a competitive edge in their market, streamline their workflow, and provide exceptional services to their clients. With The Analyst Pro, users can quickly and easily analyze properties, identify trends, and make data-driven decisions with confidence.

Description

Welcome to the "Real Estate Market Insights: Magic Bricks Web Scraped Dataset" available on Kaggle! This comprehensive dataset provides a wealth of information on real estate properties extracted from the popular real estate portal, Magic Bricks. With this dataset, you can explore and analyze the dynamic and ever-changing landscape of the real estate market.

Dataset Overview:

This dataset comprises meticulously scraped data from Magic Bricks, a prominent platform for buying, selling, and renting real estate properties in various regions. The dataset is regularly updated to ensure it reflects the most current market conditions and trends.

Key Features:

• Property Details: Gain access to a wide range of property details, including property type (apartment, house, commercial, etc.), location, size, and more.
• Price Information: Explore property prices, including listing price, area-based pricing, and price trends.
• Property Amenities: Discover the amenities and features associated with each property, from the number of bedrooms and bathrooms to parking availability and more.
• Property Status: Determine whether a property is available for sale, rent, or lease.

Use Cases:

• Market Analysis: Use this dataset to perform in-depth market analysis to understand price trends, property demand, and supply dynamics.
• Investment Opportunities: Identify potential investment opportunities in different regions based on price trends and property types.
• Location-Based Insights: Explore how property prices and amenities vary across different localities and cities.
• Real Estate Research: Use this dataset for academic research, business strategies, or data-driven decision-making.

Data Collection Method:

The dataset was collected using web scraping techniques, ensuring that it captures a wide array of properties listed on the Magic Bricks platform. Data integrity and accuracy are maintained through regular updates and quality checks.

Data Format:

The dataset is provided in a CSV format, making it easy to import and analyze using various data analysis tools and programming languages.

Disclaimer:

Please note that this dataset is for research and analytical purposes only. It is advisable to verify the data with Magic Bricks or other reliable sources before making any real estate transactions or investment decisions.

Explore the Redfin USA Properties Dataset, available in CSV format. This extensive dataset provides valuable insights into the U.S. real estate market, including detailed property listings, prices, property types, and more across various states and cities. Perfect for those looking to conduct in-depth market analysis, real estate investment research, or financial forecasting.

Key Features:

• Comprehensive Property Data: Includes essential details such as listing prices, property types, square footage, and the number of bedrooms and bathrooms.
• Geographic Coverage: Encompasses a wide range of U.S. states and cities, providing a broad view of the national real estate market.
• Historical Trends: Analyze past market data to understand price movements, regional differences, and market trends over time.
• Geo-Location Details: Enables spatial analysis and mapping by including precise geographical coordinates of properties.

Who Can Benefit From This Dataset:

• Real Estate Investors: Identify lucrative opportunities by analyzing property values, market trends, and regional price variations.
• Market Analysts: Gain a deeper understanding of the U.S. housing market dynamics to inform research and reporting.
• Data Scientists and Researchers: Leverage detailed real estate data for modeling, urban studies, or economic analysis.
• Financial Analysts: Utilize the dataset for financial modeling, helping to predict market behavior and assess investment risks.

Download the Redfin USA Properties Dataset to access essential information on the U.S. housing market, ideal for professionals in real estate, finance, and data analytics. Unlock key insights to make informed decisions in a dynamic market environment.

Looking for deeper insights or a custom data pull from Redfin?
Send a request with just one click and explore detailed property listings, price trends, and housing data.
🔗 Request Redfin Real Estate Data

The Property Intelligence Platform market is experiencing robust growth, driven by increasing demand for data-driven decision-making in the real estate sector. Technological advancements, such as AI and machine learning, are enhancing the capabilities of these platforms, providing more accurate and insightful property data analysis. This allows real estate professionals to make informed decisions regarding investments, valuations, risk assessment, and portfolio management. The market size in 2025 is estimated at $5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several factors, including the increasing adoption of cloud-based solutions, the growing need for efficient property management, and the expansion of the global real estate market. The rise of PropTech and the integration of various data sources, such as public records, transactional data, and market analytics, are further contributing to this expansion. The competitive landscape is highly fragmented, with a mix of established players and emerging startups. Key players like Yardi, VTS, and CoreLogic are leveraging their existing market presence and expertise to maintain their market share. However, agile startups are innovating with advanced analytical tools and specialized solutions, catering to niche market segments. Geographical expansion, particularly in emerging economies with rapidly growing real estate sectors, presents significant opportunities for both established and new entrants. The market's future growth will likely be shaped by the ongoing integration of data analytics, the development of more sophisticated predictive models, and the increasing adoption of these platforms by smaller real estate firms. The continued focus on enhancing data security and privacy will also play a crucial role in shaping the market's trajectory.

The n3 Real Estate company, a prominent player in the real estate industry, is a valuable resource for those seeking information on property listings and market trends. With a focus on providing accurate and reliable data, n3 Real Estate aggregates and consolidates information from various sources to give users a comprehensive view of the real estate market.

As a leading real estate data provider, n3 Real Estate offers a vast repository of information, covering everything from property listings and market analytics to sales trends and demographic data. The company's extensive database and robust tools enable users to gain insights into the real estate market, making it an essential resource for real estate professionals, investors, and homeowners alike. With its commitment to quality and accuracy, n3 Real Estate has established itself as a trusted authority in the real estate industry.

Snapshot img

US Real Estate Property Management Software Market Size 2025-2029

The us real estate property management software market size is forecast to increase by USD 447.3 million, at a CAGR of 6.1% between 2024 and 2029.

The Real Estate Property Management Software Market in the US is experiencing significant growth, driven by the increasing emphasis on customer-centric business processes. Property management companies are recognizing the value of streamlined operations and enhanced tenant experiences, leading to a surge in demand for advanced software solutions. Moreover, the adoption of big data analytics is transforming the industry, enabling data-driven decision-making and improved operational efficiency. However, the market faces challenges as well. The threat of open-source real estate property management software is growing, with some organizations opting for cost-effective alternatives. This trend could put pressure on established players to innovate and differentiate their offerings, ensuring they maintain a competitive edge. To capitalize on opportunities and navigate challenges effectively, companies must focus on delivering superior customer service, leveraging data insights, and continuously improving their technology offerings.

What will be the size of the US Real Estate Property Management Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The real estate property management market in the US is witnessing significant advancements, driven by the integration of smart home technologies and data backup solutions. Energy efficiency is a top priority, with regulatory compliance and property insurance companies encouraging the adoption of green building standards and sustainability certifications. Tenant screening services are utilizing background checks, credit history reports, and biometric authentication for thorough vetting processes. Artificial intelligence (AI) and machine learning are revolutionizing property management through predictive analytics, workflow optimization, and eviction prevention. Virtual tours and 3D modeling enable remote property inspections, while data visualization tools provide valuable insights for property investment analysis. Cloud security and mobile device management are essential for secure data access and management. Property risk management is a growing concern, with disaster recovery plans and property liability insurance playing crucial roles. Property management training and lease negotiation strategies are also key components in maintaining tenant retention. In summary, the US real estate property management market is undergoing a digital transformation, focusing on energy efficiency, regulatory compliance, tenant screening, and advanced technologies such as AI, data visualization, and predictive analytics. These trends are shaping the future of property management, offering increased efficiency, security, and profitability for businesses.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeIntegrated softwareStandalone softwareDeploymentCloud basedOn premisesApplicationResidentialCommercialIndustrialSectorLarge enterpriseSMEsIndividualsGeographyNorth AmericaUS

By Type Insights

The integrated software segment is estimated to witness significant growth during the forecast period.

Real estate property management software in the US integrates various applications to streamline operations for single-family homes, vacation rentals, student housing, and commercial properties. This software includes property marketing automation for tenant communication and listing platforms, occupancy management for rent collection and lease management, property accounting for financial reporting and automated payment processing, and property data analytics for value optimization and market trends. Compliance management ensures legal requirements, while property inspections and maintenance management maintain property conditions. API integration enables tenant screening and property investor collaboration. Cloud-based platforms offer accessibility and data security. Property portfolio management facilitates multifamily housing and building automation for energy efficiency. Insurance management and access control enhance security systems. Real estate agents and property managers can utilize these integrated features to effectively manage their property businesses.

Download Free Sample Report

The Integrated software segment was valued at USD 659.20 million in 2019 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data

The Housing Data Extracted from Homes.com (USA) dataset is a comprehensive collection of 2 million real estate listings sourced from Homes.com, one of the leading real estate platforms in the United States. This dataset offers detailed insights into the U.S. housing market, making it an invaluable resource for real estate professionals, investors, researchers, and analysts.

The dataset contains extensive property details, including location, price, property type (single-family homes, condos, apartments), number of bedrooms and bathrooms, square footage, lot size, year built, and availability status. Organized in CSV format, it provides users with easy access to structured data for analyzing trends, developing investment strategies, or building real estate applications.

Key Features:

• Record Count: 2 million housing listings from across the USA.
• Data Fields: Property address, price, property type, bedrooms, bathrooms, square footage, lot size, year built, and availability.
• Format: CSV format for easy integration with data analysis platforms, machine learning models, and real estate tools.
• Source: Directly sourced from Homes.com’s USA real estate listings.
• Geographical Focus: Comprehensive coverage of properties across all regions of the United States.

Use Cases:

• Real Estate Market Research: Analyze property prices, market trends, and housing demand in various U.S. regions.
• Investment Analysis: Use data to identify high-potential properties and regions for real estate investments.
• Property Comparison: Compare listings by price, location, and features to evaluate market conditions across different cities and states.
• Machine Learning Models: Build predictive models for price forecasting, property valuation, and real estate recommendation systems.
• Content Creation: Create real estate-related content, reports, and insights for the U.S. housing market using up-to-date data.

Property Data Analytics for Mortgage Market Outlook

According to our latest research, the global market size for Property Data Analytics for Mortgage reached USD 4.7 billion in 2024, reflecting the rapid adoption of advanced analytics in the mortgage sector. The market is poised for robust growth, projected to reach USD 13.5 billion by 2033, expanding at a CAGR of 12.2% from 2025 to 2033. This impressive growth is driven by the increasing necessity for data-driven decision-making, regulatory compliance, and the need to mitigate risk in the mortgage industry, as per our latest research findings.

The primary growth driver in the Property Data Analytics for Mortgage market is the surging demand for precise risk assessment and fraud detection capabilities. Financial institutions, mortgage lenders, and real estate agencies are under immense pressure to process high volumes of applications swiftly while minimizing default rates and fraudulent activities. Advanced analytics solutions are being deployed to analyze vast datasets, including credit scores, transaction histories, property values, and socio-economic factors, to generate actionable insights and predictive models. This not only enhances underwriting accuracy but also streamlines the loan approval process, resulting in greater operational efficiency and reduced costs. The integration of artificial intelligence and machine learning further amplifies the ability of these platforms to detect anomalies, identify patterns, and ensure robust risk management, making them indispensable in the modern mortgage landscape.

Another significant factor propelling the growth of the Property Data Analytics for Mortgage market is the evolving regulatory environment. Governments and regulatory bodies worldwide are enforcing stricter compliance requirements, particularly in areas such as anti-money laundering (AML), know your customer (KYC), and fair lending practices. Property data analytics platforms enable organizations to automate compliance checks, monitor transactions in real-time, and generate comprehensive audit trails. This not only reduces the risk of non-compliance and associated penalties but also enhances transparency and trust among stakeholders. As regulations continue to evolve, the adoption of advanced analytics solutions becomes a strategic imperative for organizations seeking to maintain a competitive edge and safeguard their reputations.

The digital transformation of the mortgage industry is also playing a pivotal role in market expansion. The proliferation of cloud-based analytics solutions has democratized access to sophisticated tools, enabling even small and medium-sized enterprises (SMEs) to leverage the power of big data. Cloud deployment offers scalability, flexibility, and cost-effectiveness, allowing organizations to process and analyze large volumes of property data without significant upfront investments in IT infrastructure. This shift towards cloud-based analytics is accelerating innovation, fostering collaboration among ecosystem participants, and driving the adoption of data-driven strategies across the mortgage value chain. As digitalization becomes ubiquitous, the demand for property data analytics solutions is expected to surge across all end-user segments.

From a regional perspective, North America continues to dominate the Property Data Analytics for Mortgage market, accounting for the largest share in 2024. The region's leadership is attributed to the presence of major financial institutions, early adoption of advanced technologies, and a highly regulated mortgage industry. However, Asia Pacific is emerging as the fastest-growing market, driven by rapid urbanization, increasing home ownership rates, and the digitalization of financial services. Europe also holds a significant share, supported by stringent regulatory frameworks and the proliferation of proptech startups. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, fueled by economic development and rising investments in real estate. Each region presents unique opportunities and challenges, shaping the competitive dynamics of the global market.

Component Analysis

The Component segment of the Property Data Analytics for Mortgage market is bifurcated into Software and Services, each playing a crucial role in the ecosystem.

Property Data Graphs Market Outlook

According to our latest research, the Global Property Data Graphs market size was valued at $2.1 billion in 2024 and is projected to reach $8.7 billion by 2033, expanding at a CAGR of 16.8% during 2024–2033. The primary factor driving the rapid growth of the Property Data Graphs market is the increasing demand for advanced data analytics and visualization tools in the real estate sector. With the proliferation of big data and the need for actionable insights, property data graphs are becoming indispensable for stakeholders seeking to make informed decisions, optimize investments, and streamline operations. The integration of artificial intelligence and machine learning into property data graph solutions is further accelerating market expansion by enabling predictive analytics, risk assessment, and automated valuation models.

Regional Outlook

North America currently holds the largest share of the global Property Data Graphs market, accounting for approximately 38% of the total market value in 2024. This dominance is attributed to the region’s mature real estate industry, robust technological infrastructure, and early adoption of digital transformation initiatives. The United States, in particular, has witnessed significant investments in property technology (PropTech) platforms, supported by favorable policies and the presence of leading market players. Additionally, the high penetration of cloud-based solutions and the growing trend of smart cities in North America have further fueled the adoption of property data graphs, making it a benchmark for other regions in terms of innovation and market maturity.

Asia Pacific is emerging as the fastest-growing region in the Property Data Graphs market, with a projected CAGR of 20.4% from 2024 to 2033. The surge in urbanization, rising disposable incomes, and a booming real estate sector in countries like China, India, and Southeast Asia are key drivers behind this growth. Governments across the region are investing heavily in digital infrastructure and smart city projects, which necessitate sophisticated data analytics tools for property management, valuation, and investment analysis. Furthermore, the increasing adoption of cloud-based solutions and mobile technologies in Asia Pacific is enabling real estate stakeholders to leverage property data graphs for enhanced operational efficiency and strategic decision-making.

In emerging economies across Latin America, the Middle East, and Africa, the Property Data Graphs market is witnessing gradual adoption, primarily due to challenges such as limited digital infrastructure, regulatory complexities, and lower awareness levels among end-users. However, localized demand is rising as governments and financial institutions recognize the value of data-driven insights for property valuation, risk management, and urban planning. Policy reforms aimed at improving transparency and digitization in real estate transactions are expected to create new opportunities for market players. The need for tailored solutions that address regional nuances and compliance requirements will be critical for driving adoption and unlocking the full potential of property data graphs in these markets.

Report Scope

Discover the explosive growth of the US real estate industry solutions market. This in-depth analysis reveals key trends, market size projections (2025-2033), and the impact of proptech on real estate investment, property management, and more. Learn about the leading technologies transforming the sector and the lucrative opportunities for investors. Key drivers for this market are: 4., Growth in Commercial Activities and Increased Competition4.; Increasing Demand for Affordable Housing Units. Potential restraints include: 4., Lack of Housing Spaces and Mortgage Regulation can Create Challenges. Notable trends are: Increase in Demand for Facility Management.

HousingCatalyst is a prominent real estate consultancy that provides in-depth market analysis and insights to investors, developers, and policymakers. With a focus on data-driven decision-making, the company's expertise spans market research, economic modeling, and strategic planning. Their online presence offers a treasure trove of information on the residential and commercial property markets, including demographic trends, housing affordability, and market forecasts.

By delving into HousingCatalyst's online repository, users can expect to find valuable data on emerging trends, market fluctuations, and regulatory changes that impact the real estate industry. The company's extensive research library is a goldmine of information for industry professionals, academics, and policymakers seeking to stay abreast of the latest developments in the sector. With a strong reputation for expertise and accuracy, HousingCatalyst's online presence is a go-to resource for those seeking insights to inform their real estate decisions.

LiveOverture is a reputable property data solutions provider that offers a wealth of information on property listings, market trends, and real estate data. The company's online presence provides insights into the property market, featuring thousands of listings, property sales data, and market analysis.

By leveraging LiveOverture's online resources, users can gain a deeper understanding of property values, trends, and market conditions, making it an invaluable resource for real estate professionals, investors, and individuals looking to buy, sell, or rent properties.

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.

REdistribute modernizes real estate data accessibility by providing access to fresh, reliable listings from trusted MLS sources.

For Market Insights & Analytics, this standardized bulk dataset enables: - Macro and micro-level housing market trend analysis - Competitive benchmarking and regional performance tracking - Consumer demand forecasting grounded in verified transaction activity

Key features: • Flexible Delivery: Available via a bulk data API or directly through Snowflake • Residential or Multi-Class: Choose a residential-only dataset or full MLS coverage across all property types, including residential, multi-family, land, commercial, rentals, farm and more • Comprehensive Field Access: Explore 800+ fields providing a complete view of both residential and non-residential property data • Fast & Fresh: Stay current with daily updates sourced directly from trusted MLSs partners

The sample data covers one listing in JSON format. For access to a broader set of sample listings (10,000+), reach out to the REdistribute sales contact.

ABOUT REDISTRIBUTE

REdistribute aims to modernize real estate data accessibility, fostering innovation and transparency through direct access to the most reliable MLS data. Our commitment to data integrity and direct MLS involvement guarantees the freshest, most accurate insights, empowering businesses across industries to drive innovation and make informed decisions.

Introduction

This dataset provide information the property of different houses and their selling prices.Through this dataset, we can understand how factors like bedrooms, bathrooms, area, and furnishing affect the price of a house.This dataset is beneficial for those student who learn prediction of price through data analysis or machine learning.

Context

One of the most frequent problems in the real estate sector is figuring out what influences property values. This dataset is used to construct prediction models that forecast property prices based on particular qualities and provides important insights into the housing market.

Content

• price:Selling price of the house
• area:Total area (in square feet)
• bedrooms:Number of bedrooms
• bathrooms:Number of bathrooms
• stories:Total floors in the house
• mainroad:Whether the house is connected to the main road (yes/no)
• guestroom:Availability of a guest room
• basement:Availability of a basement
• hotwaterheating:Whether hot water heating is available
• airconditioning:Whether air conditioning is available
• parking:Number of parking spaces
• prefarea:If the house is in a preferred area
• furnishingstatus:Furnishing condition (furnished, semi-furnished, unfurnished)