LandAtlas
accountingThe datasets combine commercial property transactions, lease market information, zoning approvals, land use permissions, and foreclosure performance into a realistic analytical environment suitable for exploratory data analysis, dashboard development, KPI reporting, market intelligence, investment analysis, urban planning, and risk assessment.
Whether you are learning SQL, Python, Excel, Power BI, Tableau, or preparing for careers in commercial real estate, property investment, urban planning, banking, financial services, housing analysis, or business intelligence, this collection provides realistic real estate scenarios for portfolio development.
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BĖ˛uĖ˛sĖ˛iĖ˛nĖ˛eĖ˛sĖ˛sĖ˛ Ė˛BĖ˛aĖ˛cĖ˛kĖ˛gĖ˛rĖ˛oĖ˛uĖ˛nĖ˛dĖ˛
Real estate markets are shaped by property values, commercial leasing activity, zoning regulations, and financial risk. Investors, developers, financial institutions, and government agencies continuously analyze these factors to support investment decisions, manage development projects, and monitor market stability.
Commercial real estate professionals evaluate property values, lease performance, and regional market conditions while urban planners monitor zoning approvals and land use regulations to guide sustainable development. Financial institutions and housing analysts track foreclosure activity to understand market risk and economic conditions.
Integrating commercial property, zoning, and foreclosure information enables organizations to identify investment opportunities, manage development risk, improve planning decisions, and strengthen long-term real estate strategies.
This dataset collection represents these interconnected real estate activities, allowing learners to analyze realistic operational data commonly used by commercial developers, banks, investment firms, municipalities, consulting firms, and property management organizations.
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WĖ˛hĖ˛aĖ˛tĖ˛\'Ė˛sĖ˛ Ė˛IĖ˛nĖ˛cĖ˛lĖ˛uĖ˛dĖ˛eĖ˛dĖ˛
âĸ Commercial Real Estate
âĸ Zoning & Land Use
âĸ Foreclosure Data
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LĖ˛eĖ˛aĖ˛rĖ˛nĖ˛iĖ˛nĖ˛gĖ˛ Ė˛OĖ˛bĖ˛jĖ˛eĖ˛cĖ˛tĖ˛iĖ˛vĖ˛eĖ˛sĖ˛
After working with this dataset you will be able to:
âĸ Analyze commercial property values across regions.
âĸ Evaluate lease pricing and lease duration trends.
âĸ Compare zoning categories and land development approvals.
âĸ Assess foreclosure activity across property types.
âĸ Analyze regional real estate market conditions.
âĸ Build executive real estate dashboards.
âĸ Support property investment decisions using data.
âĸ Evaluate urban planning and land use performance.
âĸ Develop real estate intelligence reports.
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SĖ˛kĖ˛iĖ˛lĖ˛lĖ˛sĖ˛ Ė˛YĖ˛oĖ˛uĖ˛\'Ė˛lĖ˛lĖ˛ Ė˛PĖ˛rĖ˛aĖ˛cĖ˛tĖ˛iĖ˛cĖ˛eĖ˛
âĸ SQL
âĸ Python
âĸ Pandas
âĸ Excel
âĸ Data Cleaning
âĸ Exploratory Data Analysis (EDA)
âĸ Real Estate Analytics
âĸ Property Analytics
âĸ Urban Planning Analytics
âĸ Business Intelligence
âĸ Power BI
âĸ Tableau
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BĖ˛uĖ˛sĖ˛iĖ˛nĖ˛eĖ˛sĖ˛sĖ˛ Ė˛QĖ˛uĖ˛eĖ˛sĖ˛tĖ˛iĖ˛oĖ˛nĖ˛sĖ˛
Examples include:
âĸ Which regions have the highest commercial property sale values?
âĸ How do lease prices vary across property types?
âĸ Which market conditions are associated with higher property values?
âĸ Which zoning categories receive the most development approvals?
âĸ How does land use permission vary across regions?
âĸ Which property types experience the highest foreclosure rates?
âĸ How do foreclosure outcomes change over time?
âĸ Which regions demonstrate the greatest commercial real estate opportunities?
âĸ How do zoning approvals influence regional development?
âĸ Which insights support property investment, urban planning, and real estate risk management?
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SĖ˛uĖ˛gĖ˛gĖ˛eĖ˛sĖ˛tĖ˛eĖ˛dĖ˛ Ė˛PĖ˛oĖ˛rĖ˛tĖ˛fĖ˛oĖ˛lĖ˛iĖ˛oĖ˛ Ė˛PĖ˛rĖ˛oĖ˛jĖ˛eĖ˛cĖ˛tĖ˛sĖ˛
âĸ Commercial Real Estate Dashboard
âĸ Property Investment Analytics
âĸ Lease Market Dashboard
âĸ Zoning & Land Development Dashboard
âĸ Foreclosure Risk Dashboard
âĸ Urban Planning Analytics
âĸ Real Estate Intelligence Report
âĸ End-to-End Property Analytics Project
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DĖ˛iĖ˛fĖ˛fĖ˛iĖ˛cĖ˛uĖ˛lĖ˛tĖ˛yĖ˛
Intermediate
Recommended for learners interested in commercial real estate, property investment, urban planning, financial services, housing analytics, and business intelligence.
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IĖ˛nĖ˛dĖ˛uĖ˛sĖ˛tĖ˛rĖ˛yĖ˛
âĸ Real Estate
âĸ Commercial Property
âĸ Property Investment
âĸ Urban Planning
âĸ Financial Services
âĸ Business Intelligence
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RĖ˛eĖ˛cĖ˛oĖ˛mĖ˛mĖ˛eĖ˛nĖ˛dĖ˛eĖ˛dĖ˛ Ė˛TĖ˛oĖ˛oĖ˛lĖ˛sĖ˛
âĸ Excel
âĸ SQL
âĸ Python
âĸ Pandas
âĸ Power BI
âĸ Tableau
âĸ Jupyter Notebook
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DĖ˛aĖ˛tĖ˛aĖ˛sĖ˛eĖ˛tĖ˛ Ė˛HĖ˛iĖ˛gĖ˛hĖ˛lĖ˛iĖ˛gĖ˛hĖ˛tĖ˛sĖ˛
âĸ 3 integrated real estate datasets
âĸ 3,000 total records
âĸ Excel format included
âĸ Commercial property sales, lease pricing, zoning regulations, land use approvals, and foreclosure activity.
âĸ Covers commercial property markets, urban planning, regulatory approvals, and real estate risk within a unified analytics collection.
âĸ Ideal for commercial real estate dashboards, investment analysis, zoning reporting, foreclosure monitoring, urban planning research, property valuation, and portfolio projects.
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VĖ˛aĖ˛lĖ˛uĖ˛eĖ˛ Ė˛PĖ˛rĖ˛oĖ˛pĖ˛oĖ˛sĖ˛iĖ˛tĖ˛iĖ˛oĖ˛nĖ˛
This collection is particularly valuable because it follows the complete commercial real estate decision-making process from property valuation and leasing through land development regulations and foreclosure risk assessment. Learners can investigate how commercial property values vary across markets, how zoning regulations influence development opportunities, how foreclosure activity reflects financial and economic conditions, and how these interconnected factors support property investment, urban planning, and market risk analysis. This integrated perspective closely reflects the work of commercial real estate investors, developers, urban planners, municipal authorities, financial institutions, housing analysts, property consultants, and business intelligence professionals responsible for evaluating investment opportunities, guiding development projects, and managing real estate risk.