Graph and download economic data for Real Residential Property Prices for United Arab Emirates (QAER771BIS) from Q1 2004 to Q1 2024 about United Arab Emirates, residential, HPI, housing, real, price index, indexes, and price.

According to ValuStrat, the average residential prices in Dubai reached around ***** United Arab Emirates dirhams (AED) in December 2023, rising from around *** AED in 2020. Real estate market in Dubai Despite the impact of the global COVID-19 pandemic on the real estate market, Dubai's real estate sector continues to show resilience and remains a lucrative investment option. In the first quarter of 2021, the real estate transactions in Dubai amounted to approximately ** billion U.S. dollars in value. With its emphasis goal of transforming into a high-end tourist destination, Dubai has become an appealing choice for real estate investors. In 2019, investment villas made up most urban buildings in the emirate, with around ** thousand units. Residential market outlook The residential market in Dubai has experienced substantial growth in recent years. In 2022, it was projected to witness the addition of approximately ** thousand new apartments and ***** thousand new villas. These additions contribute to the existing supply of *** thousand residential units in the emirate for that year. According to the same source, in December 2022, the capital prices of residential apartments in Jumeirah Beach Residence, Dubai, stood at approximately *** million United Arab Emirates dirhams. This represented a *** percent growth in capital values compared to the prior year. With its strong market presence and attractive investment opportunities, Dubai's residential market remains a key player in the region.

Key information about United Arab Emirates Gold Production

• United Arab Emirates Real Residential Property Price Index was reported at 143.490 2010=100 in Mar 2024.
• This records an increase from the previous number of 137.212 2010=100 for Dec 2023.
• United Arab Emirates Real Residential Property Price Index data is updated quarterly, averaging 135.369 2010=100 from Mar 2003 to Mar 2024, with 85 observations.
• The data reached an all-time high of 165.357 2010=100 in Sep 2014 and a record low of 86.733 2010=100 in Sep 2003.
• United Arab Emirates Real Residential Property Price Index data remains active status in CEIC and is reported by Bank for International Settlements.
• The data is categorized under World Trend Plus’s Association: Property Sector – Table RK.BIS.RPPI: Selected Real Residential Property Price Index: 2010=100: Quarterly. [COVID-19-IMPACT]

Dubai, UAE Rental Properties Dataset

👨‍💻 Author: Azhar Saleem

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This dataset presents a comprehensive overview of rental property listings across multiple cities in the United Arab Emirates, including Abu Dhabi, Dubai, Sharjah, Ajman, Ras Al Khaimah, Umm Al Quwain, and Al Ain. Compiled from bayut.com, it is a valuable resource for Data Analysts, Data Scientists, and Researchers looking to explore real estate trends, rental pricing patterns, or urban development studies in the UAE.

Dataset Overview

Each entry in the dataset represents a rental property listing with details about the property's features, rental terms, and location specifics. This primary and unique dataset is designed for analysis and can be used to generate insights into the rental market dynamics of the UAE.

Columns Description

• Address: Full address of the property.
• Rent: The annual rent price in AED.
• Beds: Number of bedrooms in the property.
• Baths: Number of bathrooms in the property.
• Type: Type of property (e.g., Apartment, Villa, Penthouse).
• Area_in_sqft: Total area of the property in square feet.
• Rent_per_sqft: Rent price per square foot, calculated as Rent divided by Area_in_sqft.
• Rent_category: Categorization of the rent price (Low, Medium, High) based on thresholds.
• Frequency: Rental payment frequency, which is consistently 'Yearly'.
• Furnishing: Furnishing status of the property (Furnished, Unfurnished).
• Purpose: The purpose of the listing, typically 'For Rent'.
• Posted_date: The date the property was listed for rent.
• Age_of_listing_in_days: The number of days the listing has been active since it was posted.
• Location: A more specific location within the city where the property is located.
• City: City in which the property is situated.
• Latitude, Longitude: Geographic coordinates of the property.

Usage

This dataset is open for public use and is particularly suited for:

• Analyzing trends in the rental market.
• Studying the geographical distribution of rental properties.
• Comparing rental prices across different cities and property types.
• Developing machine learning models to predict rental prices or classify property types.

Feel free to explore this dataset and derive meaningful insights to understand the dynamics of the UAE rental market.

Dubai, UAE Real Estate Market Dataset

👨‍💻 Author: Azhar Saleem

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Dataset Description

This comprehensive dataset provides an exhaustive snapshot of property listings for sale across the United Arab Emirates, including major cities like Dubai, Abu Dhabi, and Al Ain. Sourced from Bayut.com, this dataset serves as an invaluable resource for Data Scientists, Real Estate Analysts, Urban Planners, and Developers keen on exploring real estate market dynamics, price fluctuations, and development trends in the UAE.

Dataset Overview

The dataset contains over 41,000 entries, each representing a unique property for sale. It includes detailed information such as:

• Price: Listing price of the property in AED.
• Type: Specifies the property type, such as Apartment, Townhouse, etc.
• Beds: Number of bedrooms, with '0' indicating a studio flat.
• Baths: Number of bathrooms.
• Address: Full address of the property, providing insights into its precise location.
• Furnishing: Indicates whether the property is furnished or unfurnished.
• Completion Status: Current status of the property (Ready, Off-Plan).
• Building Name, Area Name, City: Provide contextual location details.
• Year of Completion: Year when the property was completed or is expected to be completed.
• Total Floors, Parking Spaces, Building Area: Key features of the property's building.
• Latitude, Longitude: Geographic coordinates for more refined location analysis.
• Purpose: Intended purpose of the listing, consistently noted as 'For Sale'.

Usage

This dataset is ideal for a variety of applications, including:

• Market Analysis: Analyze trends in property prices and types across different regions.
• Predictive Modeling: Develop machine learning models to predict property prices or to classify types of properties based on their features.
• Urban Development Studies: Examine property distribution and characteristics to inform urban planning and development strategies.
• Comparative Analysis: Compare properties across different cities and districts to identify investment opportunities or to study market behavior.

Data Accessibility

This dataset is publicly available and well-suited for anyone interested in conducting detailed analyses of the UAE real estate market, from academic researchers to industry professionals.

Feel free to dive into this dataset to unlock comprehensive insights into the vibrant and diverse property market of the UAE, supporting a wide range of real estate, economic, and geographic studies.

This dataset provides comprehensive information on various types of real estate transactions in Dubai, including property sales, rentals, and transfers. It covers a wide range of transaction details, such as property type, usage, registration, area, building and project information, nearest landmarks, facilities, and transaction values.

Data is published with open data license https://www.dubaipulse.gov.ae/docs/DDE%20_%20DRAFT_Open_Data%20Licence_LONG_Form_English%203.pdf

Dataset Contents: The dataset includes the following variables:

1. transaction_id: Unique identifier for each transaction.
2. procedure_id: Identifier for the transaction procedure type.
3. trans_group_id: Identifier for the transaction group.
4. trans_group_ar: Transaction group name in Arabic.
5. trans_group_en: Transaction group name in English.
6. procedure_name_ar: Procedure name in Arabic.
7. procedure_name_en: Procedure name in English.
8. instance_date: Date of the transaction.
9. property_type_id: Identifier for the property type.
10. property_type_ar: Property type in Arabic.
11. property_type_en: Property type in English.
12. property_sub_type_id: Identifier for the property sub-type.
13. property_sub_type_ar: Property sub-type in Arabic.
14. property_sub_type_en: Property sub-type in English.
15. property_usage_ar: Property usage in Arabic.
16. property_usage_en: Property usage in English.
17. reg_type_id: Identifier for the registration type.
18. reg_type_ar: Registration type in Arabic.
19. reg_type_en: Registration type in English.
20. area_id: Identifier for the area in Dubai.
21. area_name_ar: Area name in Arabic.
22. area_name_en: Area name in English.
23. building_name_ar: Building name in Arabic.
24. building_name_en: Building name in English.
25. project_number: Project number.
26. project_name_ar: Project name in Arabic.
27. project_name_en: Project name in English.
28. master_project_en: Master project name in English.
29. master_project_ar: Master project name in Arabic.
30. nearest_landmark_ar: Nearest landmark in Arabic.
31. nearest_landmark_en: Nearest landmark in English.
32. nearest_metro_ar: Nearest metro station in Arabic.
33. nearest_metro_en: Nearest metro station in English.
34. nearest_mall_ar: Nearest mall in Arabic.
35. nearest_mall_en: Nearest mall in English.
36. rooms_ar: Number of rooms in Arabic.
37. rooms_en: Number of rooms in English.
38. has_parking: Indicates whether the property has parking facilities.
39. procedure_area: Area of the property involved in the transaction.
40. actual_worth: Actual worth of the property at the time of the transaction.
41. meter_sale_price: Sale price per square meter for the property.
42. rent_value: Rent value of the property (if applicable).
43. meter_rent_price: Rent price per square meter for the property (if applicable).
44. no_of_parties_role_1: Number of parties involved with role 1 in the transaction.
45. no_of_parties_role_2: Number of parties involved with role 2 in the transaction.
46. no_of_parties_role_3: Number of parties involved with role 3 in the transaction.

Usage Ideas: The dataset can be used for various purposes, including:

1. Analyzing the real estate market trends in Dubai.
2. Identifying patterns and relationships between property types, locations, and transaction values.
3. Evaluating the impact of government policies and regulations on the real estate market.
4. Assessing market demand and supply for various property types and locations.
5. Developing predictive models for real estate prices and rental rates.

Acknowledgements: This dataset is sourced from the Dubai Land Department's open transaction data. The original data is collected and maintained by the Dubai government.