SQL Analysis of Dubai's Off Plan Property Market

La Breeze Limited is a private limited company specializing in real estate investments and development. This project focuses on identifying emerging trends and opportunities within Dubai's off-plan property sector. The property data used for this analysis is publicly available on Kaggle here: [https://www.kaggle.com/datasets/alexefimik/dubai-real-estate-transactions-dataset]

Insights and recommendations are provided on the following key areas:

• Frequency Analysis by Property: Analysing the frequency of each off-plan property (e.g. flat, hotel, office) across regions and over time
• Regional Comparison Analysis: An evaluation of average sales per square mile according to each region. Regions being judged by nearest metro station, landmark or mall
• Property Sales Trend Analysis: An assessment of property sales trend per square mile trends over time

The SQL queries used to inspect and clean the data for this analysis can be found here [https://github.com/Mohammed0192/Dubai-Off-Plan-Property-analysis/blob/main/SQL%20query%20code]

Targed SQL queries regarding various business questions can be found here [link].

An interactive Tableau dashboard used to report and explore sales trends can be found here [link].

Data Structure & Initial Checks

The companies main database structure as seen below consists of four tables: table1, table2, table3, table4, with a total row count of X records. A description of each table is as follows:

• Properties Table: Dubai properties data structure consists date, varchar and numerical data

[https://github.com/Mohammed0192/Dubai-Off-Plan-Property-analysis/issues/1#issue-2636534920]

Executive Summary

Overview of Findings

Across Dubai overall, hotels have remained the most expensive off-plan property purchases despite having the largest percentage decrease in average price (per square mile) in the last 3 years. There has been an apparent increase in the prices of OPP shops (per square mile) being purchased across Dubai also. Post-COVID, the average price of OPP flats has decreased but flats in the Mina Seyahi and Jumeirah Beach region have enjoyed noticeable price hikes. Another post-COVID trend are falling OPP office prices across Dubai, perhaps reflecting the post-COVID desire for workers to WFH?

Insights Deep Dive

Growing popularity of Al-Kasir / Marina Area::

• 1: More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• 2: More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• 3 More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• 4 More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

[Visualization specific to category 1]

Flats over Hotels in downtown areas:

• Hotels purchases are less popular more centralised. Less purchases are being made in the surrounding Dubai areas and becoming centralised in downtown areas (e.g. Dubai and Marina Mall)

• Flats are more popular across Dubai. OPP flats are becoming increasing popular over time especially in downtown areas but also across Dubai (e.g. other malls like Ibn Battuta and Mirdif) .

• Main insight 3. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 4. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

Office properties are in less demand post-COVID:

• Main insight 1. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 2. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 3. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 4. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

[Visualization specific to category 3]

Growing demand for Shop properties in Jebel Ali Village:

• Main insight 1. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 2. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 3. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

• Main insight 4. More detail about the supporting analysis about this insight, including time frames, quantitative values, and observations about trends.

[Visualization specific to category 4]

Recommendations:

Based on the insights and findings above, we would recommend the [stakeholder team] to consider the following:

• Specific observation that is related to a recommended action. Recommendation or general guidance based on this observation.

• Specific observation that is related to a recommended action. Recommendation or general guidance based on this observation.

• Specific observation that is related to a recommended action. Recommendation or general guidance based on this observation.

• Specific observation that is related to a recommended action. Recommendation or general guidance based on this observation.

• Specific observation that is related to a recommended action. Recommendation or general guidance based on this observation.

Assumptions and Caveats:

Throughout the analysis, multiple assumptions were made to manage challenges with the data. These assumptions and caveats are noted below:

• Assumption 1 (ex: missing country records were for customers based in the US, and were re-coded to be US citizens)

• Assumption 1 (ex: data for December 2021 was missing - this was imputed using a combination of historical trends and December 2020 data)

• Assumption 1 (ex: because 3% of the refund date column contained non-sensical dates, these were excluded from the analysis)