How We Calculate

1. Data Sources

All analytics on DXB Analytics are derived from official government open data:

2. Price Metrics

Average Price Per Square Foot (PSF)

Calculated as the simple arithmetic mean of price per square foot across all qualifying transactions in the selected period and area:

Each transaction is weighted equally regardless of property size.

Outlier Handling

We exclude transactions where:

• Property size is 0 or missing
• Price per sqft is below 10 AED or above 100,000 AED (clear data errors)
• Transaction value is 0

Total Volume

Sum of all transaction values (actual_worth) in AED for the selected period.

3. Growth & CAGR

CAGR Formula

We use Compound Annual Growth Rate rather than simple year-over-year change, as it smooths out volatility and gives a more accurate picture of long-term trends:

Example

Why CAGR Over Simple YoY?

Simple year-over-year can be misleading if a single year had unusual activity. CAGR gives a smoothed annualized rate that's more useful for comparing areas across different time periods.

Year Range Impact

The selected year range directly affects CAGR. A range starting in 2020 (COVID dip) will show higher growth than one starting in 2014 (market peak). Always consider the range when comparing.

4. Investment Score

A composite score from 0 to 100 combining three weighted factors:

Score Interpretation

⚠️ The investment score is a simplified heuristic. It does not account for macroeconomic factors, regulatory changes, or area-specific risks. Always do your own due diligence.

5. Rental Yield

Gross Yield Formula

Type-Matching Methodology

We compare like with like. Rental yield for flats is calculated using flat rental data and flat sale prices. Same for villas. Mixing property types would produce misleading yields since villas and apartments have very different price-to-rent ratios.

Why Median Over Average?

Dubai real estate has significant outliers — a single penthouse sale at 50,000 AED/sqft can skew averages dramatically. The median is more robust and better represents the "typical" transaction.

Minimum Sample Size

We require at least 20 sales transactions and 20 rental contracts in an area before displaying a rental yield. Below this threshold, the data is too sparse to be meaningful.

Data Filtering

• Only residential properties (excludes commercial, retail, industrial)
• Annual rent capped at 2,000,000 AED (higher values are likely data errors or ultra-luxury outliers)
• Rental data from the most recent 12 months; sale data from the selected period

Known Limitations

• This is gross yield — does not account for service charges, maintenance, vacancy, or management fees
• Net yield is typically 1–3% lower depending on the property
• Ejari data may not capture all informal rental arrangements
• Size matching is approximate (we use area-level medians, not unit-level matching)

6. Sentiment Analysis

Source

Community sentiment scores are derived from Reddit discussions and social media posts about Dubai areas. We analyze r/dubai, r/DubaiRealEstate, and related subreddits.

Scoring Methodology

Each mention is scored on a 1–5 scale using natural language processing. The overall area score is the weighted average of all mentions, with more recent posts weighted higher. Positive and negative themes are extracted and categorized.

Update Frequency

Sentiment data is refreshed weekly. Areas with fewer than 5 mentions show as "No data" (gray) on the map.

7. Area Classification

Area Definition

Areas are defined by the DLD's own area_en field, normalized to URL-friendly slugs (e.g., "Palm Jumeirah" → palm-jumeirah).

Community Mapping

DLD uses administrative zone names (e.g., "Wadi Al Safa 3", "Al Hebiah Fourth") that often don't match the community names people know. A single DLD zone may contain multiple well-known communities. We map these using the DLD's master_project field:

• Wadi Al Safa 3 → Al Barari, Living Legends, Majan
• Al Hebiah Fourth → Dubai Sports City, Tilal Al Ghaf
• Madinat Hind 4 → DAMAC Hills 2
• Al Yelayiss 2 → Town Square
• Al Merkadh → Sobha Hartland, Meydan / District One

In total, 49 communities are mapped from DLD zones to recognizable names. Each community's data is filtered to only include transactions belonging to that specific development, ensuring accurate per-community analytics. Areas that already have clear names (e.g., Business Bay, Palm Jumeirah, Dubai Marina) are kept as-is.

Coordinate Mapping

Area coordinates for the interactive map are sourced through a multi-step process:

1. Automated geocoding — area names are geocoded via the OpenStreetMap Nominatim API, with results validated to fall within Dubai's geographic bounds (lat 24–26, lng 54–56).
2. Manual mapping — DLD uses non-standard area names that don't always match public map databases (e.g., "Al Goze Fourth" = Al Quoz 4, "Al Thanyah Fifth" = JLT). These are mapped manually to the correct coordinates.
3. Community projects — virtual community-level entries (e.g., The Villa, Dubai Hills Estate sub-communities) are mapped to the center of the relevant development.

Currently 154 areas (105 DLD areas + 49 communities) are mapped with coordinates, covering the vast majority of transaction activity. Some very small or industrial areas may share approximate coordinates if they overlap geographically. "Nearby Areas" on detail pages is based on straight-line distance between these coordinates.

8. Limitations & Disclaimers

Data Lag

DLD transaction data is typically published with a 1–3 month delay. Recent months may show lower-than-actual volumes as transactions haven't been registered yet.

Composition Effects

Average PSF can shift even without actual price changes if the mix of properties sold changes. For example, if more studios sell in one month (lower PSF) and more penthouses the next (higher PSF), the average PSF will fluctuate without any real price movement.

Off-Plan vs Ready

Off-plan properties are typically priced differently from ready/completed properties. By default, our metrics include both. Use the sale type filter to isolate off-plan or ready transactions for cleaner comparisons.

Historical Data Quality

Earlier records (2002–2010) may have inconsistencies in property type classification, size measurements, and area naming. We recommend focusing on 2015+ data for the most reliable analysis.