Cloud analytics is actively applied in the field of real estate investment and portfolio optimizations in today's business environment. Solutions created by AWS, Microsoft Azure, and Google Cloud Platform (GCP) provide the opportunities to manage the portfolio by ingesting data, performing predictive modeling, and visualizing data sets. The current paper aims at analyzing the role of cloud analytics in data-driven portfolio optimization in seven markets: Saudi Arabia, UAE, Qatar, Oman, India, the United Kingdom, and the United States. There are a lot of developments concerning the application of predictive analytics and machine learning in recent years. The results of the JLL 2025 Global CRE Technology Survey report that 92% of the companies in the CRE sectors are running AI pilots, whereas the share was 5% in 2023 [13]. The accuracy rate of estimates made with machine learning algorithms in relation to property prices and rental demand stands between 82% and 91% [22]. It is claimed that there are potential profits worth $1.3 trillion in the global real estate sector [17]. IoT devices installed in smart buildings allow saving up to 25% on operating expenses [3]. Moreover, 60% of all sales in Dubai involve blockchain technology [30]. In each market, cloud analytics drivers have their peculiarities. The total value of the Vision 2030 program implemented in Saudi Arabia is over $819 billion, while the average annual growth rate of proptech market is 16.09% [1]. The Real Estate Data Cube in Dubai contains information that can be accessed publicly; it is used to train algorithms, and the accuracy rate of predictions reached 92% [3]. The HM Land Registry in the UK invested £72 million into digital transformation, using AI to save about £59 million annually due to fraud [10, 11]. The Indian proptech market assessed at $1.72 billion makes use of cloud business intelligence software; over 70% of large companies apply such solutions [8]. Statista reports that the total market size in 2025 equals $752 billion and it is going to reach $2.39 trillion by 2030 [25]. In terms of the real estate sector, 89% of firms use multiple clouds, whereas 52% of enterprise workloads happen in public clouds [19-25]. In this paper, the architecture of cloud analytics will be analyzed along with the comparison of the products by the leading providers, several case studies in seven countries, and the implementation roadmap.