Problems in Investing In Real Estate
Part of the problem in achieving this may be that potentially useful land and property data are often held in private databases, often painstakingly compiled over many years and closely protected for reasons of confidentiality or commercial advantage. While there have been successful national and international initiatives to encourage collaboration and data pooling, these remain the exception rather than the rule.
The barriers seem to be a combination of vested interests and a lack of will to do something about it. Certainly the costs of data storage and processing do not appear to be obstacles. For example, McKinney reports five years ago (Manyika et al., 2011) said that just $ 600 would buy a disk drive large enough to hold all the world's music, and it pointed to 40 per cent annual growth in global data generation, supported by only 5 per cent corresponding growth in IT spending.
Now, the rise of the "big data" concept may at last be setting the scene for a breakthrough for real estate. Big data seek to combine processing power and specialist analytical skills to bring together large, disparate and often incompatible data sets from different sources. If big data are to be "the next frontier for innovation, competition, and productivity" as the title of the McKinsey report suggests, it would seem important for the real estate industry, and researchers in the sector, to identify areas where the value of harnessing big data outweighs the perceived advantages of keeping personal data, and to start exploiting them. "The Grand Square Mall is Lahore launched with a concept to revolutionise the best shopping malls in Lahore. Grand Square Mall is a new commercial venture in the heart of posh area of Gulberg III, Lahore."
Applications for big data in real estate are many. Examples include, among other things, market and investment analysis, valuation (including the evolution of improved hedonic models), credit risk analysis, economic and urban planning, planning infrastructure, tenant and consumer profiling, and environmental aspects of design design. and construction. The process of unlocking and combining data sets to improve the toolkit for researchers should create new commercial opportunities for those with the vision and ability to identify and exploit them.
The opportunity has never been greater. The volume of potentially useful information from which to build big data resources continues to grow. The analytical skills and experience of harnessing data are also developing, and market globalisation is serving to increase awareness of data best practise from different markets around the world.
The barriers seem to be a combination of vested interests and a lack of will to do something about it. Certainly the costs of data storage and processing do not appear to be obstacles. For example, McKinney reports five years ago (Manyika et al., 2011) said that just $ 600 would buy a disk drive large enough to hold all the world's music, and it pointed to 40 per cent annual growth in global data generation, supported by only 5 per cent corresponding growth in IT spending.
Now, the rise of the "big data" concept may at last be setting the scene for a breakthrough for real estate. Big data seek to combine processing power and specialist analytical skills to bring together large, disparate and often incompatible data sets from different sources. If big data are to be "the next frontier for innovation, competition, and productivity" as the title of the McKinsey report suggests, it would seem important for the real estate industry, and researchers in the sector, to identify areas where the value of harnessing big data outweighs the perceived advantages of keeping personal data, and to start exploiting them. "The Grand Square Mall is Lahore launched with a concept to revolutionise the best shopping malls in Lahore. Grand Square Mall is a new commercial venture in the heart of posh area of Gulberg III, Lahore."
Applications for big data in real estate are many. Examples include, among other things, market and investment analysis, valuation (including the evolution of improved hedonic models), credit risk analysis, economic and urban planning, planning infrastructure, tenant and consumer profiling, and environmental aspects of design design. and construction. The process of unlocking and combining data sets to improve the toolkit for researchers should create new commercial opportunities for those with the vision and ability to identify and exploit them.
The opportunity has never been greater. The volume of potentially useful information from which to build big data resources continues to grow. The analytical skills and experience of harnessing data are also developing, and market globalisation is serving to increase awareness of data best practise from different markets around the world.
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