Big data is the basis for business intelligence, which is about taking all that information and turning it into knowledge to drive better business decisions. Whether its data about retail consumers or homebuyers, it's all the same game.  The business intelligence industry has been analyzing large data sets in corporations for years — decades, really. It’s only now coming to the real estate industry. The amount of data used in the real estate industry isn’t that large. A single major retailer will generate more sales data in a year than the entire real estate industry will in a decade. However, it’s all relative, and the real estate industry is still trying to figure out what data it has, let alone how to use it.

The point is that big data in real estate is about presenting a “whole consumer” picture. It’s about using data to find out who buys what, when, where, why and how. It’s about finding out who will sell a house — when, where, why and how. 

All that data can be used to create tangible insights into consumer behavior using forecasting and modelling software. It’s the analysis that makes the magic happen, that is identifying customers or providing them better services. Analytics is where raw data and the algorithms that crunch it come together. Mining census information, the results of consumer surveys, listings of homes for sale and rent, geographic information systems data and more combine what they draw from numerous databanks with their own proprietary user-generated content. The tools can deliver to consumer’s information about their property's potential value and help them understand home-value trends within a particular milieu, such as a neighborhood or a ZIP code. 

Beyond the consumer and industry-facing aspects of big data, institutions such as banks can plug into big data resources to determine whether a foreclosure or short sale is really worth what a buyer or investor might be offering.

For now, the analysis of big data is likely to stay with those who gather it and companies willing to pay for access, such as the lead generation companies. What real estate agents need to know now is that the data is there and it’s available, in some form or another, to those who are willing to use the right tools.  Read more at: http://mashable.com/2014/07/09/big-data-real-estate/

A Geographic Information System (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts. It helps you answer questions and solve problems by looking at your data in a way that is quickly understood and easily shared. There are a lot of advantages of using GIS technology. It makes data handling easier, covers large area, used for monitoring various things because of repetitive coverage, it is fast, can be used in inaccessible areas, unbiased, more accurate, reliable and economical. Data could be collected in several bands/ colors so it could be used for micro level analysis. GIS will help in decision making by government officials and in increasing transparency and accountability for good governance. It will help in management of natural resources, improved allocation of resources and planning, improved communication during crisis, cost savings by improved decision makings etc.

The effective use and implementation of Radio-frequency identification (RFID), GPS & data mining techniques in Public Distribution System (PDS) can facilitate PDS supply chain and promise eradicating mismanagement, corruption, trafficking, theft and anti-social elements. RFID provides highly accurate and detailed information by capturing the data and information at each stage of the supply chain, automatically. It also improves the safety and efficiency of the food supply chain. Location technology GPS can also be combined with RFID technology to automatically track and record the information regarding the field where the produce was picked, when and where it was transported and the current location of the produce. This also helps in reducing theft and trafficking. Data mining techniques based on the rule base classification model is used to identify the suspicious moving behavior of the objects. To read more: http://www.articlesbase.com/information-technology-articles/control-of-public-distribution-system-using-gps-gis-remote-sensing-with-data-mining-rfid-3393327.html