Data fuels the hyperconnected world of today with every search, click, scroll, swipe and “like” tracked to seamlessly meet users’ every whim and need.

From food delivery to memes, people parlay these conveniences with more and more personal information to the point that data can predict their next move even before they make it.

These small actions ultimately become data, multiplied and magnified throughout their daily lives that is eventually developed into big data that can be harnessed to predict anything from heart attacks to the next viral meme.

To put it simply, big data is the processing of large amounts of data, be it historic or real-time, and to which algorithms are applied to discover trends in user behaviour, predict future outcomes, or gain other insights, just to name just a few.

Whilst big data continues to proliferate almost every facet of people’s daily lives at an accelerated rate, it continues to receive resistance from the real estate sector.

Property data, analytics and solutions provider, MyProperty Data CEO Thor Joe Hock believes the issue often lies in viewing real estate from a finite perspective which ultimately results in a binary decision.

MyProperty Data manages a property data portal called PropertyAdvisor.

“Real estate is emotive, it is deeply entrenched in our fundamental need for shelter and to commune,” Thor says, adding that for many, home means security and comfort as well.

“It’s a huge long-term financial commitment. For this reason, this decision becomes a very emotional one.”

“Whilst we desire shelter, we also seek out community – be it in a private or public space. The areas that we congregate or commune in often attract the similar-minded,” Thor says.

He adds that as an area attracts more people, the supply of available space ultimately dwindles, giving rise to prices.

“But it is important to note that the emotive factors are what ultimately drives the fundamental economic principle of supply and demand.

Simply put, big data is about shedding light on the motivations behind a purchase rather than what was purchased. In more precise terms, big data helps in better prediction and analysis in real estate,” says Thor.

Using the data, Thor says, experts can spot trends and foretell when they may reoccur and what to expect in unexpected circumstances.

“For example, thanks to data from the Nipah virus outbreak back in 1998 and SARS in 2002, we could predict that the market would be back to normal in as early as a year.”

Prof Dr Ismail Omar, President of Land Professional Association of Malaysia (PERTAMA) concurs that having such data will help the Ministry of Housing and local government address the discrepancies between what they consider affordable versus what developers consider affordable.

“Affordability is not just about financial capability (plus accessibility to loan) to buy houses, but it depends on the ‘habitability’ of the houses. Here, an accurate, reliable and up-to-date database is important to be able to analyse and make decisions with,” Ismail says.

According to Ismail, the necessity of accurate, reliable and up-to-date data on real estate is required.

“The fact is that the nature of the imperfections of the real estate market itself need to be addressed by collecting data on ownership, investment, financial, sales and purchase, and others.

“After all, we do need big real estate data to be established,” he said.

He adds that the data inaccuracies may cause existing problems that cannot be resolved by the usual method

Beyond understanding the dynamic nature of buyer profiles, online portal, Smart Data Collective states that big data can also help developers plan their projects in terms of reducing negative sociological impact, and improving the health of their residents.

It can also help to cut costs during construction by assisting them to find better materials and becoming more energy-efficient, said the portal.

In terms of helping homebuyers, big data also offers a more transparent process, in which a prospective buyer/renter and their agent are well-informed, creating a more fluid, straightforward process.

In the debate on what is considered as “affordable housing” in Malaysia, big data offers a solution that can help those who are looking to buy their first home but just can’t afford it yet.

On the rental side, it can also help shed light on why some places are easier to rent despite going for a higher rate. Using big data, it may be possible to finally work out what is considered affordable yet still fulfils a person’s needs.

As technology advances and more data is collected, more big data companies that will substantially transform the real estate game even more will likely make its presence on the scene.

This article was written by Adlene Hanna of PropertyAdvisor.my, Malaysia’s most comprehensive source of property data, property analytics and insights.