Design From Iceland

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In a recent interview, Brandon Taubman described data science as “the business discipline of harnessing data to make better decisions.” He then clarifies that “data science is the technology and analytics that tell you things that you didn’t know.” Taubman references the role that data science can play in strategic decision making, explaining that the “pulse of the market” is essential information that can alert a company of what’s happening to competitors, but not everyone has access to it. According to Taubman, Stablewood is a data-driven real estate firm, but it’s still early days for the business.

Data science benefits in business

Brandon Taubman: The first advantage of data science is the ability to create new products and services that otherwise couldn’t exist. Imagine if we had a predictive tool like Google for every city globally, as we can today with the Google Maps API. How often do we think of something new but can’t make it because it would take infinite resources to create it? That’s what I mean by new products and services. Data science creates this wealth of ideas that otherwise didn’t exist, and that’s what we strive to achieve with our portfolio companies. I believe there are many data scientists today in every industry, but very few companies know how to use them effectively.

Data science role in commercial real estate?

Roughly 40% of the investment decisions are based on strong data analytics alone. But the data science landscape is so vast that it’s challenging to say for sure how much is usefully applied by real estate buyers, sellers, investors, and lenders. Brandon Taubman: People in our industry often assume that we need to have a big data platform to solve our problems, and that’s not true. If you look at construction, you can’t build a building without much information about the project. So we need to develop an analytical platform with the right level of machine learning, AI, and data analytics that is robust.

Biggest challenges facing businesses using data science

The biggest challenge facing businesses adopting data science is trusting the information they receive. Many people have preconceived ideas about the merits of different types of data-based analytics, like Google’s PageRank, which people mistakenly think is an algorithm. Even with the significant advances in technology that have enabled the analysis of vast amounts of data, people still don’t have a good grasp of what their data analysis means. What is fascinating about data science, and perhaps one of the biggest challenges is often used to name something that people know very little about. People use data science’ and ‘data analysis’ as synonyms. But it’s very different from one to the next.

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