Growing companies require leveraging data science to identify a real need and find a way to solve it. For companies, the data science team collects information and builds models on top of the data to identify the unknown problems a business may face.
For example, in the real estate world, it means understanding how an apartment or townhouse will perform over time and how people are spending their time in the space. You would be surprised at how poorly most data companies analyze this data.
Brandon Taubman: This means understanding investment opportunities in emerging technologies and small and early-stage startups in the investment business. We are talking about something I have been intimately involved with.
Some of the most popular is called “Big Data” and are often utilized to monitor your customer base, predict pricing trends, or implement machine learning algorithms. But, if you’re in the business of analyzing economic data, “Big Data” isn’t an option – it’s your only option.
It can be challenging and expensive to store and prepare your data for analysis, so most companies choose to offload the task of data manipulation to “Big Data” analytics companies that manage enormous piles of raw data. These companies are then responsible for analyzing the data and making it useful. They are called “Big Data Analytics” companies.
Research-Based Finance: To build the team, Brandon researches data scientists in the industry and chooses the best ones. He doesn’t limit himself to the top ten data scientists in the industry. Instead, he focuses on the people most likely to get the job done. Brandon Taubman focuses on culture fit and looks for smarter and more passionate applicants than the rest.
Data-Driven Real Estate: With Stablewood, Brandon focuses on bringing real estate to a higher level using analytics. He creates complex models that help clients uncover profitable investments. These models allow for predictive analytics of real estate. Brandon said that “over 90% of all property transactions will happen because of their results.
“Data Science is a broad term for scientific method in practice,” says Brandon Taubman, “Using technology to seek patterns in large data sets, we can create useful and practical insights to businesses, industries, and people.”