In today’s era, we create the same amount of data every two days as we did from the dawn of civilization until 2003. On an annual basis, we create 16.3 zettabytes of data. There’s a tidal wave of data coming at us and there’s no escaping it.
But the best business leaders of the future won’t want to escape it, they’ll want to run head-on towards it, and they’ll know how to embrace it with arms wide open. In order to do so, they’ll need to tame and organize their data such that it’s easily consumable by their future customers.
I’ve noticed some trends that indicate they’re already starting.
The first major trend I’m seeing is that companies are now selling data to financial institutions on a subscription basis, which I’m referring to as “data-as-a-service.” In this model, companies gather, aggregate, and disseminate their data to others for a recurring charge.
Currently, the early adopters for this data appear to be hedge funds and other financial companies that are looking for alternative data to provide them with alpha. In the future, though, I can see this data being used for market research, competitive analysis, inventory planning, and even hiring, in addition to its obvious use as alternative data for investors.
There are a variety of companies that can benefit from this growing trend. Interestingly enough, the unlikely winners for this upcoming market will likely be companies that produce data exhaust, or data that arises as a side effect of a business’ core activities. Their data garbage could become another company’s data treasure, especially if their data is orthogonal to all other publicly available datasets and it can address business needs.
But this growing market can provide an opportunity to companies that are willing to aggregate and organize data that already exists, as long as their efforts transform that data in a way that makes it easier to consume. There’s a lot of public data out there that’s currently very hard to parse and aggregate, and there’s definitely value in transforming this data in a way that others can integrate easily, and this includes in ways that are easily consumable by machines and algorithms.
The market for data is undoubtedly growing, but because of that, I believe that companies that can provide value-added services on top of their raw data will position themselves ahead of their competitors.
Currently, the marketplace for data is nascent, but I’m seeing it grow rapidly. Raw data, as valuable as it is, can also prove to be useless for companies that don’t know how to use it. It can also provide a hurdle for organizations that don’t have the ability to properly parse and process that data.
One prime example of this is satellite imagery. There has been a recent explosion in the number of companies that process satellite images, but raw satellite images themselves are extremely hard to work with. Even aggregating the number of cars in a parking lot, for example, isn’t very useful. What is useful, though, is providing a time-series of the number of cars across all retail locations for a given publicly traded company over the past five years. Even better would be investment signals or an investment-grade score that indicates what the change in time of the number of cars in a parking lot means for the stock price of publicly traded companies.
Data that’s in a form that’s easy to integrate, validate, and verify will likely prove to be more valuable to customers than raw, unaggregated data. Companies that can figure out how to use their data to answer their customers’ questions directly, rather than having their customers use their data to answer these same questions, will likely prove to be the market leaders in this newly emerging data marketplace.
There’s no doubt in my mind that these aren’t the only major changes coming to the world of data. As the amount of data grows, and AI/ML techniques improve, we’re going to open up a myriad of new applications and capabilities, and those will open up a world of business opportunities for anyone willing to grab them.
The world of finance will likely be among the early adopters of many of these new services, but there will be a variety of other industries that will benefit from these changes.
Shanif Dhanani is the co-founder & CEO of Apteo. Prior to Apteo, Shanif was a data scientist and software engineer at Twitter, and prior to that he was the lead engineer and head of analytics at TapCommerce, a NYC-based ad tech startup acquired by Twitter. He has a passion for all things data and analytics, loves adventure traveling, and generally loves living in New York City.