How To Make Sense of The Exploding Volumes of Data Available  with Brad Schneider

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Brad Schneider is the Founder and CEO of NoMad Data. He was previously the CEO of Adaptive Management. Throughout his career, Brad has focused on using alternative data to improve decision making and prediction. Brad has been a Portfolio Manager at Tiger Management, and Managing Director at Jericho Capital, a $2bn AUM TMT-focused hedge fund. Prior to Jericho, Brad also worked at Palo Alto Investors as an equity analyst and was a co-founder and head of product development for InfoLenz, a predictive analytics company. Brad holds a Bachelor of Science degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and is a CFA charterholder.

Episode Links:  

Brad Schneider’s LinkedIn: https://www.linkedin.com/in/bradschneider/

Brad Schneider’s Twitter: https://twitter.com/bschneider222?s=20

Brad Schneider’s Website: https://www.nomad-data.com/

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Outline: 

Here’s the timestamps for the episode:

(00:00) – Introduction

(01:16) –A tech guy who started in the analytics space and moved to the world of investment, which led him back to the field of data

(02:33) – Building software over the years helped him, as the user of data, to more easily interact with that data and find ways to connect the use case to the dataset.

(03:57) – NoMad Data’s goal is at a high level to be the search engine for these datasets, making it a lot easier for people in the AI space, for researchers, for computer science, for marketers, for strategy professionals, consultants, investors, help them connect those everyday business problems that they have to real datasets.

(05:33) – Data that is more frequently purchased include credit transaction data and customs data, which allows to see trade flows

(06:48) – Data sets are so powerful, but they’re also so broad.Customs data set help to understand a single company on the aspect of one company or region and economic competitive wins and losses for factories. And because they’re so broad it’s very hard to describe on a webpage what this dataset can be used for.

(08:07) – The build vs. buy dilemma: it really depends on your timeline and the availability of the data you need. Even if the data we collected was a hundred percent accurate, it would become very challenging, because we wouldn’t have enough data points to even make a simple linear regression model. So, in a lot of cases, it’s better to buy.

(10:25) – Getting that data from where it started, whoever is creating it or whoever you’re purchasing it from, and getting it somewhere that you can write that first query has historically been a bottleneck. Some services like Snowflake are creating these marketplaces where people are putting the data in a common database format.

(12:05) – It’s hard to fully automate the data search process today, and the main reason being the data you need, the metadata about the data, doesn’t really exist, and the term metadata is used very broadly. Cutting edge NLP and machine learning is used to find similar concepts.

(13:47) – The biggest change that the pandemic caused was really the need for data. Buyers are looking at more and more datasets to fill in the holes in their understanding. And because of the increasing number of those holes in their knowledge, there’s been an increasing need for data.

(15:49) – Searching the area that we’re focused on is one of the biggest problems holding back the market. People know they want to see something, they want to be able to calculate some statistics, but they don’t really know the data that would provide the requirement to do that.

(16:33) – Companies need to be really pinpointed on what they focus on, and because people have a really difficult time finding the right data, finding the best data to address their use case, services like Nomad help unlock this industry, which ultimately means you bring more and more buyers into the market.

(19:08) – Many of the companies today haven’t given much thought to data as they have for software. The data revolution has already started. And the first step in that was companies looking at their internal data. The next frontier is external data or alternative data. It’s these data sets that are coming from outside your four walls, and in a lot of different businesses, it gives you a perspective that you don’t have. It gives you a perspective that isn’t biased by your own internal processes

(21:00) – If you’re a company where your brand is extremely important, you’d be more reticent to sell data because there’s potential brand risk associated with doing that. We support anonymity on both sides of the market. In Nomad, they can post their data. It’s completely anonymous.

(22:40) – Nomad has raised $1.6 million and that was led by Bloomberg beta and some other higher profile VCs as well. Some great angels in the data space.

(23:51) – As we get out three to five years, awareness of this space and interest in this space is going to explode in orders of magnitude growth on both the number of people selling data and the number of people buying data.

(24:40) – If you’re a startup, NYC is a wonderful environment to be in. It’s also helping a lot, that housing is coming down.It’s attracting more and more people. People that don’t want to commute here don’t have to anymore. It’s going to be a Renaissance for the city.