This episode is brought to you by:

Tegus. Tegus, the modern research platform for leading investors. I’m a long-time user and advocate of Tegus, a company that I’ve been so consistently impressed with that last fall my firm, Positive Sum, invested $20M to support Tegus’ mission to expand its product ecosystem. Whether it’s quantitative analysis, company disclosures, management presentations, earnings calls - Tegus has tools for every step of your investment research. They even have over 4000 fully driveable financial models. Tegus’ maniacal focus on quality, as well as its depth, breadth and recency of content makes it the one-stop, end-to-end research platform for investors. Move faster, gather deep research to build conviction and surface high-quality, alpha-driving insights to find your differentiated edge with Tegus. As a listener, you can take the Tegus platform for a free test drive by visiting tegus.co/patrick.

Show Notes

[00:03:16] - [First question] - His 2x2 matrix for categorizing different types of data businesses

[00:04:59] - An example of what he calls a religion company in his matrix

[00:07:03] - His notion of data currency

[00:08:23] - His definition of a great business

[00:09:46] - An example of a so-called application religion company in his proverbial matrix

[00:11:24] - Co-op and non-profit business models within and outside of the data sphere

[00:13:35] - The truth application quadrant of his matrix

[00:15:00] - The more pure-data-oriented truth category of the matrix

[00:16:18] - How data has exploded in prevalence for the business world as a whole

[00:18:57] - How to think about the end market for data and its demand

[00:21:09] - Characteristics of a good data set and how to identify it

[00:23:14] - Other factors that impact the usability of a data set

[00:24:30] - Optimizing data collection itself

[00:26:30] - The slow growth that’s typical of early-stage data companies

[00:27:27] - Market share considerations for data businesses

[00:28:47] - Brand-building for data companies and how it can supercharge market share

[00:30:03] - Common struggles for data entrepreneurs

[00:31:55] - How he found a big problem that he could feasibly solve with data

[00:34:01] - The genesis of his business; SafeGraph

[00:35:15] - Progress in privacy protocols for gathering and mobilizing people’s data

[00:37:08] - The power of self-maintained and user-maintained databases

[00:38:34] - The kinds of data that SafeGraph gathers and how he foresees it expanding

[00:40:16] - Typical customers and use cases for SafeGraph’s data

[00:41:08] - How SafeGraph and other companies protect against data theft

[00:42:12] - Frequency of change as a proxy for the value of a given data set

[00:43:27] - How to optimize the systems of a business to continually gather and maintain accurate databases

[00:45:32] - Categorizing inbound data based on the most important criteria

[00:47:07] - The founder personalities he finds in the data industry

[00:48:36] - The most noteworthy or quintessential data businesses in his opinion

[00:49:53] - Why he feels the data truth quadrant of his matrix is underdeveloped

[00:50:30] - Bloomberg as an important data company to study

[00:51:42] - The importance of transparency in business and in data distribution

[00:53:07] - Failure modes that he sees most commonly in data-based startups

[00:53:53] - Data businesses becoming application businesses and vice-versa

[00:55:29] - Innovations in the join keys and mechanisms that enable data to travel

[00:57:35] - The great dinner parties he’s known for

[00:59:50] - How he makes the dinner parties appeal to introverts

[01:03:11] - Dead people he would most like to have as dinner guests

[01:04:09] - Questions he would ask the most influential religious figures

[01:04:58] - Why he thinks people are generally good and want to be inspired and passionate

[01:06:20] - The kindest thing anyone has ever done for him