A Deep Dive on Data

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[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