Data Gurus

FROM THE PODCASTS

Data Quality, Part 1 of 4 with Matt Staudt, CEO of Venture Development Center | Ep. 84

In this special series on data quality, you’ll hear different perspectives from other industries regarding market research and the analytics industry.

Sima chats with Charlie Allieri, CEO of Imperium, and the sponsor of this series on data quality, and Matt Staudt, CEO of Venture Development Center.

Bringing Traditional and Alternative Assets to the Marketplace

Venture Development Center, started in 1996, is an organization that works in the big data market space, primarily with traditional data and alternative data. 

They have assembled 190 relationships with organizations that have the traditional and alternative assets and Venture DC looks to bring these assets to the marketplace that they’ve created where buyers of data can be traditional players themselves. 

They can be brands or professional service organizations, and Venture DC assists with helping them to understand these assets and how they might be used in particular use cases, thereby creating licensing events and making these matches.

Traditional and Alternative Data as Transformational

From the perspective of Venture DC, traditional data is the kind that has been around for 30 years. In other words, demographic dataset, which typically consists of a mailing address, business name, business sector, contact name, and email address.

Matt defines alternative data as the behavioral activities, such as signal data, geolocation, search, transactional, and crowdsource. 

The amount of data Venture DC represents in the marketplace is tremendous. They have access to transactional data files that cover the spectrum of all types of activities, and are terabytes in size.

The traditional models can be incredibly enhanced by looking at the alternative behavioral activities. 

Looking at models isn’t a question of accuracy but the timeliness of it. The behavioral and signal aspects is immediate and when you have access to it you can react quickly. There are privacy compliance concerns when you start using it but using it properly can be transformative.

Representative Criteria and Measuring Quality

In order for Venture DC to represent an organization, there are 3 factors at play: (1) Compliance. The organization needs to be in a position where the data they’re getting is being collected in a compliant fashion. (2) Historical data. Is it represented there? People may have great data that they’re collecting but if they don’t have some sort of history associated with it, then it’s hard to test. (3) The future. Are they going to be able to collect this data for the foreseeable future? They don’t want to represent any file where a potential buying entity within their portfolio utilizes the data and then all of a sudden, it’s no longer available. 

One of the biggest challenges is pricing, which depends on unique data points of value and what kind of use-cases it can be used in. How unique is it? Are there data points of value within the dataset that are compelling, and if they are, how unique are they? How do they measure up against other things that are represented in the marketplace? 

The Impact of Privacy Issues

Matt discusses how many companies have ignored privacy issues, the ensuing lawsuits, CCPA, and more.

Sima suggests that there’s a positive side to this, however, in that it makes everybody rise and clears the bad actors out of the system.

There needs to be a country-wide level of legislation because complying with all the nuances that exist state to state poses a challenge.

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Sima is passionate about data and loves to share, learn and help others that share that passion. If you love data as much as her, subscribe on iTunes and don’t forget to leave a rating and review!

This 4 part series is sponsored by Imperium. We are grateful for their support to bring you this important series.
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