The NY Enterprise Tech meetup was one of my favorite events to attend in-person prior to the pandemic. While the meetup is now all virtual, the speakers they bring in continue to be top-notch--particularly in the data space. The host of the meetup is Work-Bench, a VC focused on enterprise software companies. Priyanka Somrah is a VC analyst at Work-Bench who speaks with the most innovative startups building data tools on a weekly basis. In this episode, Priyanka talks about how data tools can effectively sell into the enterprise, how the data engineering profession has grown in the last few years, and the most effective Go-to-Market (GTM) strategies for data companies.

Note: There were some recording issues with this episode so apologies in advance for some of the gaps in the conversation as well as the background noise.

Flipping VC on its head

Work-bench is early-stage enterprise VC firm that flips the VC model upside down. Unlike most VCs that go off and try to source the most innovative companies, Work-Bench hosts quarterly corporate roundtables with Fortune 500 companies. From speaking with the end customer of these data infrastructure and engineering tools, Work-Bench finds the pain points these large enterprises face. From there, they go and find the companies that offer a solution to these problems.

This aligns with what I hear a lot in the B2B SaaS space in terms of creating an effective marketing strategy. Paint point selling or solution selling are some buzzwords you might hear in this regard. Instead of selling the features of your product, you focus on the problems your product solves for your target customer. Seems like a reasonable strategy marketing and sales people should adopt, but all the cold spam InMails and connections on LinkedIn might convince you otherwise.

How to become enterprise-ready

One of the main challenges for data infrastructure tools is selling into the enterprise. A company's data is one of the most important assets the company has, and Priyanka provides some best practices on how data tools can better prepare themselves to be a legitimate enterprise solution:

* Security - Being able to safeguard the customer's data is priority number one. This means getting SOC 2 certification or offering a single sign-on feature.* Scale - Can the tool reduce the administrative overhead and grow and scale as the customer's requirements grow and scale* Flexibility - This is becoming a table stakes feature. Is the tool modular enough to integrate with a customer's existing tool stack?

Source: Work-Bench SOC 2 Playbook

Assuming the data tool meets these enterprise standards, Work-Bench then acts as the matchmaker between the various Fortune 500 companies they are connected with and the startup that provides a relevant solution.

Big data and the rise of data engineering

Big data has really changed the face of the world. As a result, the ETL process and data modeling have changed considerably as well. With tools and processes changing, the skills and expertise required by data professionals needs to adapt. We saw with the last episode about