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How Webflow enhanced exploratory analysis & data collaboration with Deepnote

Using Deepnote, our team can conduct analyses in the language most comfortable for them, which makes it accessible to and powerful for everyone.

Photograph of Allie Russel's face

Allie Russel

Senior Manager of Data Science & Analytics

Challenge

Webflow wanted to harness the power of its data to drive more value for the company and its customers.

After implementing Snowflake as its data warehouse, the company needed a way to help its data team easily explore data and collaborate on projects, as well as provide greater visibility to company leaders and cross-functional partners.

I was personally skeptical about the 
performance of a collaborative, hosted platform, but when I used Deepnote to collaborate with a colleague and we were able to remotely troubleshoot and try different plots, I immediately saw its value.

Photograph of Allie Russel's face

Allie Russel

Senior Manager of Data Science & Analytics

Solution

With Deepnote — and its native integration with Snowflake as a Snowflake Select Technology Partner — Webflow can quickly explore, collaborate on, and share data across the entire company.

Deepnote lowers the barrier to entry to prototype. There’s nothing that filled the space in our stack that allowed us to do an analysis and share it in a repeatable way until we adopted it.

Photograph of Allie Russel's face

Allie Russel

Senior Manager of Data Science & Analytics

Strategy

Webflow’s data team uses Deepnote to code together in real time, as well as organize different projects, notebooks, and apps in dedicated workspaces. Team members are able to use whichever programming language they’re most comfortable with, including Python, SQL, R, Julia, and more.

Deepnote’s collaborative, time-saving features — including commenting, autocomplete, and scheduling — allow the team to quickly run statistics to help inform decision-making, prototype experiments for various business stakeholders, and share important metrics with domain experts, who can then easily manipulate the data to suit their needs.

With the ability to share projects with a link — and include context in the form of code, charts, text, and more — Webflow brings stakeholders from across the company into the exploratory data analysis phase to help them gain a deeper understanding of the company’s data and speed up necessary buy-in.

Deepnote enables us to bring people into the phase of data science that’s all about experimentation, helps them understand our processes, and encourages folks to leverage data science in even more ways.

Outcome

Webflow can now make the most of its data warehouse by enabling teams to easily work together and share their findings with each other. This helps the company’s data professionals experiment and troubleshoot, as well as quickly find and view each other's work. Increased collaboration and visibility among both data experts and business stakeholders help to de-risk ideas, support critical investment in projects, and reduce time to market.

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