Data sharing is the difference between action and indecision.
Whether giving feedback as part of a team-wide code review or passing along key results to a business stakeholder, insights are only valuable if they’re shared with the right people. The trick is how to do so quickly and securely.
Let’s look at how teams use modern data notebooks to improve data sharing and accelerate insight delivery.
You spend hours of painstaking work querying your database, writing code, visualizing results, and documenting your thought processes. Then, when it comes time to share your findings, you trade cutting-edge technology for a carrier pigeon.
That’s an exaggeration, but only slightly. Downloading and sharing
.ipynb files each time you want to pass along your work to a teammate is a headache, but it’s not even the worst way to share a Jupyter notebook.
If you’re trying to collaborate with someone who can’t fire up the file on their machine (i.e., your average business stakeholder), odds are you'll resort to the standard screenshot strategy. Not exactly a state-of-the-art (or secure) way to distribute insights.
But here’s the beauty of cloud-based notebooks: Sharing your work is as simple as sending a link. Once your teammate opens your email or Slack message, they can jump into your notebook with a click and enjoy the exact access level you assigned them. And this isn’t a static notebook or a carbon copy that lives in an isolated environment — it’s the real deal: completely reproduced and connected to the same data sources, in the same environment (commence actual data collaboration!).
Of course, sharing shouldn’t be an all-or-nothing proposition. Say you don’t want to share your entire notebook, just a specific SQL, code, or chart block. You can easily share or embed the code and output of individual blocks (which are then automatically refreshed each time you make a change in your notebook). Embed them in websites or popular workplace applications, such as Notion, or simply pass along the URL so teammates can open it up in the web browser of their choice.
Ease of shareability is one reason companies such as VantAI use notebooks for data sharing — it helps them spend less time translating analysis via other channels and more time getting to work.
“More and more, the VantAI team is able to move discussions around abstract ideas and complex data out of presentation tools (e.g., PowerPoint) and into direct implementations in code,” said VantAI’s CEO Zachary Carpenter.
Plus, avoiding copying and pasting screenshots that contain sensitive data will do wonders for your chief of security’s blood pressure. Just ask the team at Gusto, which now uses a cloud-based data notebook to easily share analyses.
“We’re no longer copying and pasting screenshots from external sources,” said Gusto’s Head of People Analytics & Insights Scott Jacobsen.
Not everyone needs to see your code. And more importantly, not everyone will understand it (we’re looking at you, CMO who just wants to know why certain customer segments are at a higher risk of churn).
But transforming a notebook full of exploratory analysis into a human-readable format can be time-consuming. That goes double if you need to put together a fancy presentation or build a dashboard.
With modern data notebooks, you can turn your notebook into a beautiful, interactive, and easy-to-read article (complete with table of contents!), application, or dashboard with the click of a button. Just drag and drop your blocks where you like and hit publish. As with the notebook itself, you have total control of the access rights to the published project (i.e., who can open it, view it, rerun it, or modify inputs).
Whenever a teammate interacts with one of your inputs (e.g., a dropdown menu, a text input, etc.) and applies their changes, the whole notebook is run with the new input values. Want to make sure the data in your dashboard is always fresh? Republish it automatically after a scheduled run on an hourly, daily, or weekly basis.
The ability to quickly convert complicated coding environments into business-friendly formats is one reason companies turn to modern data notebooks. Said Gusto’s Scott Jacobsen:
“Because we partner with many people across the company — we might have 200 people viewing our analysis — the ability to publish notebooks into an article using Deepnote has been a game changer. Now all of our important stakeholders can work and interact with the article.”
The interactivity of these published projects helps organizations empower different stakeholders to self-serve where possible. That’s why companies such as Webflow depend on modern data notebooks for data sharing.
“We use this a lot for experimentation,” said Webflow’s Senior Manager of Data Science & Analytics Allie Russell. “Data flows in and gets modeled for experimentation, then we make it interactive and available for product managers and data scientists to use.”
Build a knowledge base
Traditional notebooks stay buried on your machine (likely surrounded by an elephant graveyard’s worth of half-finished or abandoned projects). This creates bottlenecks (or, at the very least, a barrage of Slack messages asking you for access).
Cloud-based data notebooks increase the discoverability of projects by centralizing them into an organized, searchable database. Creating a top-level organizational layer for all projects and resources makes it easy for data teams and business stakeholders alike to put analyses to work.
Notebooks and all associated data connections, scripts, etc. can be arranged and nested in whichever way suits your team’s workflows. Teammates can manually browse the workspace or use search functionality to query what’s available, along with helpful project-level metadata such as location, machine status, author, and more.
Instead of forcing teammates to hunt for static notebooks in GitHub, your colleagues can dive right into projects with the same connections to warehouses, databases, buckets, and other services (as long as they’ve been granted the proper permissions). Goodbye environment configuration, hello innovation.
Just ask VantAI CTO Luca Naef.
“You have direct access to the runtime and program state, which makes understanding complex models much easier and leads to much more spontaneous creative ideas,” Naef said.
Increasing the visibility of projects, as well as simplifying access to them, helps teams build on each other’s work. That’s why one Deepnote customer — a hedge fund with a large data team — uses modern notebooks.
"Notebooks are often used as a quick prototyping tool, but we don't want to create one-off work,” the customer said. “We want to invest in ideas that compound over time. Deepnote gives our team one place to create, store ideas, and build on top of the work of others. Visibility goes up over time."
Sharing data doesn’t just need to be easy — it needs to be secure. That’s the problem with passing along files and screenshots: You don’t get to decide what level of access people have, and before you know it, credentials and other secrets are floating around in the wild.
But that’s not the case with modern data notebooks. Whether you’re sharing a link to a notebook or inviting someone to explore a shared workspace, granular role-based access controls make it easy to safeguard data.
Workspace members can be assigned as viewers, contributors, editors, and administrators, with each level featuring different access controls (e.g., commenting on notebooks, executing notebooks, connecting or disconnecting data sources). Even team members who aren’t official members of a workspace can be invited as guests.
Meanwhile, published projects, such as dashboards and apps, can be made viewable by everyone or accessible only by people with the link or who have access to the original project.
And with a built-in audit log, you can track every user’s actions within a workspace, along with the metadata associated with them. New versions of notebooks are saved automatically, making it easy to preview and restore older versions, as well as keep tabs on all actions taken by collaborators and any significant system events.
These safeguards help companies find the sweet spot for sharing data across teams while ensuring security and privacy standards are satisfied.
"Deepnote allowed us to gradually experiment with collaboration at little cost, and slowly scale our collaborative workflows,” our hedge fund customer said. “Ultimately, it has made a huge difference for collaboration in our team — it's night and day. There's before Deepnote and after Deepnote time."
There’s a thin line between innovation and stagnation. Which side a company is on depends on how quickly, easily, and securely data teams can share insights with others.
That’s why leading data teams use data notebooks to do it right.
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