Today, the Einblick team is thrilled to introduce the newest version of our Python canvas, fully integrating the intuitive UI of canvas tools like Figma and Miro with the power and flexibility of traditional Python notebooks. At Einblick, we’ve always designed our product putting data scientists’ experiences first. In pursuit of our mission, we’re recommitting our efforts to the canvas as a necessity of the modern data science workflow.
Our multidimensional workspace frees data scientists to build the way they think in a frictionless and infinite canvas. In addition, the familiar look and feel of popular canvas tools improves accessibility for all the nontechnical stakeholders, who need to understand the data science pipeline at a glance.
Currently Python notebooks are a staple in the data science toolkit, but linear, one-dimensional notebooks are too restrictive given the speed and agility required in today’s rapidly changing and growing field of data science.
Read on to learn more about how we designed the Python canvas.
Data science problems are multidimensional–your notebook should be too
When faced with a new business problem, data scientists are keenly aware of the multistep, iterative process that lies ahead. You need to identify the business problem and context, collect and clean data, run exploratory data analysis, build and improve models, and finally present findings and solutions to stakeholders. This entire process is complex and requires juggling different crafts:
- Statistics
- Programming
- Business
- Design
- Communication
- Collaboration
The power of Einblick’s Python canvas lies in the ability to branch off into every facet of the iterative process, all in the same workspace. A multidimensional workspace allows interdisciplinary thought and the creative act of building data science pipelines to truly flourish.
Never feel lost reopening an old notebook again. Your work is now all in one spot, created and organized the way you think.
Focused data science workspace–the most critical tools all in one place
Currently, Python notebooks cannot handle every part of the data science pipeline. Not only do data scientists need to code in Python, but they also need to use SQL, Databricks, Snowflake, AWS–the list goes on! There is a lot demanded of data scientists, and the time spent context switching between tools and programming languages is taxing and wasteful.
By using a superpowered, comprehensive workspace built for the entire data science process, you are no longer constrained to only Python and markdown cells. In Einblick’s Python canvas:
- You’re free to code in Python for data cleaning and analysis, and code in SQL for data ingestion and joining.
- You’re free to compare different iterations of charts, tables, and summary statistics side-by-side.
- You’re free to explore and chase down different thought processes, organized by colored data zones and bookmarks.
Now, the only limitation is your creativity. Fork the canvas below to see what Einblick can do for you:
Easy to use for the whole team–web-based canvas with an intuitive UI
When starting a new project, you shouldn’t be spending hours setting up your environment, and then later down the line, troubleshooting your co-worker’s environment, which for some reason, can’t run your code, or needing to hop on an hourlong call to explain what you did.
In Einblick, you get:
- A fully hosted, web-based Python notebook, no installation or setup required.
- Sleek toolbar, side panels, and hotkeys give you quick access to your favorite tools whenever you need them.
- A shared runtime environment in every Python canvas, so your team is part of the same ecosystem, every time.
There’s enough to manage as a data scientist, your environment shouldn’t be one of them.
What’s new in Einblick
You can read more about all our product updates and feature releases on our changelog. Hear more about our UI updates from Einblick CXO and co-founder, Phil:
About
Einblick is an agile data science platform that provides data scientists with a collaborative workflow to swiftly explore data, build predictive models, and deploy data apps. Founded in 2020, Einblick was developed based on six years of research at MIT and Brown University. Einblick customers include Cisco, DARPA, Fuji, NetApp and USDA. Einblick is funded by Amplify Partners, Flybridge, Samsung Next, Dell Technologies Capital, and Intel Capital. For more information, please visit www.einblick.ai and follow us on LinkedIn and Twitter.