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Is your current BI tool holding you (and your data) back?

If you’re currently managing and analyzing your data in a BI tool, it’s time to ask yourself: how happy are you? It’s okay, you can be honest. We promise we won’t tell. Truthfully, most people utilize tools like Excel because it’s comfortable. They know how to use it, how to navigate it, and feel confident with how it works. But, it may be time to break out of your comfort zone by switching to a programmatic approach like Python.

Why switch to a programmatic approach?
We’re not one for clichés, but in this situation, the grass really is greener on the other side. Let us explain three reasons where Excel can limit your data analysis and management:

  1. For those who work with large sets of data, it can be hard to manage when you’re confined to row and column data and lookups. It can also take a long time to open and load your data, and in a day-and-age where data collection is more popular and datasets are increasingly getting larger, programmatic data management can improve your data organization by facilitating easier connections to databases and allowing simple imports into data frames.
  2. Even if Excel is getting the job done for you, you’re very limited to the visualizations you can build around your data. Sure, you’re able to get your point across, but your data is much more impactful when its visualized in a way that is meaningful, tells a story, and is on-brand.
  3. Collaborating and sharing at scale can be frustrating in Excel. Users typically turn to tools like DropBox or email to share files, which can be very limiting. With a programmatic approach, you can easily edit, collaborate, and share your data effortlessly.

The switch to Python
Due to its powerful infrastructure and flexibility, Python is rapidly increasing in popularity for analyzing and managing data. So, what makes this programming language so great? For starters, it’s as simple to learn as it is to use. The language’s syntax is clear and easy to understand and its large fanbase means support is readily available, making it ideal for beginners. Additionally, Python’s extensive integration abilities can significantly increase productivity.

The benefits of Dash
Built as a Python framework, Plotly’s Dash will give you all the benefits of a programmatic approach, and then some. Even if you’re working with manageable data, you’re still limited to your current tool’s style and chart offerings. With a programmatic approach, especially one with Plotly’s Dash, you’ll have easier access to a number of data viz options, allowing you to build, test, and deploy beautiful interactive apps. Yep — you read that right — Dash apps are completely interactive. Because Dash is built on top of plotly.js, the charts are inherently interactive. Dash then gives you the ability to add additional interactive features such as drop-downs, sliders, and buttons, all built around your data code.

Interested in learning more? Check out Dash at ODSC East
Don’t take our word for it — come see Dash in action. Our Head of Project Management, Chelsea Douglas, will be presenting a demo of Dash at the Open Data Science Conference (ODSC) East in Boston on Friday, May 3. Click here to learn more.

But wait, there’s more. We’ll be hosting the 10:30am coffee breaks at ODSC East. So you can grab a coffee and some snacks and schedule some time to talk with us. Register now!

Also — be sure to stay tuned for our upcoming Excel to Python blog series, where we’ll be discussing this in more detail and sharing best practices for moving over to a programmatic approach.



Plotly is a data visualization company that makes it easy to build, test, and deploy beautiful interactive web apps, charts and graphs—in any programming language.

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The low-code framework for rapidly building interactive, scalable data apps in Python.