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Faster data exploration in Jupyter through Lux

Domino Data Lab

Lux is a Jupyter library integrated with an interactive widget that automates the generation of data visualizations from inside a notebook. This allows data scientists to quickly browse through a series of visualizations to seek out correlations and interesting trends. Saving visualizations in Lux. df.exported. Conclusion.

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Move Beyond Excel, PowerPoint And Static Business Reporting with Powerful Interactive Dashboards

datapine

Visualizing the data and interacting on a single screen is no longer a luxury but a business necessity. They enable you to easily visualize your data, filter on-demand, and slice and dice your data to dig deeper. Maps are important data visualizations and at datapine, we love utilizing them in our dashboards.

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Know Your Data Ingredients

Juice Analytics

This is an often overlooked step on the rush to visualize data. In an effort to lay a strong foundation for your visualizations, here are three steps to understand and evaluate your data fields before you throw it into the Cuisinart that is your visualization tool. (1) These are the ways you slice and dice your metrics.

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6 Principles to Make your Data Story Stick

Juice Analytics

This is the (Juicebox) Way: We encourage and enable visually strong titles, big bold images, and fully-width color. This is the (Juicebox) Way: We make beautiful, intuitive visualizations — and provide training and resources to make the most of those capabilities. Don’t start with a wall of charts. C oncrete Make it tangible.

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In Times of Rapid Change, Business Process Modeling Becomes a Critical Tool

erwin

With the help of business process modeling (BPM) organizations can visualize processes and all the associated information identifying the areas ripe for innovation, improvement or reorganization. You then can understand where your data is, how you can find it, how you can monetize it, how you can report on it, and how you can visualize it.

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Super-charged pivot tables in Amazon QuickSight

AWS Big Data

Additionally, with Amazon QuickSight Q , end-users can simply ask questions in natural language to get machine learning (ML)-powered visual responses to their questions. This involved migrating complex tables and pivot tables, helping them slice and dice large datasets and deliver pixel-perfect views of their data to their stakeholders.

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Data Storytelling: What's Easy and What's Hard

Juice Analytics

Gathering a collection of visualizations and calling it a data story is easy (and inaccurate). Making it meaningful is so much harder. Making data-driven narrative that influences people.hard. Schedule a demo.