kpitree.io
Count.co
KPI Fire
Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
kpitree.io is a self-service platform for building KPI Trees from your own data.
It helps you organize your metrics into a clear structure so you can understand how performance is built and where changes come from. Instead of looking at metrics in separate dashboards, you connect them into one model where each number has context.
You can start from an outcome like revenue, retention, or activation, and break it down into the drivers behind it. Each relationship is defined by your own logic, so the structure reflects how your business actually works.
With kpitree.io, you can: โข Connect metrics into one structured view โข See how performance flows from drivers to outcomes โข Identify where changes start and how they propagate โข Define your own KPIs and formulas โข Work directly with your own data โข Build and update everything without code
The structure stays in place, so when a metric changes, you can follow the logic instead of rebuilding the analysis.
This makes it easier to: โข Explain performance clearly and consistently โข Align teams around the same metrics โข Focus on the drivers that impact results โข Move faster from analysis to decisions
kpitree.io is designed for teams that want a simple and reliable way to understand performance using the data they already have, without long onboarding processes or external support.
kpitree.io PlotlyPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
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Based on our record, Plotly seems to be more popular. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 5 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
Count.co - Start driving better decision making in your team with one simple document. Get started for free.
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
KPI Fire - Align Strategy, Drive Execution, Engage People
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
