6 links tagged with all of: data-visualization + analytics
Click any tag below to further narrow down your results
Links
nao is a framework for creating and deploying analytics agents that can interact through a chat interface. It allows data teams to manage context, test performance, and ensure security while enabling business users to ask questions and visualize data in natural language.
Ada.im offers a tool for creating data dashboards and visualizations quickly, catering to users with varying levels of technical expertise. It features automatic visualization, a prediction tool based on historical data, and supports multiple export formats. Users appreciate its ease of use, though some report concerns with setup and data handling.
Perspective is a tool for creating interactive analytics and data visualizations, particularly for large datasets. It supports user-configurable reports and dashboards, operating in the browser or with Python and JupyterLab. The system uses a fast query engine and a flexible user interface to enable efficient data handling and visualization.
mviz is a Claude skill that simplifies the creation of static reports for ad hoc data analysis by converting compact JSON specifications into professional HTML visualizations. It emphasizes a fast, AI-driven workflow that allows users to iterate quickly, generate reports, and utilize a variety of chart types without extensive coding. The tool works seamlessly with data from various sources, including local files and cloud databases.
Plotly Studio is a new platform designed to enhance the way users create and share data visualizations. It integrates various tools to streamline the data analysis process, offering a user-friendly interface and collaborative features for teams. The platform aims to empower users by simplifying complex data interactions and fostering better insights through visual storytelling.
A guide on building and explaining cohort charts, detailing three common types: Range Retention Tables, Spider Charts, and Stacked Cohort Area Charts. It emphasizes the importance of cohorts, defined as groups of users with similar characteristics, and provides templates for recreating these visualizations to analyze user retention and activity metrics effectively.