Connect Mode to Your Data Sources

As an advanced, high-speed data analytics platform, Mode helps you understand the information in your data warehouses. As a hybrid solution Mode lets (1) data teams customize queries and visualizations in Python, SQL, or R; and (2) empowers non-tech-savvy users to dive into visualizations and explore live-updating reports to get the data they need.

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Mode Connector Overview

Mode White-Label Embeds and Visualizations

Mode's White-Label Embeds allow you to integrate customized, interactive visualizations, and analytics into your applications — so your customers can access powerful reporting that seamlessly blends with your apps. White-Label Embeds also secure your data by ensuring that specific customers see appropriate information only. Lastly, Mode includes pre-built charts and the ability customize your visualizations in JavaScript, HTML, and CCS.

Mode SQL Editor

Mode's SQL editor features a schema browser to explore the tables and columns of your connected data sources. It also has an autocomplete function to assist with query writing, a query history to browse and reuse old queries, and advanced logic tools for creating loops, IF statements, and more.

Mode Helix Data Engine

The technology behind Mode's analytics solution is Helix, a high-performance in-memory data engine that combines modern drag-and-drop business intelligence tools with a code-first (SQL, Python, R) data science platform to offer an instantly responsive user experience. Mode streams query results into the Helix data engine to reduce database load, provide quick responsiveness, and give users the ability to visually navigate as much as 10 gigabytes of data.

Mode Dashboard Features

Powered by SQL, Python, and R, Mode dashboards display automatically-refreshing metrics without the need for proprietary tools. Customize your dashboards the way you want, with on-brand reporting and interactive features to facilitate collaboration with others across your organization.

Mode Native Python and R Notebooks

Mode features native Python and R Notebooks. This allows you to query in SQL, send the results to a dataframe in R or pandas, and conveniently access them in the platform's native Notebook. At the same time, a sidebar provides tips, shortcuts, and documentation to help you get the most of these features.