Use the Slack integration to get vital information about your organization, your team, and their habits or productivity.
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.
Bring all your Slack data to Amazon Redshift
Load your Slack data to Google BigQuery
ETL all your Slack data to Snowflake
Move your Slack data to MySQL
Bring all your Mode data to Amazon Redshift
Load your Mode data to Google BigQuery
ETL all your Mode data to Snowflake
Move your Mode data to MySQL
Gather and set information on members of your Slack team: get a user’s identity, find a user with email addresses, set user profile pictures, and more.
Get info on your team's Slack channels, create or archive channels, invite users, set the topic and purpose, or mark a channel as read. Use this information to track and improve company communication.
Interface with all kinds of conversations, including public conversations, private channels, and direct messages.
Get info on files uploaded, upload new files, and control things like file sharing, filters, and file information.
Get info on your team's private channels, or groups, and on your team's user groups.
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.
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.
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 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.