Basecamp consolidates many project management systems into one centralized location that includes to-do lists, shared documents, schedules and discussions. In the Basecamp interface, users can see what tasks need to be accomplished, who they are assigned to and when they are due. They can also access public documents and discussion boards. This allows for more organized communication and more efficient and comprehensive teamwork.
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.
Popular Use Cases
Bring all your Basecamp data to Amazon Redshift
Load your Basecamp data to Google BigQuery
ETL all your Basecamp data to Snowflake
Move your Basecamp 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
Basecamp's End Points
Get data about a project, including its name, status, and the list of tools enabled for that project (schedules, to-do’s, and message boards, for example). You can also use this endpoint to modify existing projects that need additional functionality or to trash projects that are no longer being worked on.
Retrieve information about a to-do task, such as its name, status, creator and assignee. Then, look at important information about your tasks such as what tasks a person has assigned to them, what tasks are still active and how long those tasks have been active. This can help you measure project performance and other key metrics.
Track any time a change occurs in Basecamp i.e. if there is a new comment, an assigned to-do, a new document, or any number of other events. This data can help you highlight trends, run analytics, and support any other data sources that rely on event reporting.
Get information about any comment made in Basecamp, including the name of the commenter, the date the comment was made, the content of the comment, and what project the comment was on. This data can help you both monitor user engagement and gauge which projects are being talked about the most.
Mode's End Points
Mode White-Label Embeds and Visualizations
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.