Twilio offers scalable, cloud-based communications for web and mobile apps. This includes the ability for companies to call, SMS, chat, or video conference without having to create a communications infrastructure on their own. Further, Twilio can track tasks, evaluate worker performance and availability, and gather event data that can be used to create historical analytics reports.
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 Twilio data to Amazon Redshift
Load your Twilio data to Google BigQuery
ETL all your Twilio data to Snowflake
Move your Twilio 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
Retrieve data about Twilio tasks that are part of your team’s workflow and filter those tasks using an array of fields including priority, assignment status and name. This data can be gathered from within Twilio or integrated from external sources and added to Twilio’s workflow.
Track each workspace event that occurs, including things like the creation of a new Twilio task, a worker being assigned to a task or a change in a worker’s activity status. You can use this data to both generate current analytics and store historical record data for future use.
Get data about your workers, including their activity, availability and relevant skills. This will help you both assign your workers the tasks that are most suited to their skill sets and ensure that those tasks are only assigned when workers are ready to tackle them.
Monitor a worker’s Twilio activity status and use it to determine whether or not to assign an open task to a specific worker.
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.