Redash is a collaboration tool for SQL based data analysis. It's an open source project built with Python on top of the Flask web framework, PostgreSQL and ReactJS.

Redash features a simple interface that allows you to create new queries, visualize the data and share dashboards. It integrates with the most popular databases out there, including MySQL, PostgreSQL and Redshift (and more). It's often used for business intelligence, since it's designed to be user friendly and accessible to anyone who is working with data within an organization.

Redash Meaning

Redash was inspired by the lack of existing solution that will allow business users to work with SQL (or similar query language) without knowing it. It's a product of a team that spent too much time generating reports and answering questions to people outside of the data organization with answers like: "it depends on the time of day", "how many times did you refresh?", "did you use the 'sum' function?" or "did you remember to clear the cache?". Redash helps you make sense of your data by connecting and querying your data sources, build dashboards to visualize data and share them with your company.

How it works

Redash is most used for connecting commonly used data resources to create visualizations and ultimately tell the story of what your data is saying. This makes it easy to share with others within and outside of your data organization, collaborate, and make data-backed decisions. It's also used to make sure that everyone in the organization has consistent information, creating a single source of truth with regards to your data. Some of the key features of Redash include:

• Web-based tooling, so users don't need to set up an environment dedicated to it.
• Query editing. This means that using Redash allows users to add, delete, and alter data from the toolk itself.
• Drag and drop data visualization. This is a user-friendly capability that allows anyone to create dashboards comprising of the data they need to demonstrate and work with.
• Data source connectivity: Redash supports connectivity to various data sources, including databases, cloud data warehouses, and business applications. It has built-in connectors for popular data sources like MySQL, PostgreSQL, Amazon Redshift, Google BigQuery, and more.
• Query building and visualization: Redash allows users to create custom queries and visualize the results using a wide range of chart types and formatting options. It supports SQL queries, as well as other query languages such as Python and R.
• Dashboards and reports: Redash enables users to build and share interactive dashboards and reports with others, allowing them to easily track key performance metrics and monitor business trends.
• Collaboration and sharing: Redash provides collaborative features such as sharing, commenting, and annotations, allowing users to work together on data analysis projects and share insights with others.
• Security and access controls: Redash provides robust security features, including role-based access controls, data source permissions, and encrypted connections, ensuring that sensitive data remains secure.

Redash use cases

Redash is used for data visualization and collaboration, primarily in the context of business intelligence and data analytics. Here are some common use cases for Redash:

1. Data exploration: Redash allows users to connect to various data sources and explore the data using custom queries and visualizations. This helps users to gain insights into business performance and identify trends and patterns in the data.
2. Dashboarding: Redash enables users to build custom dashboards that display key performance indicators (KPIs) and metrics in a visually appealing and interactive format. This helps organizations to track progress towards business goals and make data-driven decisions.
3. Reporting: Redash allows users to create custom reports that summarize the data in a meaningful way. This helps organizations to communicate insights to stakeholders and make informed decisions.
4. Collaboration: Redash provides collaborative features such as sharing, commenting, and annotations, allowing users to work together on data analysis projects and share insights with others.
5. Data-driven decision-making: Redash helps organizations to make data-driven decisions by providing easy access to data and enabling users to visualize and analyze the data in a way that is meaningful to them.

Overall, Redash is used by organizations of all sizes and across a range of industries to democratize data access, improve data literacy, and drive data-informed decision-making.

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Is Redash open source?

Redash is built atop two powerful open source tools:

Data Sources: Redash supports many common databases out of the box (PostgreSQL, MySQL, SQL Server, Redshift, BigQuery and more), but its functionality can be extended further by writing custom queries and integrations.

Visualizations: Redash uses Metabase’s open source visualizations library as a foundation for building charts. They are highly customizable and you can create new ones using D3 or Vega-Lite (you must be a JavaScript master).

What are the limitations?

• Technical understanding of SQL. In order to use Redash to its full capabilities, the user must have a thorough understanding of SQL. This cuts out the ability for anyone with limited data knowledge to interact with the data without the help of a data analyst or engineer.
• Not always time-efficient. When working with Big Data, Redash must parse every record before actually displaying the data itself.

Learn more about Secoda

Secoda is the #1 Data Enablement Platform for data driven companies to activate more of their data. Learn more about our integration with Redash here