Redash Masterclass: Dashboards, SQL & On-Prem Deployment

Install docker desktop on Windows 10/11 by downloading the installer, running it as an administrator, and launching the app. Access docker desktop and manage containers, images, volumes, and build.

Learn to run redash on Windows with Docker Desktop by cloning redash, modifying the compose.yml, and starting containers. Then log in at localhost to access the dashboard.

Learn to use the Redash admin panel to manage users, groups, and permissions for secure on-prem deployments, and apply best practices for role-based access and security governance.

Manage data source permissions with group-based access, restrict critical databases, and govern dashboard visibility in on-premises environments; secure credentials, rotate passwords, and grant read-only access to trusted groups.

Distribute and control data source permissions by adding Cassandra, Hive, and MySQL, granting admins full access and business users read-only access to MySQL only.

Explore Redash's data sources from relational databases and data warehouses to NoSQL and big data engines, and see how SQL-first analytics and on-premises deployment fit enterprise needs.

Connect Redash to Apache Cassandra by deploying a Cassandra docker image, creating a keyspace and table, inserting two records, and querying from Redash.

Set up Redash with Docker, start the Hive container, connect Redash to Hive, create testdb and a sample table, insert records, and run a query to fetch them.

Learn to connect MySQL to Redash, set up a MySQL 8.4 instance, create a test database and company table, and query two records via a new Redash data source.

Learn to write efficient sql queries in Redash using the sql editor, schema browser, and autocomplete, then apply best practices for high-performance queries in an on-premises Redash environment.

Learn how query parameters in Redash create interactive dashboards with drop-downs, date pickers, and multi-select filters, applied at the dashboard level for reusable, user-friendly analytics in on premises environment.

Learn how to create reusable SQL snippets in Redash to speed development, enforce standards, and reduce errors, then manage snippet templates for central updates and team collaboration in on-prem setups.

Load a csv file into a MySQL 8.0 database using Docker, then set up Redash to create charts from the loaded data.

Turn query results into powerful Redash visualizations to form the foundation of dashboards. Create multiple visualizations from a single query and configure axes, grouping, and formatting for clear on-prem dashboards.

Select the appropriate chart by matching data type and message to chart types like line, area, bar, pie, histogram, scatter, and consider audience and context.

Create a table chart in redash by running a sql query on the video game sales database, adding a table visualization, and saving the visualization.

Create a box plot visualization in Redash by querying video game sales to plot global sales by genre, filtering out null values, and saving the visualization named box plot.

Create a line chart by querying the my SQL db, visualizing video game sales over time with year as the category axis, and save the chart.

Create a bar chart from a sql query summing global sales by platform. Disable x-axis sorting to show platforms in descending order.

Create an area chart in Redash by querying sum of global sales by year and platform, then set x axis to category and enable sort values and labels.

Create a pie chart of the top ten global sales by genre in redash by writing a query on the MySQL database, grouping by genre, and visualizing the results.

Create a scatter chart by querying North America sales, Europe sales, and January from video game sales in MySQL, then plot with x axis and y axis, grouped by January.

Create a cohort chart by starting a new query, copying it, selecting the database, add a cohort visualization, configure name, date, total number, and values, show data axis, and save.

Create a counter chart in Redash by writing a select query to compute total global sales from video game sales, configure the visualization, and save.

Create a funnel chart in Redash by running a SQL query, selecting a MySQL database, and adding a funnel visualization with step and value columns.

Create a map visualization by querying a MySQL database, executing the SQL to fetch total sales by country (United States, Germany, Japan, Australia), and saving the map.

Create a pivot table visualization by running a select query against the MySQL db. Name it sales pivot table and adjust fields to generate and save the pivot chart.

Create a Sankey chart by querying a MySQL database, selecting publisher as source, platform as target, and count star as value, then add and view the Sankey visualization.

Learn to create a sunburst chart by running a select query, adding visualization, and saving the chart to explore gaming platform level details.

Explore building a word cloud chart from a SQL query on video game sales data for January, select a database, configure frequency, and visualize terms like action and sports.

Create interactive dashboards in Redash by organizing layouts, applying filters, and using widgets. Publish visuals, parameterize queries, and monitor real-time metrics for on-prem deployments.

Master interactive dashboards in Redash with auto refresh, cross filtering, and drill-down queries for real-time monitoring and data exploration.

Run a parameterized SQL query on a video game sales dataset, create a bar chart, save a demo query, and build a dashboard with a dashboard-level filter.

Master the auto refresh feature by setting a one-minute interval to refresh the dashboard automatically. Disable auto refresh and adjust parameters like platform (PS4) while watching the circular refresh indicator.

Build an interactive redash dashboard to analyze global video game sales by platform, genre, publisher, and region using SQL-powered visualizations and trend charts.

Create a video game sales dashboard in Redash using MySQL, building multiple visualizations—area, pie, bar, and stacked charts—to analyze global sales by platform, genre, and market over time.