...

3.1. View

3.1.1. Choose dashboard

1. Click dashboards on toolbar.
2. Search title or filter by owner, created by, status,...
3. Click Choose dashboard to view

3.1.2. Filter

1. After choose dashboard, select Filters on left-side bar
2. Apply filters

3.1.3. View query

On current dashboard, choose the chart → Click View query

3.1.4. Download data from chart

1. Choose the chart you would like to download
2. Select Export to .CSV or Download as image

3.2. Edit

1. Click button Edit dashboard
2. Create, Edit, Delete charts
3. Discard or Save

3.3. Create

1. Click dashboards on toolbar
2. Click button Add dashboard
3. Set title dashboard, create new chart...
4. Save

4. Chart

4.1. View

4.1.1. Choose chart

1. Click Charts on toolbar
2. Search or filter
3. Choose chart you would like to view

4.1.2. Filter

1. Click box Time range
2. Select range type
3. Apply
4. Select column at Filters
5. Click button Update chart

Note: Please do not save if you only want to view the chart.

4.2. Create

1. Click Charts on toolbar
2. Click button Add chart
3. Choose a dataset
4. Click button Create new chart
5. Add name, time column, metrics, filters and customize

5. Query

1. Click SQL on toolbar

1. Select database
2. Select schema
3. Write code SQL to get data
4. Select limit
5. Click button Run

Optional: 

• Save query or Save dataset
• Select "See table schema" to Preview table

6. Considerations when querying

Given Superset's shared usage, it's crucial to optimize queries and datasets while creating dashboards to ensure a seamless experience for all users

1. Specify What You Need: Be clear about the data you need and only request the necessary fields to minimize the amount of data returned.

2. Avoid SELECT *: Avoid using SELECT * as it retrieves all columns, which can be inefficient. Instead, explicitly list the columns you need.

3. Filter Early: Apply filters and conditions early in your query to reduce the dataset size before any complex operations are performed.

4. Use Joins Wisely: Be mindful of how you use joins, as they can be resource-intensive. Use INNER JOIN, LEFT JOIN, etc., as appropriate for your data relationships.

5. Aggregate Smartly: When performing aggregations, consider the efficiency of GROUP BY and aggregation functions like COUNT, SUM, AVG, etc.

6. Limit Results: Use the LIMIT clause to restrict the number of rows returned, especially when working with large datasets.

7. Monitor Performance: Regularly monitor query performance, identify bottlenecks, and optimize slow queries.

8. Avoid Nested Subqueries: Be cautious when using nested subqueries, as they can be complex and impact performance.

9. Consider Data Types: Be aware of data types and conversions when filtering or manipulating data.

10. Caching: Implement caching for frequently used queries to reduce database load.