Organizational datasets contain a powerful query system which lets you explore and slice data. You control the query system through the 'Filter' text box, and you use a language which is very similar to SQL (documentation).
Only available for enterprise customers
Organizational features are only available for enterprise customers. View our pricing for more information.
For example, here are some queries that you can make:
dataset like '%AMS Activity Study%' - returns all items and files from the study.
bucket_name = 'edge-impulse-health-reference-design' AND --labels sitting,walking - returns data whose label is 'sitting' and 'walking, and that is stored in the 'edge-impulse-health-reference-design' bucket.
metadata->ei_check = 0 - return data that have a metadata field 'ei_check' which is '0'.
created > DATE('2022-08-01') - returns all data that was created after Aug 1, 2022.
After you've created a filter, you can select one or more data items, and select Actions...>Download selected to create a ZIP file with the data files. The file count reflects the number of files returned by the filter.
The previous queries all returned all files for a data item. But you can also query files through the same filter. In that case the data item will be returned, but only with the files selected. For example:
file_name LIKE '%.png' - returns all files that end with .png.
If you have an interesting query that you'd like to share with your colleagues, you can just share the URL. The query is already added to it automatically.
These are all the available fields in the query interface:
dataset - Dataset.
bucket_id - Bucket ID.
bucket_name - Bucket name.
bucket_path - Path of the data item within the bucket.
id - Data item ID.
name - Data item name.
total_file_count - Number of files for the data item.
total_file_size - Total size of all files for the data item.
created - When the data item was created.
metadata->key - Any item listed under 'metadata'.
file_name - Name of a file.
file_names - All filenames in the data item, that you can use in conjunction with CONTAINS. E.g. find all items with file X, but not file Y: file_names CONTAINS 'x' AND not file_names CONTAINS 'y'.
