- version
- 2.0.0
- name
- Azuredatastudio
- description
- Azure Data Studio is a data management and development tool with connectivity to popular cloud and o azuredatastudio, typescript, azure, azure-data-studio.
- author
- BytesAgain
- homepage
- https://bytesagain.com
- source
- https://github.com/bytesagain/ai-skills
Azure Data Studio
A data processing and analysis toolkit for querying, importing, exporting, transforming, and validating data. Provides a lightweight CLI interface for common data operations with persistent local storage.
Commands
| Command | Description |
|---|---|
query | Query data with provided search terms |
import | Import a data file into the local data store |
export | Export results to a specified destination or stdout |
transform | Transform data from one format to another |
validate | Validate data against the expected schema |
stats | Show basic statistics (record count) |
schema | Display the data schema (id, name, value, timestamp) |
sample | Show sample data (first 5 records from data log) |
clean | Clean and deduplicate data entries |
dashboard | Show a quick dashboard with total record count |
help | Show the help message with all available commands |
version | Print the current version number |
Data Storage
- Data directory:
~/.local/share/azuredatastudio/(override withAZUREDATASTUDIO_DIRenv variable) - Data log:
$DATA_DIR/data.log— primary data storage file for records - History log:
$DATA_DIR/history.log— tracks all command executions with timestamps
Schema
The default data schema uses the following fields:
| Field | Description |
|---|---|
id | Unique record identifier |
name | Entry name or label |
value | Data value |
timestamp | When the record was created |
Requirements
- Bash 4.0+
- Standard Unix utilities (
wc,head,cat,date) - No API keys or external services needed
- No database server required — uses flat file storage
- Works on Linux and macOS
When to Use
- Data querying — When you need to run quick queries against your local data store without spinning up a full database
- File import/export — When you need to import data files into the local store or export records for use in other tools
- Data validation — When you want to verify your data conforms to the expected schema before processing
- Data transformation — When you need to convert data between formats (e.g., restructuring fields)
- Quick statistics — When you want to see basic metrics like total record count or preview sample data at a glance
Examples
# Query data with search terms
azuredatastudio query "SELECT * FROM users WHERE active=1"
# Import a CSV file
azuredatastudio import data.csv
# Export results to a file
azuredatastudio export results.json
# Transform data from one format to another
azuredatastudio transform input.csv output.json
# Validate data against the schema
azuredatastudio validate
# Show basic statistics
azuredatastudio stats
# Display the data schema
azuredatastudio schema
# Preview sample data (first 5 records)
azuredatastudio sample
# Clean and deduplicate data
azuredatastudio clean
# Show a quick dashboard with totals
azuredatastudio dashboardOutput
All command results are printed to stdout. You can redirect output with standard shell operators:
azuredatastudio query "users" > query-results.txt
azuredatastudio export | jq .
azuredatastudio stats >> report.logConfiguration
Set the AZUREDATASTUDIO_DIR environment variable to change the data directory:
export AZUREDATASTUDIO_DIR="/custom/path/to/azuredatastudio"Default location: ~/.local/share/azuredatastudio/
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