如何批量获取多仪表板的usage metrics（浏览次数）并动态生成报告

Hey there! Totally feel your pain—manual checking of usage metrics (like view counts) for dozens of dashboards is such a time-suck and leaves room for mistakes. Here are some practical, dynamic approaches to solve this:

1. Use Your BI Platform's REST API (Most Flexible Option) #

Nearly all modern BI tools (Tableau, Power BI, Looker, etc.) expose a REST API that lets you pull usage data programmatically. This is the most scalable way if you have a lot of dashboards.

For example, if you're using Tableau, you could write a quick Python script to loop through your dashboard IDs and fetch view counts:

import requests
import pandas as pd

# Configure your server details and auth
base_url = "https://your-tableau-server.com/api/3.20"
auth_token = "your-auth-token"
site_id = "your-site-id"
dashboard_ids = ["dash-id-1", "dash-id-2", "dash-id-3"]  # List all your dash IDs

usage_data = []
headers = {"X-Tableau-Auth": auth_token}

for dash_id in dashboard_ids:
    # Fetch view metrics for the dashboard
    endpoint = f"{base_url}/sites/{site_id}/views?filter=dashboardId:eq:{dash_id}"
    response = requests.get(endpoint, headers=headers)
    views = response.json()["views"]["view"]
    
    for view in views:
        usage_data.append({
            "dashboard_id": dash_id,
            "dashboard_name": view["name"],
            "total_views": view["viewCount"]
        })

# Convert to DataFrame and export to CSV/Excel for your report
df = pd.DataFrame(usage_data)
df.to_excel("dashboard_usage_report.xlsx", index=False)

Just adapt this to your tool's specific API endpoints—check their official docs for exact payloads and auth methods.

2. Use Command-Line Tools (No Coding Required for Basic Tasks) #

If you're not into writing scripts, many tools have CLI tools that let you bulk export metrics. For example:

• Power BI: Use the pbicli tool to pull workspace usage data and filter for dashboards.
• Looker: Use the looker CLI with commands like looker usage dashboard to export metrics in bulk.

You can wrap these commands in a shell/PowerShell script to automate the export and even pipe the output straight into your report file.

3. Use Built-in Admin Reporting Features #

Don't overlook your platform's native admin tools! Most BI platforms have built-in reports that show usage across all content:

• Tableau Server: Go to the Site Usage report under Admin > Reports, and you can export a CSV with all dashboard view counts.
• Power BI: In the Admin Portal, navigate to Usage metrics > Dashboards and export the full dataset.
• Looker: Use the System Activity dashboard to filter and export dashboard usage data.

This is the quickest option if your tool supports it—no code needed, just a few clicks to get a bulk export.

4. Automate the Pipeline to Your Report #

Once you have the bulk data, you can automate feeding it into your report:

• If your report is in Excel/Google Sheets: Use pandas (Python) or Google Sheets API to write the data directly into your report tab.
• If it's another BI dashboard: Set up a scheduled refresh to pull the exported usage data into your report dashboard automatically.

Pro Tips #

• Always test with a small set of dashboards first before running a full bulk request.
• Handle API pagination—many APIs return data in chunks, so you'll need to loop through pages if you have hundreds of dashboards.
• Schedule your script/export to run automatically (using cron on Linux, Task Scheduler on Windows) so your report stays up-to-date without manual work.

Hope one of these methods works for you—let me know if you need help adapting it to your specific BI tool!

内容的提问来源于stack exchange，提问作者SREEKAR