Connect Google Cloud Storage to Cortex: Dashboards in Minutes

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Google Cloud Storage
Cortex

Visualize Google Cloud Storage Data in Cortex

How to visualize Google Cloud Storage data in Cortex? Kondado provides a direct connection that lets you replicate your CSV files from Google Cloud Storage directly into Cortex without any intermediate databases or complex technical setup. You simply select your files, choose how often you want the data refreshed, and start building visualizations that help you track file inventory and monitor data assets. Business teams can analyze file modification patterns, track storage usage trends, and make informed operational decisions without waiting for IT support or writing any code.

Kondado connects Google Cloud Storage to Cortex using a direct “Via Kondado” connection that replicates your CSV file data on a configurable schedule, enabling you to track file basenames, paths, and modification dates directly in your Cortex dashboards to monitor your cloud storage assets continuously.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

With the CSV pipeline from Google Cloud Storage, you can visualize detailed file metadata including basenames, file paths, and modification timestamps directly in Cortex. This lets you build custom dashboards that track when files were last updated, monitor which directories contain the most recent data, and identify storage patterns across your cloud buckets. You can also set up additional CSV pipelines to track different file groups or buckets, enabling marketing teams to verify campaign data freshness while operations teams audit file delivery schedules and ensure critical business documents follow expected update timelines.

Try out all the features for free for 14 days

Google Cloud Storage data available in Cortex

1
available pipeline
8
extractable fields

Available integrations

Integration Description
CSV Table includes information about CSV files, featuring fields such as __file_basename, __file_path, and __kdd_insert_time, enabling tracking of the modification date and value of each file.
CSV
Table includes information about CSV files, featuring fields such as __file_basename, __file_path, and __kdd_insert_time, enabling tracking of the modification date and value of each file.

Try out all the features for free for 14 days

How to create Google Cloud Storage dashboards in Cortex

Visualize your data automatically — no spreadsheet exports or custom scripts.

1
Connect Google Cloud Storage source

Authorize your Google Cloud Storage account in Kondado and select the CSV files you want to visualize in Cortex.

2
Choose Cortex destination

Select Cortex as your destination to receive the file metadata, with no intermediate databases required for the transfer.

3
Configure refresh and build dashboards

Set your preferred update frequency, then start building custom dashboards in Cortex to track file modifications, paths, and storage patterns.

Access Google Cloud Storage data in Cortex and combine it with dozens of other data sources

If the source you want is not listed, drop us a chat message. We love to add new sources!

Visualize Google Cloud Storage data in other BI tools

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Frequently Asked Questions (FAQ)

Answers about visualizing Google Cloud Storage data in Cortex automatically

How do I connect Google Cloud Storage to Cortex using Kondado?
Authorize your Google Cloud Storage account in Kondado, select the CSV files you want to visualize, and choose Cortex as your destination. The connection uses a direct "Via Kondado" method that requires no intermediate databases or coding knowledge, allowing you to start replicating data within minutes.
What dashboards can I build with Google Cloud Storage data in Cortex?
You can build custom dashboards that monitor file modification dates, track storage bucket organization, and visualize file inventory trends over time. These reports help operations teams audit data freshness and marketing teams verify that campaign files are being updated on schedule.
How often does the data update in Cortex from Google Cloud Storage?
You configure the refresh schedule based on your business needs, with options ranging from every 5 minutes to daily or weekly updates. This configurable schedule ensures your Cortex dashboards reflect the most recent file metadata without manual intervention or complex automation scripts.
What specific KPIs can I track from my CSV files in Cortex?
You can track metrics such as the number of files modified per day, average time between file updates, storage directory usage patterns, and file naming consistency across buckets. These insights help identify data delivery delays and optimize your cloud storage organization.
Are there pre-built report templates for Google Cloud Storage in Cortex?
There are no pre-built report templates for this connection, allowing you to create fully customized dashboards tailored to your specific file tracking needs. You design visualizations that focus on the exact file metadata fields and time ranges that matter most to your business operations.
How do I share Cortex dashboards with my team using Google Cloud Storage data?
Once your dashboards are built in Cortex, you can share them with stakeholders through standard Cortex sharing features, giving team members access to current file status without requiring them to browse your Google Cloud Storage buckets manually. This simplifies collaboration while keeping your data access separate from your reporting layer.
Can I visualize multiple CSV files from different buckets in one Cortex dashboard?
Yes, you can combine data from multiple CSV files across different buckets into unified Cortex dashboards by setting up separate pipelines for each file location. This consolidated view lets you compare file update patterns across projects, regions, or departments in a single visualization.
What fields are available when replicating Google Cloud Storage files to Cortex?
The CSV pipeline includes eight fields such as __file_basename for the filename, __file_path for the full directory location, and __kdd_insert_time for tracking when the record was last replicated. These fields enable you to monitor file locations, identify storage patterns, and track data freshness automatically.

Try out all the features for free for 14 days