Skip to content
Notis

See Uploadcare volume trends before planning day

Use recent activity to make capacity conversations easier.

Trigger

Recurring schedule

Notis starts this workflow on a schedule, such as daily, weekly, or during business hours.

Action

Query

Query tool will run a sql query in bigquery. note: make sure the query being input in a single line format. for example, select * from sample dataset.sample table where column name = 'value'

Why this helps

Volume changes are noticed only after they disrupt plans.

  • Earlier planning signals
  • Less reactive coordination

Setup

Build it in a few focused steps.

  • 1Connect Uploadcare and Google BigQuery to Notis once.
  • 2Create an automation through the portal or by asking Notis.
  • 3Ask Notis to query recent asset-volume trends in BigQuery.
  • 4Pick a weekly schedule and report channel.
  • 5Test with your current activity data.

Questions about this workflow

Is this a prediction model?

It runs the trend analysis you describe in BigQuery.

When this happens · Trigger

Do this · Action

Supported Triggers and Actions

Notis builds workflows that link Uploadcare to Google BigQuery. A trigger fires from one place; an action lands in another.

Uploadcare triggers

Google BigQuery actions

Recurring trigger

Notis starts this workflow on a schedule, such as daily, weekly, or during business hours.

TriggerScheduled

Query

Query tool will run a sql query in bigquery. note: make sure the query being input in a single line format. for example, select * from sample dataset.sample table where column name = 'value'

ActionInstant

Webhook trigger

Notis starts this workflow when an external tool or custom backend sends an HTTP request.

TriggerInstant

Connect any two apps with Notis in the middle.

Uploadcare and Google BigQuery, or any other combination from 1,000+ integrations.

When this happens · Trigger

Do this · Action

Save your first hour today.

7-day trial of any paid plan, with 20$ of usage included.
No card. Works with personal or business Google BigQuery.