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Automated Bigeye Data Quality Alert Digest

Every morning, WebRun opens Bigeye, reads every data quality alert triggered since the last check, books a data quality review slot on Google Calendar when the number of alerts spikes past normal, and posts the full digest to Microsoft Teams.

Runs on WebRun · Strict Lockdown policy
Every day at 7:00 AM WebRunorchestrates each step
1 Bigeye read triggered alerts
2 Google Calendar book a review slot on a spike
3 Microsoft Teams post the digest
In short

How do I get a daily digest of Bigeye data quality alerts?

WebRun checks Bigeye every morning for data quality alerts triggered since the last run, books a review slot on Google Calendar when the alert count spikes past normal, and posts the full digest to Microsoft Teams. Data observability teams see the day's quality issues grouped by table with a review already scheduled on a real spike.

  • A quality alert spike gets a booked review slot the same morning
  • Alerts are grouped by table, not read one by one
  • Normal day to day noise never triggers a false alarm

Built for data observability teams · data engineering teams · analytics engineering teams

Step by step

What does WebRun do on every run?

The exact actions WebRun takes, in order - in plain language, so you can adjust anything.

  1. WebRun signs in and gets to work

    Opens app.bigeye.com in a real browser with your saved login - no setup, no API keys.

  2. 1
    Bigeye - read triggered alerts
    bigeye.com
    WebRun in Bigeye: read triggered alerts
    WebRun opens Bigeye to read triggered alerts.
    • Open Bigeye and check alerts triggered since the last run
    • Read each alert's affected table and metric
    • Compare today's alert count to the normal daily range

    Done when Every alert since the last check is read and counted.

  3. 2
    Google Calendar - book a review slot on a spike
    calendar.google.com
    WebRun in Google Calendar: book a review slot on a spike
    WebRun opens Google Calendar to book a review slot on a spike.
    • If the alert count spiked past normal range, open Google Calendar
    • Find the next open working hours slot for the data team
    • Book a data quality review titled with the spike's size

    Done when A spike has a booked review slot on the calendar.

  4. 3
    Microsoft Teams - post the digest
    microsoft.com
    WebRun in Microsoft Teams: post the digest
    WebRun opens Microsoft Teams to post the digest.
    • Open the data platform channel in Microsoft Teams
    • Post today's alerts grouped by affected table
    • Include the review slot time if one was booked

    Done when The team has today's alert digest in Teams.

Run settings

How is each run configured?

Starting pageWhere Chrome opens at the start of each run
app.bigeye.com
ScheduleRuns automatically on this cadence
Every day at 7:00 AM
DeliveryHow each run's result reaches you
Quality digest · Microsoft Teams
OutputWhat each run produces - A daily digest of data quality alerts by table, with a booked review slot whenever alerts spike.
Text
Setup & safety

Secure by default

Connect once, stays signed in

WebRun signs in once and keeps each session in a persistent environment, so every run picks up right where it left off.

Your credentials stay in your own private environment - WebRun never stores your passwords.
Strict Lockdown

Every action is checked against this policy before it runs.

Domains ALLOWLIST
Typed input ALLOW
Shell command BLOCK
File uploads BLOCK
Runs in a contained environment More on policies
Good to know

Questions, answered

Does WebRun resolve or mute a Bigeye alert?

No. It only reads triggered alerts and reports them. Resolving, muting, or tuning an alert stays a manual task.

What counts as a spike?

An alert count outside the normal daily range you set. Ordinary day to day noise does not trigger a review booking.

Does it check every metric in detail?

No. It reads the alerts Bigeye already triggered, not every underlying metric value.

Put this on autopilot.

Turn it on in minutes - or have our team set it up for you.