What is BigQuery Connected Sheets?

BigQuery Connected Sheets (also called the BigQuery Data Connector) is a built-in Google Sheets feature that lets you run BigQuery queries directly from a spreadsheet. The results appear in your sheet as a connected range — no data export, no CSV download. The data refreshes from BigQuery on demand or on a schedule you configure.

Do I need to be a BigQuery admin to use Connected Sheets?

You need read access to the BigQuery dataset you want to query. A project Viewer role is sufficient. Your Google Workspace admin may also need to enable the BigQuery Data Connector in Sheets — it is generally enabled by default in Google Workspace Business and Enterprise tiers.

How does Chartcastr connect to Connected Sheets data?

Chartcastr connects to the Google Sheet (via OAuth) and reads from the range where Connected Sheets has placed the query results. On each pulse delivery, Chartcastr triggers a data refresh in the sheet, waits for the updated results, then renders and posts the chart. This means each Slack post reflects current BigQuery data at delivery time.

Is there a cost for BigQuery Connected Sheets queries?

Yes — each query refresh consumes BigQuery query capacity at standard on-demand rates (or against your flat-rate reservation if you have one). For typical reporting views (weekly aggregates, monthly rollups), the query cost is minimal — usually a few cents per run. Use a materialised view or Scheduled Query to write results into a native BQ table first if you want to cap query costs.

BigQuery Connected Sheets to Slack: Step-by-Step Setup

May 6, 2026•6 min read

A practical walkthrough of connecting BigQuery to Google Sheets using the Data Connector, then delivering those results to Slack automatically with Chartcastr — no Python, no Cloud Functions.

BigQuery Connected Sheets to Slack: Step-by-Step Setup

BigQuery Connected Sheets is the least-friction path to get BigQuery data into a format that Chartcastr can deliver to Slack. No Python. No Cloud Functions. No export pipelines. You write a SQL query in a spreadsheet, and Chartcastr handles the rest.

This guide walks through the full setup — from an empty Google Sheet to a scheduled Slack pulse — in under 30 minutes.

What You're Building

BigQuery SQL view
       ↓
Google Sheets (Connected Sheets / Data Connector)
       ↓
Chartcastr source
       ↓
Slack channel — scheduled chart + AI summary

The Connected Sheet acts as a thin bridge between BigQuery and Chartcastr. Chartcastr reads from the sheet, renders the data as a chart, and posts to Slack on your schedule with an AI-written summary of what changed.

Prerequisites

A BigQuery project with a dataset you want to report on
A Google account with read access to that dataset
A Chartcastr account (free tier works)
Chartcastr connected to your Slack workspace

Step 1: Create Your BigQuery View

Before connecting to Sheets, shape your data into a clean, reportable format. The SQL view is the right place to do aggregations, filters, and date logic — not in the spreadsheet.

Good practices for reporting views:

Use human-readable column names (weekly_revenue, not sum_rev_usd_7d)
Pre-aggregate to the granularity you want to display (week, month)
Include a date column for time series
Filter to a meaningful rolling window

-- Example: weekly revenue by channel, last 16 weeks
CREATE OR REPLACE VIEW `your-project.reporting.weekly_revenue_by_channel` AS
SELECT
  DATE_TRUNC(order_date, WEEK(MONDAY)) AS week_start,
  channel,
  COUNT(DISTINCT order_id)             AS order_count,
  ROUND(SUM(revenue_usd), 2)           AS revenue_usd,
  ROUND(SUM(revenue_usd) / NULLIF(COUNT(DISTINCT order_id), 0), 2) AS avg_order_value
FROM `your-project.sales.orders`
WHERE
  order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 16 WEEK)
  AND status NOT IN ('cancelled', 'refunded')
GROUP BY 1, 2
ORDER BY 1 DESC, 3 DESC

Test the view in the BigQuery Console before connecting it to Sheets. Confirm the columns look right and the row count is reasonable (a few hundred rows is ideal — Connected Sheets can handle thousands, but smaller is faster and cheaper to query).

Step 2: Connect BigQuery to Google Sheets

Open a new Google Sheet.
Go to Data → Data connectors → Connect to BigQuery.
- If you don't see this option, check that BigQuery Data Connector is enabled in your Google Workspace admin console.
Select your GCP project.
Choose Custom query (rather than browsing tables — it gives you more control).

Paste your SQL, or reference your view:

SELECT * FROM `your-project.reporting.weekly_revenue_by_channel`
ORDER BY week_start DESC

Click Connect.

Sheets runs the query and places results in a connected range starting at cell A1. You'll see a small "Connected to BigQuery" badge in the top-left of the range.

Name and organise your sheet

Rename the tab to something descriptive: bq_weekly_revenue
In a separate tab, you can build formatting or pivot tables on top of the connected range without affecting the connector

Refresh behaviour

Connected Sheets results are cached. To get fresh data:

Click the Refresh icon next to the connected range
Or use Data → Data connectors → Manage → Refresh now

Chartcastr will trigger a refresh before each pulse run, so your Slack posts always reflect current BigQuery data.

Step 3: Connect the Sheet to Chartcastr

In Chartcastr, go to Sources → Add source → Google Sheets.
Authenticate with your Google account.
Paste the URL of the Google Sheet you just set up.
Select the tab containing the connected data range (bq_weekly_revenue).
Chartcastr detects your columns and asks you to confirm the data range.
Save the source.

Chartcastr reads your data, detects the numeric and date columns, and suggests a chart type. For a weekly time series with a category breakdown (week, channel, revenue), it'll default to a grouped bar or stacked bar chart.

Step 4: Set Up the Slack Connection

In Chartcastr, go to Connections → New connection.
Select the Google Sheets source you just added.
Choose your Slack channel. This is where the chart will be posted.
Preview the chart — check that the columns and chart type look right.
Set your schedule: daily, weekly (e.g. every Monday 8:30am), or a custom cadence.
Activate the connection.

Your first pulse will be delivered at the next scheduled time.

What the Pulse Looks Like

Each Chartcastr pulse to Slack includes:

Chart image — a clean bar, line, or area chart rendered from your connected data.
AI summary — a plain-English explanation of what changed since the last delivery: which channels grew, which contracted, notable week-over-week shifts.
Thread Q&A — your team can reply in the thread to ask follow-up questions; Chartcastr answers against the current data.

Common Report Configurations

Different teams use slightly different query patterns for their Connected Sheets sources. Here are three proven setups:

Marketing: Weekly channel performance

SELECT
  DATE_TRUNC(date, WEEK(MONDAY)) AS week_start,
  channel,
  SUM(sessions)     AS sessions,
  SUM(conversions)  AS conversions,
  SUM(revenue_usd)  AS revenue
FROM `your-project.marketing.attribution`
WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 12 WEEK)
GROUP BY 1, 2
ORDER BY 1 DESC, 4 DESC

Pulse cadence: every Monday at 9am. Posted to #marketing-weekly.

Finance: Monthly P&L summary

SELECT
  DATE_TRUNC(transaction_date, MONTH) AS month,
  account_category,
  SUM(amount_usd) AS net_amount
FROM `your-project.finance.gl_entries`
WHERE
  transaction_date >= DATE_TRUNC(DATE_SUB(CURRENT_DATE(), INTERVAL 6 MONTH), MONTH)
GROUP BY 1, 2
ORDER BY 1 DESC, 2

Pulse cadence: first Monday of each month. Posted to #finance-leads.

Product: Daily active users

SELECT
  event_date,
  COUNT(DISTINCT user_id) AS dau
FROM `your-project.analytics.events`
WHERE
  event_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)
  AND event_name = 'session_start'
GROUP BY 1
ORDER BY 1

Pulse cadence: daily at 10am. Posted to #product-metrics.

Troubleshooting

The Connected Sheets range is empty after connecting The query may have returned zero rows for the date range. Check your WHERE clause — particularly the interval used for date filtering.

Chartcastr shows "no data" when I add the source Confirm the tab name in Chartcastr matches exactly the tab name in your sheet (case-sensitive). Also check that the connected range starts at A1 with headers in row 1.

Data in Slack looks stale Connected Sheets caches results. Chartcastr triggers a refresh before delivery, but if your GCP project has query quota limits, the refresh may time out. Consider writing results to a native BigQuery table with a Scheduled Query and reading from that instead — see BigQuery Scheduled Queries → Slack Reporting.

BigQuery Connected Sheets to Slack: Step-by-Step Setup

BigQuery Connected Sheets to Slack: Step-by-Step Setup

What You're Building

Prerequisites

Step 1: Create Your BigQuery View

Step 2: Connect BigQuery to Google Sheets

Name and organise your sheet

Refresh behaviour

Step 3: Connect the Sheet to Chartcastr

Step 4: Set Up the Slack Connection

What the Pulse Looks Like

Common Report Configurations

Marketing: Weekly channel performance

Finance: Monthly P&L summary

Product: Daily active users

Troubleshooting

Related Reading

Frequently Asked Questions

Turn your data into automated team updates.

Chartcastr