diff --git a/.env_sample b/.env_sample
new file mode 100644
index 0000000..4a5577f
--- /dev/null
+++ b/.env_sample
@@ -0,0 +1 @@
+GCP_PROJECT_ID =
diff --git a/.github/workflows/bigquery-integration.yml b/.github/workflows/bigquery-integration.yml
new file mode 100644
index 0000000..42b1b1c
--- /dev/null
+++ b/.github/workflows/bigquery-integration.yml
@@ -0,0 +1,64 @@
+name: BigQuery Integration Tests
+
+on:
+  workflow_dispatch:
+    inputs:
+      test_suite:
+        type: choice
+        description: Test Suite to Run
+        default: "all"
+        options:
+          - all
+          - cohort_analysis
+          - composite_rank
+          - cross_shop
+          - customer_decision_hierarchy
+          - haversine
+          - hml_segmentation
+          - product_association
+          - revenue_tree
+          - rfm_segmentation
+          - segstats_segmentation
+          - threshold_segmentation
+
+permissions:
+  contents: read
+
+concurrency:
+  group: "bigquery-tests"
+  cancel-in-progress: true
+
+jobs:
+  integration-tests:
+    name: Run BigQuery Integration Tests
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install uv Package
+        run: |
+          pip install --upgrade pip
+          pip install uv==0.5.30
+
+      - name: Install Dependencies
+        run: |
+          uv sync
+          uv sync --group dev
+
+      - name: Set up GCP Authentication
+        uses: google-github-actions/auth@v2
+        with:
+          credentials_json: ${{ secrets.GCP_SA_KEY }}
+
+      - name: Run Integration Tests
+        env:
+          TEST_SUITE: ${{ inputs.test_suite }}
+        run: |
+          uv run pytest tests/integration/bigquery -v \
+            $(if [ "$TEST_SUITE" != "all" ]; then echo "-k $TEST_SUITE"; fi)
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 415c56d..1ae46c6 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -25,7 +25,7 @@ repos:
     hooks:
       - id: pytest
         name: pytest
-        entry: uv run pytest --cov=pyretailscience --cov-report=xml --cov-branch tests
+        entry: uv run pytest --cov=pyretailscience --cov-report=xml --cov-branch tests --ignore=tests/integration/bigquery
         language: system
         types: [python]
         pass_filenames: false
diff --git a/README.md b/README.md
index 24ca462..635ff7e 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,4 @@
+<!-- README.md -->
 ![PyRetailScience Logo](https://raw.githubusercontent.com/Data-Simply/pyretailscience/main/readme_assets/logo.png)
 
 # PyRetailScience
@@ -208,3 +209,68 @@ Built with expertise doing analytics and data science for scale-ups to multi-nat
 ## License
 
 This project is licensed under the Elastic License 2.0 - see the [LICENSE](LICENSE) file for details.
+
+# BigQuery Integration Tests
+
+## Overview
+
+This directory contains integration tests that verify all PyRetailScience analysis modules
+work correctly with Google BigQuery as a backend. These tests confirm that the Ibis-based
+code paths function correctly when connected to BigQuery.
+
+## Test Coverage
+
+The integration tests cover the analysis modules.
+
+## Prerequisites
+
+To run these tests, you need:
+
+1. Access to a Google Cloud Platform account
+2. A service account with BigQuery permissions
+3. The service account key JSON file
+4. The test dataset must be loaded in BigQuery (dataset: `test_data`, table: `transactions`)
+
+## Running the Tests
+
+### Manual Setup
+
+- Set up authentication:
+
+```bash
+export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your/service-account-key.json
+export GCP_PROJECT_ID=your-project-id
+```
+
+- Install dependencies:
+
+```bash
+uv sync
+```
+
+- Run the tests:
+
+```bash
+# Run all tests
+uv run pytest tests/integration/bigquery -v
+
+# Run specific test module
+uv run pytest tests/integration/bigquery/test_cohort_analysis.py -v
+```
+
+## Using GitHub Actions
+
+These tests can be run manually in GitHub Actions via the "BigQuery Integration Tests" workflow. To run:
+
+1. Go to the "Actions" tab in the GitHub repository
+2. Select the "BigQuery Integration Tests" workflow
+3. Click "Run workflow"
+4. Optionally enter a test filter pattern (e.g., "test_cohort_analysis")
+5. Click "Run workflow"
+
+### Required Secrets
+
+To run the workflow in GitHub Actions, add these secrets to your repository:
+
+- `GCP_SA_KEY`: The entire JSON content of your GCP service account key file
+- `GCP_PROJECT_ID`: Your GCP project ID
diff --git a/pyproject.toml b/pyproject.toml
index f8b11b9..2ec5965 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,11 +27,13 @@ name  = "Murray Vanwyk"
 [dependency-groups]
 dev = [
     "freezegun>=1.5.1,<2",
+    "ibis-framework[bigquery]>=10.0.0,<11",
     "nbstripout>=0.7.1,<0.8",
     "pre-commit>=3.6.2,<4",
     "pytest-cov>=4.1.0,<5",
     "pytest-mock>=3.14.0,<4",
     "pytest>=8.0.0,<9",
+    "python-dotenv>=1.0.0,<2",
     "ruff>=0.9,<0.10",
     "tomlkit>=0.12,<1",
 ]
diff --git a/pyretailscience/segmentation/threshold.py b/pyretailscience/segmentation/threshold.py
index 933c0bb..a216fb0 100644
--- a/pyretailscience/segmentation/threshold.py
+++ b/pyretailscience/segmentation/threshold.py
@@ -83,14 +83,11 @@ def __init__(
         window = ibis.window(order_by=ibis.asc(df[value_col]))
         df = df.mutate(ptile=ibis.percent_rank().over(window))
 
-        case = ibis.case()
-
+        case_args = []
         for quantile, segment in zip(thresholds, segments, strict=True):
-            case = case.when(df["ptile"] <= quantile, segment)
-
-        case = case.end()
+            case_args.append((df["ptile"] <= quantile, segment))
 
-        df = df.mutate(segment_name=case).drop(["ptile"])
+        df = df.mutate(segment_name=ibis.cases(*case_args)).drop(["ptile"])
 
         if zero_value_customers == "separate_segment":
             df = ibis.union(df, zero_df)
diff --git a/tests/integration/bigquery/conftest.py b/tests/integration/bigquery/conftest.py
new file mode 100644
index 0000000..c65b03e
--- /dev/null
+++ b/tests/integration/bigquery/conftest.py
@@ -0,0 +1,33 @@
+"""BigQuery integration test fixtures."""
+
+import os
+
+import ibis
+import pytest
+from dotenv import load_dotenv
+from google.cloud import bigquery
+from loguru import logger
+
+load_dotenv()
+client = bigquery.Client(project="pyretailscience-infra")
+
+
+@pytest.fixture(scope="session")
+def bigquery_connection():
+    """Connect to BigQuery for integration tests."""
+    try:
+        conn = ibis.bigquery.connect(
+            project_id=os.environ.get("GCP_PROJECT_ID"),
+        )
+        logger.info("Connected to BigQuery")
+    except Exception as e:
+        logger.error(f"Failed to connect to BigQuery: {e}")
+        raise
+    else:
+        return conn
+
+
+@pytest.fixture(scope="session")
+def transactions_table(bigquery_connection):
+    """Get the transactions table for testing."""
+    return bigquery_connection.table("test_data.transactions")
diff --git a/tests/integration/bigquery/test_cohort_analysis.py b/tests/integration/bigquery/test_cohort_analysis.py
new file mode 100644
index 0000000..545a443
--- /dev/null
+++ b/tests/integration/bigquery/test_cohort_analysis.py
@@ -0,0 +1,27 @@
+"""Integration tests for Cohort Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.cohort import CohortAnalysis
+
+
+def test_cohort_analysis_with_bigquery(transactions_table):
+    """Integration test for CohortAnalysis using BigQuery backend and Ibis table.
+
+    This test ensures that the CohortAnalysis class initializes and executes successfully
+    using BigQuery data with various combinations of aggregation parameters.
+    """
+    limited_table = transactions_table.limit(5000)
+
+    try:
+        CohortAnalysis(
+            df=limited_table,
+            aggregation_column="unit_spend",
+            agg_func="sum",
+            period="week",
+            percentage=True,
+        )
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(
+            f"CohortAnalysis failed: {e}",
+        )
diff --git a/tests/integration/bigquery/test_composite_rank.py b/tests/integration/bigquery/test_composite_rank.py
new file mode 100644
index 0000000..c25f3b1
--- /dev/null
+++ b/tests/integration/bigquery/test_composite_rank.py
@@ -0,0 +1,58 @@
+"""Integration tests for Composite Rank Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.composite_rank import CompositeRank
+
+
+@pytest.fixture
+def test_transactions_table(transactions_table):
+    """Fetch test transactions data from BigQuery and convert it to a pandas DataFrame.
+
+    The expected table should include columns like `product_id`, `unit_spend`, and `customer_id`.
+    Adds a calculated column `spend_per_customer`.
+    """
+    try:
+        ibis_table = transactions_table.mutate(
+            spend_per_customer=transactions_table.unit_spend / transactions_table.customer_id,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"Failed to fetch or preprocess test data: {e}")
+    else:
+        return ibis_table
+
+
+def test_composite_rank_basic(test_transactions_table):
+    """Test basic CompositeRank functionality with BigQuery data."""
+    rank_cols = [
+        ("unit_spend", "desc"),
+        ("customer_id", "desc"),
+        ("spend_per_customer", "desc"),
+    ]
+    try:
+        result = CompositeRank(
+            df=test_transactions_table,
+            rank_cols=rank_cols,
+            agg_func="mean",
+            ignore_ties=False,
+        )
+        assert result is not None
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"CompositeRank basic test failed: {e}")
+
+
+@pytest.mark.parametrize("ignore_ties", [False, True])
+def test_tie_handling(test_transactions_table, ignore_ties):
+    """Test handling of ties during rank calculation."""
+    rank_cols = [("unit_spend", "desc")]
+    try:
+        result = CompositeRank(
+            df=test_transactions_table,
+            rank_cols=rank_cols,
+            agg_func="mean",
+            ignore_ties=ignore_ties,
+        )
+        assert result is not None
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"CompositeRank failed with ignore_ties={ignore_ties}: {e}")
diff --git a/tests/integration/bigquery/test_cross_shop.py b/tests/integration/bigquery/test_cross_shop.py
new file mode 100644
index 0000000..ef75a3d
--- /dev/null
+++ b/tests/integration/bigquery/test_cross_shop.py
@@ -0,0 +1,49 @@
+"""Integration tests for Cross Shop Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.cross_shop import CrossShop
+
+
+def test_cross_shop_with_bigquery(transactions_table):
+    """Test CrossShop with data fetched from BigQuery.
+
+    This parameterized test verifies that CrossShop can be initialized
+    and run with data from BigQuery using different combinations of group columns,
+    value columns, and aggregation functions without throwing exceptions.
+    """
+    transactions_df = transactions_table.limit(5000)
+    group_1_col = "brand_name"
+    group_2_col = "category_0_name"
+    group_3_col = "category_1_name"
+    group_1_vals = transactions_df[group_1_col].execute().dropna().unique()
+    group_2_vals = transactions_df[group_2_col].execute().dropna().unique()
+
+    group_1_val = group_1_vals[0]
+    group_2_val = group_2_vals[0]
+
+    group_3_val = None
+    if group_3_col is not None:
+        group_3_vals = transactions_df[group_3_col].execute().dropna().unique()
+        if len(group_3_vals) == 0:
+            pytest.skip(f"Not enough unique values for {group_3_col}")
+        group_3_val = group_3_vals[0]
+
+    labels = ["Group 1", "Group 2"] if group_3_col is None else ["Group 1", "Group 2", "Group 3"]
+
+    try:
+        CrossShop(
+            df=transactions_table,
+            group_1_col=group_1_col,
+            group_1_val=group_1_val,
+            group_2_col=group_2_col,
+            group_2_val=group_2_val,
+            group_3_col=group_3_col,
+            group_3_val=group_3_val,
+            labels=labels,
+            value_col="unit_quantity",
+            agg_func="count",
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"CrossShop failed with parameters {group_1_col}, {group_2_col}, {group_3_col}: {e}")
diff --git a/tests/integration/bigquery/test_customer_decision_hierarchy.py b/tests/integration/bigquery/test_customer_decision_hierarchy.py
new file mode 100644
index 0000000..3d828dc
--- /dev/null
+++ b/tests/integration/bigquery/test_customer_decision_hierarchy.py
@@ -0,0 +1,46 @@
+"""Integration tests for Customer Decision Hierarchy Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.customer_decision_hierarchy import CustomerDecisionHierarchy
+from pyretailscience.options import ColumnHelper
+
+cols = ColumnHelper()
+
+
+@pytest.mark.parametrize(
+    ("method", "min_var_explained", "exclude_same_transaction"),
+    [
+        ("truncated_svd", 0.7, False),
+        ("truncated_svd", 0.7, None),
+        ("truncated_svd", None, False),
+        ("yules_q", 0.7, False),
+        ("yules_q", 0.7, None),
+        ("yules_q", None, False),
+        ("yules_q", None, None),
+    ],
+)
+def test_customer_decision_hierarchy_with_bigquery(
+    transactions_table,
+    method,
+    min_var_explained,
+    exclude_same_transaction,
+):
+    """Test CustomerDecisionHierarchy with data fetched from BigQuery.
+
+    This parameterized test verifies that CustomerDecisionHierarchy can be initialized
+    and run with data from BigQuery using different combinations of product columns
+    and methods without throwing exceptions.
+    """
+    transactions_df = transactions_table.limit(5000).execute()
+
+    try:
+        CustomerDecisionHierarchy(
+            df=transactions_df,
+            product_col="product_name",
+            exclude_same_transaction_products=exclude_same_transaction,
+            method=method,
+            min_var_explained=min_var_explained if min_var_explained is not None else 0.8,
+        )
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"CustomerDecisionHierarchy failed with, method={method}: {e}")
diff --git a/tests/integration/bigquery/test_haversine.py b/tests/integration/bigquery/test_haversine.py
new file mode 100644
index 0000000..25c4a77
--- /dev/null
+++ b/tests/integration/bigquery/test_haversine.py
@@ -0,0 +1,21 @@
+"""Integration tests for haversine distance function."""
+
+import ibis
+import pytest
+
+from pyretailscience.analysis.haversine import haversine_distance
+
+
+def test_haversine():
+    """Test the haversine function."""
+    lat1 = ibis.literal(37.7749, type="float64")
+    lon1 = ibis.literal(-122.4194, type="float64")
+    lat2 = ibis.literal(40.7128, type="float64")
+    lon2 = ibis.literal(-74.0060, type="float64")
+
+    distance_expr = haversine_distance(lat1, lon1, lat2, lon2)
+
+    result = distance_expr.execute()
+
+    expected_distance = 4129.086165
+    assert pytest.approx(result, rel=1e-3) == expected_distance, "Distance calculation error"
diff --git a/tests/integration/bigquery/test_hml_segmentation.py b/tests/integration/bigquery/test_hml_segmentation.py
new file mode 100644
index 0000000..c7740a6
--- /dev/null
+++ b/tests/integration/bigquery/test_hml_segmentation.py
@@ -0,0 +1,32 @@
+"""Integration tests for the HMLSegmentation class using BigQuery."""
+
+import pytest
+
+from pyretailscience.segmentation.hml import HMLSegmentation
+
+
+@pytest.mark.parametrize(
+    "zero_value_customers",
+    ["separate_segment", "include_with_light", "exclude"],
+)
+def test_hml_segmentation_with_bigquery(
+    transactions_table,
+    zero_value_customers,
+):
+    """Test HMLSegmentation with data fetched from BigQuery.
+
+    This parameterized test verifies that HMLSegmentation can be initialized
+    and process data from BigQuery using zero-value handling without throwing exceptions.
+    """
+    limited_transactions = transactions_table.limit(5000)
+
+    try:
+        HMLSegmentation(
+            df=limited_transactions,
+            value_col="unit_cost",
+            agg_func="mean",
+            zero_value_customers=zero_value_customers,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"HMLSegmentation failed: {e}")
diff --git a/tests/integration/bigquery/test_product_association.py b/tests/integration/bigquery/test_product_association.py
new file mode 100644
index 0000000..6ae22d1
--- /dev/null
+++ b/tests/integration/bigquery/test_product_association.py
@@ -0,0 +1,39 @@
+"""Integration tests for Product Association Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.product_association import ProductAssociation
+
+
+@pytest.mark.parametrize(
+    "target_item",
+    [None, "Electronics"],
+)
+def test_product_association_with_bigquery(
+    transactions_table,
+    target_item,
+):
+    """Test ProductAssociation with data fetched from BigQuery.
+
+    This parameterized test verifies that ProductAssociation can be initialized
+    and process data from BigQuery using target items without throwing exceptions.
+    """
+    limited_transactions = transactions_table.limit(5000)
+
+    try:
+        ProductAssociation(
+            df=limited_transactions,
+            value_col="brand_name",
+            group_col="transaction_id",
+            target_item=target_item,
+            min_occurrences=5,
+            min_cooccurrences=3,
+            min_support=0.01,
+            min_confidence=0.05,
+            min_uplift=1.0,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(
+            f"ProductAssociation failed with target_item={target_item}: {e}",
+        )
diff --git a/tests/integration/bigquery/test_revenue_tree.py b/tests/integration/bigquery/test_revenue_tree.py
new file mode 100644
index 0000000..8311cd9
--- /dev/null
+++ b/tests/integration/bigquery/test_revenue_tree.py
@@ -0,0 +1,116 @@
+"""Integration tests for Revenue Tree Analysis with BigQuery."""
+
+import pytest
+
+from pyretailscience.analysis.revenue_tree import RevenueTree, calc_tree_kpis
+from pyretailscience.options import ColumnHelper
+
+cols = ColumnHelper()
+
+
+@pytest.mark.parametrize(
+    "group_col",
+    [None, "category_0_name"],
+)
+def test_revenue_tree_with_bigquery(
+    transactions_table,
+    group_col,
+):
+    """Test RevenueTree with data fetched from BigQuery.
+
+    This parameterized test verifies that RevenueTree can be initialized
+    and process data from BigQuery using different group columns
+    without throwing exceptions.
+    """
+    period_col = "transaction_date"
+
+    limited_transactions = transactions_table.limit(10000)
+
+    try:
+        RevenueTree(
+            df=limited_transactions,
+            period_col=period_col,
+            p1_value="2023-05-24",
+            p2_value="2023-04-15",
+            group_col=group_col,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"RevenueTree failed with period_col={period_col}, group_col={group_col}: {e}")
+
+
+def test_calc_tree_kpis_with_bigquery(transactions_table):
+    """Test calc_tree_kpis function with data from BigQuery.
+
+    This test verifies that the calc_tree_kpis function can process data derived
+    from BigQuery without throwing exceptions.
+    """
+    limited_transactions = transactions_table.limit(8000)
+
+    try:
+        df, p1_index, p2_index = RevenueTree._agg_data(
+            df=limited_transactions,
+            period_col="transaction_date",
+            p1_value="2023-05-24",
+            p2_value="2023-04-15",
+            group_col=None,
+        )
+
+        calc_tree_kpis(
+            df=df,
+            p1_index=p1_index,
+            p2_index=p2_index,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"calc_tree_kpis failed: {e}")
+
+
+@pytest.mark.parametrize(
+    "include_qty",
+    [
+        True,
+        False,
+    ],
+)
+def test_revenue_tree_quantity_handling_with_bigquery(
+    transactions_table,
+    include_qty,
+):
+    """Test RevenueTree with and without quantity columns using BigQuery data.
+
+    This test verifies that RevenueTree can process BigQuery data both with and
+    without quantity-related columns without throwing exceptions.
+    """
+    period_col = "transaction_date"
+    limited_transactions = transactions_table.limit(6000)
+
+    try:
+        if include_qty:
+            columns_to_keep = [
+                cols.customer_id,
+                cols.transaction_id,
+                cols.unit_spend,
+                cols.unit_qty,
+                period_col,
+            ]
+        else:
+            columns_to_keep = [
+                cols.customer_id,
+                cols.transaction_id,
+                cols.unit_spend,
+                period_col,
+            ]
+
+        filtered_transactions = limited_transactions.select(columns_to_keep)
+
+        RevenueTree(
+            df=filtered_transactions,
+            period_col=period_col,
+            p1_value="2023-05-24",
+            p2_value="2023-04-15",
+            group_col=None,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"RevenueTree quantity handling test failed with include_qty={include_qty}: {e}")
diff --git a/tests/integration/bigquery/test_rfm_segmentation.py b/tests/integration/bigquery/test_rfm_segmentation.py
new file mode 100644
index 0000000..20ef6df
--- /dev/null
+++ b/tests/integration/bigquery/test_rfm_segmentation.py
@@ -0,0 +1,29 @@
+"""Integration tests for the RFMSegmentation class using BigQuery."""
+
+import datetime
+
+import pytest
+
+from pyretailscience.segmentation.rfm import RFMSegmentation
+
+
+@pytest.mark.parametrize(
+    "current_date",
+    [None, "2023-12-31", datetime.date(2023, 6, 30)],
+)
+def test_rfm_segmentation_with_bigquery(
+    transactions_table,
+    current_date,
+):
+    """Test RFMSegmentation with data fetched from BigQuery.
+
+    This parameterized test verifies that the RFMSegmentation class can be initialized
+    and process data from BigQuery using different current_date parameters without throwing exceptions.
+    """
+    limited_table = transactions_table.limit(5000)
+
+    try:
+        RFMSegmentation(df=limited_table, current_date=current_date)
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(f"RFMSegmentation failed with current_date={current_date}: {e}")
diff --git a/tests/integration/bigquery/test_segstats_segmentation.py b/tests/integration/bigquery/test_segstats_segmentation.py
new file mode 100644
index 0000000..e9db3f0
--- /dev/null
+++ b/tests/integration/bigquery/test_segstats_segmentation.py
@@ -0,0 +1,38 @@
+"""Integration tests for segmentation statistics using BigQuery data."""
+
+import pytest
+
+from pyretailscience.segmentation.segstats import SegTransactionStats
+
+
+@pytest.mark.parametrize(
+    ("calc_total", "extra_aggs"),
+    [
+        (True, None),
+        (False, {"unique_products": ("product_id", "nunique")}),
+    ],
+)
+def test_seg_transaction_stats_with_bigquery(
+    transactions_table,
+    calc_total,
+    extra_aggs,
+):
+    """Test SegTransactionStats with data fetched from BigQuery.
+
+    This test verifies that SegTransactionStats can process data directly from
+    a BigQuery connection using Ibis without throwing exceptions.
+    """
+    try:
+        limited_table = transactions_table.limit(10000)
+
+        SegTransactionStats(
+            data=limited_table,
+            segment_col=["category_0_name", "category_1_name"],
+            calc_total=calc_total,
+            extra_aggs=extra_aggs,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(
+            f"SegTransactionStats failed with calc_total={calc_total}, extra_aggs={extra_aggs}: {e}",
+        )
diff --git a/tests/integration/bigquery/test_threshold_segmentation.py b/tests/integration/bigquery/test_threshold_segmentation.py
new file mode 100644
index 0000000..b5f24c2
--- /dev/null
+++ b/tests/integration/bigquery/test_threshold_segmentation.py
@@ -0,0 +1,39 @@
+"""Tests for the ThresholdSegmentation class with BigQuery integration."""
+
+import pytest
+
+from pyretailscience.options import ColumnHelper
+from pyretailscience.segmentation.threshold import ThresholdSegmentation
+
+cols = ColumnHelper()
+
+
+@pytest.mark.parametrize(
+    "zero_value_handling",
+    ["separate_segment", "exclude", "include_with_light"],
+)
+def test_threshold_segmentation_with_bigquery(
+    transactions_table,
+    zero_value_handling,
+):
+    """Test ThresholdSegmentation with data fetched from BigQuery.
+
+    This test verifies that ThresholdSegmentation can process data directly from
+    a BigQuery connection using Ibis without throwing exceptions.
+    """
+    try:
+        limited_table = transactions_table.limit(1000)
+
+        ThresholdSegmentation(
+            df=limited_table,
+            thresholds=[0.33, 0.66],
+            segments=["Low", "High"],
+            value_col=cols.unit_spend,
+            agg_func="mean",
+            zero_value_customers=zero_value_handling,
+        )
+
+    except Exception as e:  # noqa: BLE001
+        pytest.fail(
+            f"ThresholdSegmentation failed with zero_value_handling={zero_value_handling}: {e}",
+        )
diff --git a/uv.lock b/uv.lock
index 187d485..8cbb41b 100644
--- a/uv.lock
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+version = "1.4.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "packaging" },
+    { name = "pandas" },
+    { name = "pyarrow" },
+]
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 version = "1.8.5"
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+    { name = "grpcio-status" },
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+version = "2.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "oauthlib" },
+    { name = "requests" },
+]
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+wheels = [
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 version = "0.1.4"
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+dependencies = [
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+wheels = [
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