Spanner & BigQuery: Real-Time Fraud Defense Shield

1. Introduction

Welcome to the backend of Petverse, a multiplayer online game where players create animal avatars, explore the world, and trade in-game currency.

Recently, the game's economy has been under threat. Huge sums of money are draining from the accounts of wealthy Dog players, converted entirely into premium tuna stocks. We suspect a group of "Robin Hood Cats," stealing from the rich hounds to feed the feline masses.

In this codelab, you will build a real-time fraud defense shield to catch the ringleader and their automated bot ring. You will experience how operational data in Spanner converges with analytics in BigQuery to detect and investigate complex fraud patterns with graph (GQL) and relational queries.

What you'll do

• Detect an anomaly in real-time stream using BigQuery continuous queries and push it to Spanner.
• Investigate the fraud ring using Spanner Graph to trace financial relationships.
• Identify bot accounts using Spanner vector search to find similar profile descriptions.
• Uncover the coordination plot using BigQuery Graph to analyze massive communication logs.

What you'll need

• A Google Cloud Project with Billing Enabled.
• Basic knowledge of SQL, terminal commands, and python.
• You may need a GitHub account (code is hosted on GitHub).

Audience: Intermediate Developers, Data Engineers, and Architects.

Estimated Total Duration: 45 to 60 minutes.

Cost Estimate: The resources created in this codelab should cost less than $5.

2. Before You Begin / Setup

Create or Select a Google Cloud Project

You need a Google Cloud project with billing enabled to use the services required for this lab.

1. In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.
2. Ensure that billing is enabled for your Cloud project. Learn how to verify if billing is enabled.
3. Find your project ID from the Cloud Console home page

Start Cloud Shell

You will use Google Cloud Shell as your execution environment. Cloud Shell comes pre-installed with gcloud, git, and other tools you'll need.

1. Navigate to the Google Cloud Shell.
2. If prompted, click Authorize.
3. Ensure you are working in your project by setting the environment variable in the Cloud Shell terminal:

Replace <YOUR_PROJECT_ID> with your actual project ID. Use Ctrl or Command + v to paste into the terminal.

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

Enable Necessary APIs

Run the following command to enable the APIs for Spanner, BigQuery, and Vertex AI:

gcloud services enable spanner.googleapis.com \
    bigquery.googleapis.com \
    aiplatform.googleapis.com \
    run.googleapis.com

Clone the Repository

Clone the repository containing the application code and sample schemas:

git clone https://github.com/GoogleCloudPlatform/cloud-spanner-samples.git
cd cloud-spanner-samples/spanner-bq-fraud-defense

3. Provision Infrastructure

You will now set up the data warehouse in BigQuery and the operational database in Spanner.

Set up BigQuery Dataset and Connection

BigQuery will analyze the telemetry stream from the game.

Still within the console in Google Cloud Shell, run the following commands to make sure your project ID is still set:

Replace <YOUR_PROJECT_ID> with your actual project ID. Use Ctrl or Command + v to paste into the terminal.

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

1. Create a game_analytics BigQuery dataset:

bq mk -d --location=US game_analytics

2. Create a connection to connect to Storage buckets and (optionally) to Spanner:

bq mk --connection --location=US --project_id=$PROJECT_ID \
    --connection_type=CLOUD_RESOURCE unicorn-connection

3. Create the schemas for GameplayTelemetry, AccountSignals, Players, and ChatLogs tables using the schema file:

bq query --use_legacy_sql=false < bq_schema.sql

Set up Spanner

Google Cloud Spanner will handle operational real-time transactions. For this lab, we will use a cost-effective 100 Processing Units (PUs) instance.

1. Create a Spanner instance:

gcloud spanner instances create game-instance \
    --config=regional-us-central1 \
    --description="Game Instance" \
    --processing-units=100 \
    --edition=ENTERPRISE

2. Create the Spanner database game-db:

gcloud spanner databases create game-db --instance=game-instance

3. Update the Spanner schema with the application tables (Players, Transactions, AccountSignals) and property graph (PlayerNetwork):

gcloud spanner databases ddl update game-db --instance=game-instance --ddl-file=spanner_schema.sql

4. Create the AvatarSearchIndex for our multimodal vector search:

gcloud spanner databases ddl update game-db --instance=game-instance \
    --ddl="CREATE SEARCH INDEX AvatarSearchIndex ON Players(AvatarDescriptionTokens)"

Import Data into BigQuery

1. Import the demo data into BigQuery:

bq load --source_format=AVRO game_analytics.GameplayTelemetry gs://sample-data-and-media/spanner-bq-fraud-heist/GameplayTelemetry
bq load --source_format=AVRO game_analytics.AccountSignals gs://sample-data-and-media/spanner-bq-fraud-heist/AccountSignals
bq load --source_format=AVRO game_analytics.Players gs://sample-data-and-media/spanner-bq-fraud-heist/Players
bq load --source_format=AVRO game_analytics.ChatLogs gs://sample-data-and-media/spanner-bq-fraud-heist/ChatLogs

3. Navigate to the BigQuery Console and explore the data in the game_analytics dataset.

Import Data into Spanner

Navigate to the Spanner Console and explore the data in the game-db database.

Click Spanner Studio and open a New Query (+).

Paste the following INSERT statements into the query editor and click Run:

-- Table: Players
INSERT INTO Players (
  PlayerId,
  Name,
  Species,
  Clan,
  AvatarDescription,
  ProfilePictureUrl,
  CreatedAt
) VALUES
  ('dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 'Pixel', 'Cat', 'CatClan', 'A heroic cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/pixel_profile_booth.png', '2026-03-02T05:11:28.077335+00:00'),
  ('e82df4fb-0b6d-44dc-8609-70b41430af38', 'Rocky_1', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077374+00:00'),
  ('ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', 'Whiskers_2', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077389+00:00'),
  ('f37d558b-fd0a-404c-a193-bc3a8a2edfba', 'Felix_3', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077407+00:00'),
  ('f3687206-405e-43b6-afb0-8ca73eee5dd1', 'Luna_4', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077419+00:00'),
  ('82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 'Luna_5', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077429+00:00'),
  ('755c7aff-e538-4681-9b90-4b870a42ac72', 'Buddy_6', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077439+00:00'),
  ('8a034e84-26b3-4198-8ec9-3749b1f60537', 'Charlie_7', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077462+00:00'),
  ('ca288a07-2bf8-46fa-a121-9bd0d0f44c64', 'Rocky_8', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077474+00:00'),
  ('7b2881f0-289b-4ea4-9c0e-c1748249b70a', 'Bella_9', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077484+00:00'),
  ('153f4022-a4ce-404a-8544-25d004fd34ad', 'Simba_10', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077494+00:00'),
  ('3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', 'Charlie_11', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077507+00:00'),
  ('e37b6dcf-7ccb-47d0-8b9d-0da2fa30ad09', 'Felix_12', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077516+00:00'),
  ('0b395a7b-0673-4348-afd0-7cea9252629f', 'Bella_13', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077527+00:00'),
  ('64921a63-bea6-4a5c-9e49-7a817678c94f', 'Charlie_14', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077537+00:00'),
  ('0d9040df-34a3-4e54-b660-a85e3c60a6fe', 'Felix_15', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077546+00:00'),
  ('188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 'Max_16', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077556+00:00'),
  ('a2eaefc9-dbff-4704-b908-74518d687e17', 'Rocky_17', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/shiba_inu_105.jpg', '2026-03-02T05:11:28.077565+00:00'),
  ('b59d9b9a-a169-43c1-832d-7e7d4acfa19c', 'Felix_18', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077581+00:00'),
  ('7019b91a-d908-4c93-8ed2-d1c60e518630', 'Nala_19', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077595+00:00'),
  ('1a972a71-a530-407a-b3f7-1dd9b2532cec', 'Luna_20', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077604+00:00'),
  ('3bd0489d-3f43-428d-be2d-0434f0e04ed8', 'Luna_21', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077613+00:00'),
  ('28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'Whiskers_22', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077623+00:00'),
  ('87d880d4-c949-40e3-8d76-9307b45d57fe', 'Rocky_23', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077632+00:00'),
  ('b49a4523-83ff-4f59-8fca-54356928a18b', 'Nala_24', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077641+00:00'),
  ('1e049026-1231-4763-bc50-82cb51950fa2', 'Nala_25', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077650+00:00'),
  ('e83caccd-e81e-454a-bf92-9d9a5a509e25', 'Simba_26', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077659+00:00'),
  ('45650b49-9701-4415-92a9-79073243d198', 'Simba_27', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077668+00:00'),
  ('2eb95b36-c9c3-4720-849b-fc240c9434da', 'Bella_28', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/samoyed_97.jpg', '2026-03-02T05:11:28.077677+00:00'),
  ('491943d2-8aa3-4484-9d6d-afcab7ec579a', 'Buddy_29', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077687+00:00'),
  ('004ac8b2-a37d-42c8-aba3-35b204f596f0', 'Max_30', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077697+00:00'),
  ('5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 'Whiskers_31', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077706+00:00'),
  ('4736fc20-1c22-49c2-af87-c35802302507', 'Luna_32', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077715+00:00'),
  ('d98fc7ff-dd92-4723-994c-6267ef951bcc', 'Buddy_33', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077797+00:00'),
  ('3de80488-e1b6-4908-a6ec-9c51f46f43b9', 'Luna_34', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077821+00:00'),
  ('710128e0-4e1d-479c-acbc-497bbc5bc802', 'Bella_35', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/scottish_terrier_108.jpg', '2026-03-02T05:11:28.077836+00:00'),
  ('7e5d416f-f42c-410e-8e2a-19be0cdfc1e5', 'Simba_36', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077850+00:00'),
  ('b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 'Buddy_37', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/scottish_terrier_108.jpg', '2026-03-02T05:11:28.077864+00:00'),
  ('145cc805-810a-4320-864d-ba6b5c6fbc33', 'Max_38', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077884+00:00'),
  ('34fa84c8-3356-4ed6-9ac5-967cd2baabac', 'Whiskers_39', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077894+00:00'),
  ('a50c967b-2e89-448d-be47-4df628c51572', 'Luna_40', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077906+00:00'),
  ('64aeeb22-42db-46bf-85bd-b21b135c9803', 'Simba_41', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077915+00:00'),
  ('dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 'Felix_42', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077924+00:00'),
  ('d9380e8d-8949-4849-af57-7a91a1a2b953', 'Bella_43', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077933+00:00'),
  ('88a425a0-b499-4825-8a16-3d33b85feec9', 'Whiskers_44', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077942+00:00'),
  ('e17ae312-37c6-4a66-9172-2d20d8528033', 'Simba_45', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077958+00:00'),
  ('ae82282e-d380-4500-99e0-2dc4e276c0cf', 'Nala_46', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077967+00:00'),
  ('9ce13d41-dede-4658-a7e4-7bc00372d65c', 'Simba_47', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077976+00:00'),
  ('8db26b5c-2c09-4578-89bf-f9afaf765e36', 'Whiskers_48', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077989+00:00'),
  ('eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', 'Luna_49', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078002+00:00'),
  ('3f064471-24a0-47cd-8927-925cb3e5df7f', 'Felix_50', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078012+00:00'),
  ('ed20f879-2d42-4ba7-8df7-d696c4b6aafd', 'Whiskers_51', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078021+00:00'),
  ('7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'Buddy_52', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.078030+00:00'),
  ('398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'Rocky_53', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.078040+00:00'),
  ('0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'Bella_54', 'Dog', 'DogClan', 'A loyal golden retriever with a happy smile', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078049+00:00'),
  ('0b1e7a03-2922-4d53-8871-290520e6bb76', 'Max_55', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078059+00:00'),
  ('d0ad6342-88fd-443f-82ba-919fc1d652d0', 'Luna_56', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.078068+00:00'),
  ('73e9a7c4-09e6-46d8-a093-b241d7d1d5df', 'Charlie_57', 'Dog', 'DogClan', 'A loyal golden retriever with a happy smile', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078081+00:00'),
  ('55a1207d-a029-48da-a79d-c1f3f6824a37', 'Buddy_58', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078090+00:00'),
  ('61dd4370-bff0-4d09-be31-19f19c4dad5d', 'Max_59', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078099+00:00'),
  ('4e9dfce6-555b-434a-81b6-237c61b9b530', 'Merry_Cat_0', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078112+00:00'),
  ('686337b0-304e-4270-89c3-d015f9039294', 'Merry_Cat_1', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078165+00:00'),
  ('1627bc18-c42e-4599-b5f1-6f3d52669edb', 'Merry_Cat_2', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078212+00:00'),
  ('215b3d04-402a-4ac2-83ed-1edb9a421691', 'Merry_Cat_3', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078258+00:00'),
  ('78d66ff4-0519-4157-9d95-76c2900ba7f9', 'Merry_Cat_4', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078301+00:00'),
  ('822a8aae-57bd-460e-9643-69815990bec8', 'Merry_Cat_5', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078349+00:00'),
  ('9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'Merry_Cat_6', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078390+00:00'),
  ('3910b199-caf7-4822-8346-1ba9bd750c8e', 'Merry_Cat_7', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078427+00:00'),
  ('78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'Merry_Cat_8', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078463+00:00'),
  ('eba84e9d-bd10-466e-8fcd-899c0a868149', 'Merry_Cat_9', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078508+00:00'),
  ('37a1e15c-a38c-4763-a2bd-042741bce012', 'Merry_Cat_10', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078544+00:00'),
  ('c5337857-3b58-4b0c-8814-4585dcbf765f', 'Merry_Cat_11', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078587+00:00');

-- Table: Transactions
INSERT INTO Transactions (
  TransactionId,
  SenderId,
  ReceiverId,
  Amount,
  Timestamp,
  IsSuspicious
) VALUES
  ('83086ce9-1813-40c7-8e60-624662e7dff8', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', '4e9dfce6-555b-434a-81b6-237c61b9b530', 13481, '2026-03-02T05:11:28.078136+00:00', TRUE),
  ('8c8f38a8-424f-4752-b662-78800e04b137', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 7327, '2026-03-02T05:11:28.078145+00:00', TRUE),
  ('e4b88c5e-ad32-4fa7-87d7-7e7e70ab133a', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', '686337b0-304e-4270-89c3-d015f9039294', 11283, '2026-03-02T05:11:28.078182+00:00', TRUE),
  ('8fe11946-c0ef-4b84-a259-11850955a3ea', '686337b0-304e-4270-89c3-d015f9039294', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 8181, '2026-03-02T05:11:28.078191+00:00', TRUE),
  ('c2d024eb-9131-47ce-84c0-3404e5a01db0', '145cc805-810a-4320-864d-ba6b5c6fbc33', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 11086, '2026-03-02T05:11:28.078228+00:00', TRUE),
  ('7a51d50f-63ac-4406-b4df-2d6fd862977f', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 9443, '2026-03-02T05:11:28.078237+00:00', TRUE),
  ('edc980d0-539e-4951-9eaf-4ba98b88b40c', '2eb95b36-c9c3-4720-849b-fc240c9434da', '215b3d04-402a-4ac2-83ed-1edb9a421691', 10438, '2026-03-02T05:11:28.078274+00:00', TRUE),
  ('0e98eb5f-a942-4bb3-931a-1de1bdbb2e03', '215b3d04-402a-4ac2-83ed-1edb9a421691', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 7612, '2026-03-02T05:11:28.078286+00:00', TRUE),
  ('13cf3599-f18a-47a5-8b7d-71f9eda250ab', 'ca288a07-2bf8-46fa-a121-9bd0d0f44c64', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 14301, '2026-03-02T05:11:28.078318+00:00', TRUE),
  ('db7051ef-aa4b-47fa-a54e-54ff03dbabf1', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 10294, '2026-03-02T05:11:28.078330+00:00', TRUE),
  ('9080d8a1-def2-4b95-bc9f-56c25ec9c3ba', 'e82df4fb-0b6d-44dc-8609-70b41430af38', '822a8aae-57bd-460e-9643-69815990bec8', 9613, '2026-03-02T05:11:28.078365+00:00', TRUE),
  ('06593b48-2546-4a52-a078-cf4ddfaed856', '822a8aae-57bd-460e-9643-69815990bec8', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 9787, '2026-03-02T05:11:28.078376+00:00', TRUE),
  ('d540b1d5-5e20-4252-985c-275b82fdad80', '491943d2-8aa3-4484-9d6d-afcab7ec579a', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 11403, '2026-03-02T05:11:28.078406+00:00', TRUE),
  ('6ba654b3-4c04-48ed-9975-1aae3f557a38', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13564, '2026-03-02T05:11:28.078413+00:00', TRUE),
  ('da73004f-a9e6-4078-af54-4dc7a697a0e4', '710128e0-4e1d-479c-acbc-497bbc5bc802', '3910b199-caf7-4822-8346-1ba9bd750c8e', 10088, '2026-03-02T05:11:28.078442+00:00', TRUE),
  ('ac25cfd6-1c64-483a-8b36-5fe4c6c36e36', '3910b199-caf7-4822-8346-1ba9bd750c8e', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 11354, '2026-03-02T05:11:28.078450+00:00', TRUE),
  ('3f09bdb0-5831-44f8-b293-98cbdb953c9d', 'd98fc7ff-dd92-4723-994c-6267ef951bcc', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 12426, '2026-03-02T05:11:28.078479+00:00', TRUE),
  ('65803100-7b84-4ff5-a273-b54fe48d5ad2', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13858, '2026-03-02T05:11:28.078490+00:00', TRUE),
  ('7caeab6c-eb5c-4284-9857-87ab6ba744d1', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 14851, '2026-03-02T05:11:28.078523+00:00', TRUE),
  ('441b31cd-1c7b-4385-a5da-490a6c98d58d', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 12481, '2026-03-02T05:11:28.078530+00:00', TRUE),
  ('ea509bae-75a0-4878-b73c-0688efd2808e', 'd9380e8d-8949-4849-af57-7a91a1a2b953', '37a1e15c-a38c-4763-a2bd-042741bce012', 8042, '2026-03-02T05:11:28.078564+00:00', TRUE),
  ('7ac7d043-2744-4689-835a-20b21dca962b', '37a1e15c-a38c-4763-a2bd-042741bce012', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 11248, '2026-03-02T05:11:28.078572+00:00', TRUE),
  ('1fdfc9a6-af31-4151-a96e-6df93e8fafff', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 11357, '2026-03-02T05:11:28.078603+00:00', TRUE),
  ('3408e82d-61c5-49e1-a037-b8e25422d9ca', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13411, '2026-03-02T05:11:28.078612+00:00', TRUE),
  ('a63fa5df-9d00-44e4-bd00-3d993c737a99', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 312, '2026-03-02T05:11:28.078658+00:00', FALSE),
  ('26b8b704-7b50-4ce5-894f-452741649286', 'e17ae312-37c6-4a66-9172-2d20d8528033', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 52, '2026-03-02T05:11:28.078679+00:00', FALSE),
  ('9d8197de-888c-42ce-8bcf-ef0fe6fccc39', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 65, '2026-03-02T05:11:28.078700+00:00', FALSE),
  ('b0fd1afe-871a-4afc-be00-5c203b147a90', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 292, '2026-03-02T05:11:28.078715+00:00', FALSE),
  ('b7be0c34-2d44-4d48-8cef-ddb74dd11260', 'ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', '45650b49-9701-4415-92a9-79073243d198', 199, '2026-03-02T05:11:28.078730+00:00', FALSE),
  ('0baea611-d24a-43d6-be24-49286f4b80bc', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'e17ae312-37c6-4a66-9172-2d20d8528033', 313, '2026-03-02T05:11:28.078739+00:00', FALSE),
  ('936234c3-3d96-4649-8679-cdc7a35c7c14', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', 306, '2026-03-02T05:11:28.078748+00:00', FALSE),
  ('f29c2881-9ce1-47e3-8934-be21250d807b', '55a1207d-a029-48da-a79d-c1f3f6824a37', '1e049026-1231-4763-bc50-82cb51950fa2', 356, '2026-03-02T05:11:28.078757+00:00', FALSE),
  ('aea90ceb-8669-48b2-ad20-903fa2592cc4', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'ca288a07-2bf8-46fa-a121-9bd0d0f44c64', 320, '2026-03-02T05:11:28.078766+00:00', FALSE),
  ('e5cb67d4-7fb5-4788-b705-e4b156846cf1', '37a1e15c-a38c-4763-a2bd-042741bce012', '45650b49-9701-4415-92a9-79073243d198', 96, '2026-03-02T05:11:28.078780+00:00', FALSE),
  ('1484d14a-4ece-4c60-8760-aca02d8912d3', 'b49a4523-83ff-4f59-8fca-54356928a18b', '4e9dfce6-555b-434a-81b6-237c61b9b530', 286, '2026-03-02T05:11:28.078797+00:00', FALSE),
  ('55bfca86-c16e-4d83-a3be-4a9339b5ca90', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'e82df4fb-0b6d-44dc-8609-70b41430af38', 94, '2026-03-02T05:11:28.078812+00:00', FALSE),
  ('626b175d-7954-4b48-bfc3-47e1759eb62e', '4e9dfce6-555b-434a-81b6-237c61b9b530', '2eb95b36-c9c3-4720-849b-fc240c9434da', 364, '2026-03-02T05:11:28.078826+00:00', FALSE),
  ('657b64cd-eb82-47f7-af15-c485f09e4c6a', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 180, '2026-03-02T05:11:28.078835+00:00', FALSE),
  ('45a3d118-9ada-400f-8007-f90f6573012f', 'f3687206-405e-43b6-afb0-8ca73eee5dd1', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 21, '2026-03-02T05:11:28.078844+00:00', FALSE),
  ('bad0c577-9063-4315-a923-609b55354aec', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 96, '2026-03-02T05:11:28.078852+00:00', FALSE),
  ('f3f3c44c-29e5-4356-bcdb-34fceead7277', '4e9dfce6-555b-434a-81b6-237c61b9b530', '45650b49-9701-4415-92a9-79073243d198', 206, '2026-03-02T05:11:28.078863+00:00', FALSE),
  ('89e9f697-6cfe-4a11-ada1-2846a9a0e815', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 62, '2026-03-02T05:11:28.078878+00:00', FALSE),
  ('2d980b9e-ec93-4d4c-98b1-4f9440489e0e', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'e17ae312-37c6-4a66-9172-2d20d8528033', 379, '2026-03-02T05:11:28.078894+00:00', FALSE),
  ('1eabdf25-5b41-4773-8870-bb3e71ad320a', '0b395a7b-0673-4348-afd0-7cea9252629f', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 10, '2026-03-02T05:11:28.078911+00:00', FALSE),
  ('eeb9524c-5aa7-4c5a-a8b6-b96fea0c0502', '1a972a71-a530-407a-b3f7-1dd9b2532cec', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 200, '2026-03-02T05:11:28.079050+00:00', FALSE),
  ('2c38f9e6-97fe-477f-8ceb-a6e29880c926', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 197, '2026-03-02T05:11:28.079063+00:00', FALSE),
  ('a85ab466-5c6d-4863-b5fd-ec5418a52534', 'a50c967b-2e89-448d-be47-4df628c51572', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 215, '2026-03-02T05:11:28.079079+00:00', FALSE),
  ('b273c634-1b47-492e-9651-d32e54bdcbb8', 'ae82282e-d380-4500-99e0-2dc4e276c0cf', '491943d2-8aa3-4484-9d6d-afcab7ec579a', 298, '2026-03-02T05:11:28.079088+00:00', FALSE),
  ('93956d3c-c44b-4624-87d8-ac139b1310d0', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '2eb95b36-c9c3-4720-849b-fc240c9434da', 495, '2026-03-02T05:11:28.079096+00:00', FALSE),
  ('1d827b0f-710e-4af6-8492-4e8753c11584', '153f4022-a4ce-404a-8544-25d004fd34ad', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 242, '2026-03-02T05:11:28.079107+00:00', FALSE),
  ('226c5063-77e1-4888-90f1-a1f23cfb7461', '004ac8b2-a37d-42c8-aba3-35b204f596f0', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 63, '2026-03-02T05:11:28.079115+00:00', FALSE),
  ('11584808-fc90-4f7f-bbb0-d9b444bf09b9', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 'a50c967b-2e89-448d-be47-4df628c51572', 385, '2026-03-02T05:11:28.079124+00:00', FALSE),
  ('69ac1396-8377-4e44-9257-d14eafdd8c3d', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', '4e9dfce6-555b-434a-81b6-237c61b9b530', 331, '2026-03-02T05:11:28.079133+00:00', FALSE),
  ('c0400153-b737-4c54-8ae3-c6958c481aa5', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'f3687206-405e-43b6-afb0-8ca73eee5dd1', 254, '2026-03-02T05:11:28.079142+00:00', FALSE),
  ('80ca0f0e-6a9d-446a-adeb-16a4388120f4', '755c7aff-e538-4681-9b90-4b870a42ac72', '0b1e7a03-2922-4d53-8871-290520e6bb76', 183, '2026-03-02T05:11:28.079150+00:00', FALSE),
  ('289f79a4-5743-4577-9880-85648f4e4c17', '8db26b5c-2c09-4578-89bf-f9afaf765e36', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 344, '2026-03-02T05:11:28.079159+00:00', FALSE),
  ('fcea8d5f-c180-480d-83eb-45bd0801e1f3', 'a50c967b-2e89-448d-be47-4df628c51572', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 416, '2026-03-02T05:11:28.079167+00:00', FALSE),
  ('a142f26e-c281-44d7-b7f2-e023a2362f56', '8a034e84-26b3-4198-8ec9-3749b1f60537', 'a2eaefc9-dbff-4704-b908-74518d687e17', 168, '2026-03-02T05:11:28.079176+00:00', FALSE),
  ('ad62fcc0-2bb3-430c-9dda-dd309e346f59', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', 18, '2026-03-02T05:11:28.079185+00:00', FALSE),
  ('2ba99e26-8967-4cc0-b024-4545ea3220d9', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 489, '2026-03-02T05:11:28.079194+00:00', FALSE),
  ('7c8c664b-5491-47f2-bd93-c5ad2a263e87', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 175, '2026-03-02T05:11:28.079202+00:00', FALSE),
  ('3e5b5fae-26c5-44ff-97c0-e1b0624e208d', '7019b91a-d908-4c93-8ed2-d1c60e518630', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 272, '2026-03-02T05:11:28.079211+00:00', FALSE),
  ('6995eaea-b5f3-4291-a1e4-68450d25b19b', 'd98fc7ff-dd92-4723-994c-6267ef951bcc', '88a425a0-b499-4825-8a16-3d33b85feec9', 186, '2026-03-02T05:11:28.079219+00:00', FALSE),
  ('9c50c700-e887-4336-b092-d5e37120d304', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 15, '2026-03-02T05:11:28.079232+00:00', FALSE),
  ('9e27bc69-bb96-4392-8e2c-a911db3e9dcb', 'e37b6dcf-7ccb-47d0-8b9d-0da2fa30ad09', 'd9380e8d-8949-4849-af57-7a91a1a2b953', 81, '2026-03-02T05:11:28.079241+00:00', FALSE),
  ('ba31c88c-49ec-4934-bc99-f036aa1e3cb5', '0d9040df-34a3-4e54-b660-a85e3c60a6fe', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', 208, '2026-03-02T05:11:28.079259+00:00', FALSE),
  ('93e0c429-0788-492a-935a-4674a4cf1522', '4736fc20-1c22-49c2-af87-c35802302507', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 244, '2026-03-02T05:11:28.079268+00:00', FALSE),
  ('9f001cbb-a6fb-4192-a0ae-892219b99444', '4736fc20-1c22-49c2-af87-c35802302507', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 239, '2026-03-02T05:11:28.079277+00:00', FALSE),
  ('0ee4d029-3905-49ab-98cb-c7e5ffcd08bc', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', 204, '2026-03-02T05:11:28.079290+00:00', FALSE),
  ('e39956dd-af1f-4cc9-8831-cabbfbf5bec6', '61dd4370-bff0-4d09-be31-19f19c4dad5d', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 129, '2026-03-02T05:11:28.079310+00:00', FALSE),
  ('2404c2d3-4738-40f3-a169-9af84c909a79', '1e049026-1231-4763-bc50-82cb51950fa2', '87d880d4-c949-40e3-8d76-9307b45d57fe', 14, '2026-03-02T05:11:28.079319+00:00', FALSE),
  ('c9ba7281-5b78-4fe2-ad7c-105fafaad0b4', '8db26b5c-2c09-4578-89bf-f9afaf765e36', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 232, '2026-03-02T05:11:28.079327+00:00', FALSE),
  ('b848f820-a6d9-4f2b-b7e1-13ddfd887fe1', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 426, '2026-03-02T05:11:28.079336+00:00', FALSE),
  ('db409655-050a-41e1-be6b-52c9d792deb2', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 448, '2026-03-02T05:11:28.079344+00:00', FALSE),
  ('79811268-69cf-4542-8258-ad795155964c', '73e9a7c4-09e6-46d8-a093-b241d7d1d5df', '4e9dfce6-555b-434a-81b6-237c61b9b530', 244, '2026-03-02T05:11:28.079353+00:00', FALSE),
  ('71b40f64-aef1-4a83-a021-3118c6404475', 'd0ad6342-88fd-443f-82ba-919fc1d652d0', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 223, '2026-03-02T05:11:28.079361+00:00', FALSE),
  ('06b9f40d-2988-446f-9eaf-7222198b7c52', '0b395a7b-0673-4348-afd0-7cea9252629f', '37a1e15c-a38c-4763-a2bd-042741bce012', 290, '2026-03-02T05:11:28.079374+00:00', FALSE),
  ('d3a2bd8f-5796-48bd-82bb-1c94f89b24a4', '0b1e7a03-2922-4d53-8871-290520e6bb76', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 411, '2026-03-02T05:11:28.079385+00:00', FALSE),
  ('1b8d50ce-4083-4b0b-b12d-b94529d200f3', '0b395a7b-0673-4348-afd0-7cea9252629f', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 237, '2026-03-02T05:11:28.079393+00:00', FALSE),
  ('d6ed7dff-b106-42cf-99c7-4f15bf114b79', 'e82df4fb-0b6d-44dc-8609-70b41430af38', '215b3d04-402a-4ac2-83ed-1edb9a421691', 205, '2026-03-02T05:11:28.079402+00:00', FALSE),
  ('de837bd6-5b12-47a3-ac05-c8fa4ac02ca3', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', '73e9a7c4-09e6-46d8-a093-b241d7d1d5df', 251, '2026-03-02T05:11:28.079411+00:00', FALSE),
  ('56080f4e-a404-4340-b119-8f82a1f2d6d0', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', '755c7aff-e538-4681-9b90-4b870a42ac72', 334, '2026-03-02T05:11:28.079419+00:00', FALSE),
  ('db94e731-6ed8-42a4-a62d-2227814c95f7', '78d66ff4-0519-4157-9d95-76c2900ba7f9', '87d880d4-c949-40e3-8d76-9307b45d57fe', 477, '2026-03-02T05:11:28.079428+00:00', FALSE),
  ('cf051085-4625-44aa-bf03-e4529f1324d8', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '34fa84c8-3356-4ed6-9ac5-967cd2baabac', 285, '2026-03-02T05:11:28.079441+00:00', FALSE),
  ('137f933b-40a1-441d-b547-d296bc977244', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '822a8aae-57bd-460e-9643-69815990bec8', 34, '2026-03-02T05:11:28.079449+00:00', FALSE),
  ('164295cd-bb80-4c24-bbfa-29b582aa8e0f', '3f064471-24a0-47cd-8927-925cb3e5df7f', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', 311, '2026-03-02T05:11:28.079458+00:00', FALSE),
  ('2b3a7e6b-7474-439e-b387-baa708683ca8', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', '755c7aff-e538-4681-9b90-4b870a42ac72', 432, '2026-03-02T05:11:28.079466+00:00', FALSE),
  ('fcecd45c-f950-4704-9405-8ff6cc34f3fc', 'ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 368, '2026-03-02T05:11:28.079474+00:00', FALSE),
  ('c2d81a86-0c03-4495-a1e8-702e1754f424', '2eb95b36-c9c3-4720-849b-fc240c9434da', '34fa84c8-3356-4ed6-9ac5-967cd2baabac', 353, '2026-03-02T05:11:28.079483+00:00', FALSE),
  ('462f5078-6df6-4f57-843e-47d0b51bc7ea', '8a034e84-26b3-4198-8ec9-3749b1f60537', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 173, '2026-03-02T05:11:28.079496+00:00', FALSE),
  ('059a2a27-e019-4f5f-8e24-8208898c723f', '4e9dfce6-555b-434a-81b6-237c61b9b530', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 411, '2026-03-02T05:11:28.079507+00:00', FALSE),
  ('8ab52f88-d38c-4c60-b9ca-c2d08a337a33', '64921a63-bea6-4a5c-9e49-7a817678c94f', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 457, '2026-03-02T05:11:28.079516+00:00', FALSE),
  ('117ff05e-21d2-48ab-a3c8-29e61658c822', 'c5337857-3b58-4b0c-8814-4585dcbf765f', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 142, '2026-03-02T05:11:28.079525+00:00', FALSE),
  ('34e5ea80-59b4-4cb0-a8c1-552e2ba6ecc5', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '3910b199-caf7-4822-8346-1ba9bd750c8e', 142, '2026-03-02T05:11:28.079533+00:00', FALSE),
  ('db1cfbb1-8555-492e-b6c9-45f8040c469b', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'ae82282e-d380-4500-99e0-2dc4e276c0cf', 478, '2026-03-02T05:11:28.079542+00:00', FALSE),
  ('370f50b3-e558-447e-bfbe-fe4eca7e9628', '9ce13d41-dede-4658-a7e4-7bc00372d65c', '3910b199-caf7-4822-8346-1ba9bd750c8e', 72, '2026-03-02T05:11:28.079550+00:00', FALSE),
  ('d08c71a3-bfde-4f95-895a-dc6fa810250f', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', '822a8aae-57bd-460e-9643-69815990bec8', 330, '2026-03-02T05:11:28.079558+00:00', FALSE),
  ('81d6bb50-9127-4e2d-acd5-ecaaa797fcb1', '1a972a71-a530-407a-b3f7-1dd9b2532cec', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 149, '2026-03-02T05:11:28.079567+00:00', FALSE),
  ('6ac1ba71-9852-4f0c-97b2-0bb166057ef0', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '2eb95b36-c9c3-4720-849b-fc240c9434da', 479, '2026-03-02T05:11:28.079575+00:00', FALSE),
  ('9125a495-66f2-435b-8eab-8a2557f55820', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 220, '2026-03-02T05:11:28.079670+00:00', FALSE),
  ('e11b19c9-6bf7-45e2-9831-bb42050b7e8e', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', '4e9dfce6-555b-434a-81b6-237c61b9b530', 380, '2026-03-02T05:11:28.079687+00:00', FALSE),
  ('09b6649c-99a3-48c3-864b-9cbd3d57980a', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'ed20f879-2d42-4ba7-8df7-d696c4b6aafd', 317, '2026-03-02T05:11:28.079696+00:00', FALSE),
  ('68940de9-65d3-4afb-b080-0354b5c6b1a5', '153f4022-a4ce-404a-8544-25d004fd34ad', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 284, '2026-03-02T05:11:28.079710+00:00', FALSE),
  ('050b1905-c72a-446d-81f7-087cddb24434', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'e17ae312-37c6-4a66-9172-2d20d8528033', 156, '2026-03-02T05:11:28.079870+00:00', FALSE),
  ('7d1bbcaf-69eb-4acc-855d-3174d659a430', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', '755c7aff-e538-4681-9b90-4b870a42ac72', 210, '2026-03-02T05:11:28.079923+00:00', FALSE),
  ('07fb83e9-5818-4991-aeba-54f65239954e', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 291, '2026-03-02T05:11:28.079938+00:00', FALSE),
  ('a8a3e69b-392d-4d59-a016-183152eda94a', '64aeeb22-42db-46bf-85bd-b21b135c9803', '8a034e84-26b3-4198-8ec9-3749b1f60537', 261, '2026-03-02T05:11:28.079948+00:00', FALSE),
  ('dcdbd81b-9c64-42cb-9960-4f10b13675ac', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'a50c967b-2e89-448d-be47-4df628c51572', 104, '2026-03-02T05:11:28.079958+00:00', FALSE),
  ('df5490e1-cb3f-4109-be18-2aa10a52d848', '491943d2-8aa3-4484-9d6d-afcab7ec579a', '7019b91a-d908-4c93-8ed2-d1c60e518630', 302, '2026-03-02T05:11:28.079967+00:00', FALSE),
  ('801607a9-a4f7-424d-b80f-915094a6f389', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '55a1207d-a029-48da-a79d-c1f3f6824a37', 129, '2026-03-02T05:11:28.079979+00:00', FALSE),
  ('80851b7f-a1b5-4eb5-a54e-2c3c55e9dd2a', 'a50c967b-2e89-448d-be47-4df628c51572', '710128e0-4e1d-479c-acbc-497bbc5bc802', 450, '2026-03-02T05:11:28.079999+00:00', FALSE),
  ('b1b728aa-177f-4b2f-a5ff-0267898ff6b1', '145cc805-810a-4320-864d-ba6b5c6fbc33', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 490, '2026-03-02T05:11:28.080011+00:00', FALSE),
  ('bc2e3265-7349-4ef4-a47d-9cd004d8baa4', 'a50c967b-2e89-448d-be47-4df628c51572', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 82, '2026-03-02T05:11:28.080021+00:00', FALSE),
  ('1b51395e-1dc0-4201-9596-34f3dbac4a14', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '1e049026-1231-4763-bc50-82cb51950fa2', 175, '2026-03-02T05:11:28.080032+00:00', FALSE),
  ('cb319fb3-2707-4712-a042-b58a51d5407a', 'a2eaefc9-dbff-4704-b908-74518d687e17', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 20, '2026-03-02T05:11:28.080041+00:00', FALSE),
  ('5339f7f9-fd7e-4dc5-861b-98121e3fd696', '2eb95b36-c9c3-4720-849b-fc240c9434da', 'd9380e8d-8949-4849-af57-7a91a1a2b953', 339, '2026-03-02T05:11:28.080050+00:00', FALSE),
  ('ae4424b0-27d2-43d3-89d7-a1d8c49f5ee0', '37a1e15c-a38c-4763-a2bd-042741bce012', 'a50c967b-2e89-448d-be47-4df628c51572', 342, '2026-03-02T05:11:28.080059+00:00', FALSE),
  ('92c39e1d-45a3-41c9-9583-cfcaca15c4a3', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'a50c967b-2e89-448d-be47-4df628c51572', 484, '2026-03-02T05:11:28.080067+00:00', FALSE),
  ('a7cf23d8-b178-4a65-ba03-3ece7b259d51', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '4736fc20-1c22-49c2-af87-c35802302507', 400, '2026-03-02T05:11:28.080076+00:00', FALSE),
  ('1a1981a8-b63a-4a73-9b8a-ff517286745d', 'ed20f879-2d42-4ba7-8df7-d696c4b6aafd', '8a034e84-26b3-4198-8ec9-3749b1f60537', 72, '2026-03-02T05:11:28.080087+00:00', FALSE),
  ('473dbb0e-652c-43b3-b571-f88c1af1e8c5', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 146, '2026-03-02T05:11:28.080095+00:00', FALSE),
  ('26ebb626-b5a4-4a23-b411-9428219bc8ae', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', '2eb95b36-c9c3-4720-849b-fc240c9434da', 261, '2026-03-02T05:11:28.080104+00:00', FALSE);

-- Table: AccountSignals
-- This is pushed by BigQuery through a continuous query if it is configured
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('50b64a6a-2e8f-4a0b-9742-c7e180949e82', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078156+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('d2659e80-bce0-46b0-9570-6bb8b3c99d34', '686337b0-304e-4270-89c3-d015f9039294', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078198+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('10504018-b7a4-47a4-89b2-950fa492bbd4', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078244+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('ccbba78a-0f45-49b9-a58b-21777de250cf', '215b3d04-402a-4ac2-83ed-1edb9a421691', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078293+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('affa841d-0f9a-4b0f-ad6d-eb3e180263fe', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078337+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('1fbdd097-b431-4a21-9a5c-a1f53db6d754', '822a8aae-57bd-460e-9643-69815990bec8', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078383+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('0fc87891-dd4b-494b-8c47-f6ccc2c592c7', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078420+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('cc117869-7a6b-4e66-89bf-e3148ac8c6ea', '3910b199-caf7-4822-8346-1ba9bd750c8e', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078456+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('c85a78c6-3cc8-4262-8fd2-2fb9661a1b96', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078499+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('ccdb20f8-cd05-42ae-b942-cb41396ec27d', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078537+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('721511f1-ebc4-45dc-adb5-9dafc5426bc3', '37a1e15c-a38c-4763-a2bd-042741bce012', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078579+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('4d8b0f0d-211a-4537-8c79-c2fd815812f3', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078627+00:00');

This may take a few minutes to run. You should be able to preview data after it is completed.

4. The Watchdog (BigQuery Continuous Queries & Spanner Sync)

Our first line of defense is the telemetry data streaming into BigQuery. We want to monitor for suspicious movements (e.g., impossible distances) and push an alert back to Spanner in real-time.

In a real-world scenario, you would use BigQuery continuous queries and reverse ETL to stream this data. However, this requires a reservation with ENTERPRISE edition or higher.

This is what the command would look like if the reservation was available. You do not need to copy this into the console if you have not set up reservations:

EXPORT DATA
  OPTIONS (
    uri = 'https://spanner.googleapis.com/projects/<YOUR_PROJECT_ID>/instances/game-instance/databases/game-db',
    format='CLOUD_SPANNER',
    spanner_options="""{ "table": "AccountSignals" }"""
  ) AS
SELECT
  GENERATE_UUID() as SignalId,
  PlayerId,
  'SUSPICIOUS_MOVEMENT' as AlertType,
  CURRENT_TIMESTAMP() as EventTime
FROM `game_analytics.GameplayTelemetry`
WHERE
  EventType = 'player_move'
  AND (LocationX > 1000 OR LocationY > 1000);

To create the continuous query, you would click on More > Create continuous query in the BigQuery Console SQL Workspace.

This query acts as a reverse-ETL engine, ensuring our transactional system (Spanner) is instantly aware of anomalies detected in our analytical system (BigQuery).

For this lab, we artificially inserted some transactions into Spanner.

5. The Multimodal Detective (Spanner Graph & Vector Search)

Now that Spanner has the "High Risk" signal, you can investigate the fraud ring. We will use Spanner Graph to visualize the financial web and find the ringleader.

Run these queries in Spanner Studio

Graph: Find the Ringleader

This query traces the financial web of transactions where victims transfer to a thief, who then transfers to a boss node. It groups by the boss and sums the loot.

Copy it into Spanner Studio and click on Run.

GRAPH PlayerNetwork
MATCH (victim)-[:Transfers]->(thief)-[t:Transfers]->(boss)
RETURN
  boss.Name AS RingLeader, COUNT(t) AS TributesReceived,
  SUM(t.Amount) AS TotalLoot
GROUP BY RingLeader
ORDER BY TotalLoot DESC
LIMIT 5;

You should see "Pixel" as the top recipient of tributes.

Multi-signal Investigation

Let's join the Graph results with the real-time behavioral signals we pushed from BigQuery earlier. We want to find players who are sending money to "Pixel" AND have been flagged for suspicious movement.

SELECT DISTINCT
  p.Name,
  s.AlertType as BQ_Signal,
  s.EventTime as SignalTime
FROM GRAPH_TABLE (
  PlayerNetwork
  MATCH (associate:Players)-[:Transfers]->(boss:Players)
  WHERE boss.Name = 'Pixel'
  RETURN DISTINCT associate.Name
) as g
JOIN Players p
  ON p.Name = g.Name
JOIN AccountSignals s
  ON p.PlayerId = s.PlayerId
ORDER BY s.EventTime DESC;

Vector search: Identify Bot Accounts

Are these real players or a coordinated bot ring? Use vector search to identify accounts with profile descriptions suspiciously similar to "Pixel's".

SELECT
  Name, AvatarDescription,
  COSINE_DISTANCE(AvatarEmbedding, (SELECT AvatarEmbedding FROM Players WHERE Name = 'Pixel')) as Similarity
FROM Players
WHERE Name != 'Pixel'
ORDER BY Similarity ASC
LIMIT 5;

Lower similarity score means they are closer to "Pixel's" vector. If they have similar descriptions, they are likely bots!

We can also apply scalar functions in the MATCH clause:

GRAPH PlayerNetwork
MATCH (associate:Players)-[:Transfers]->(boss:Players)
WHERE boss.Name = 'Pixel'
ORDER BY (
  COSINE_DISTANCE(associate.AvatarEmbedding, (SELECT AvatarEmbedding FROM Players WHERE Name = 'Pixel'))
) ASC
RETURN DISTINCT associate.Name

6. Uncovering the Plot (BigQuery Property Graph & GCS Integration)

We've caught the ringleader, but we need to understand how they coordinated this massive "tuna heist." We will trace the communication patterns in BigQuery using BigQuery Property Graph to query game chat logs.

Run the following query in BigQuery Studio:

BigQuery Property Graph

Tracing communication between "Pixel" and other players:

GRAPH game_analytics.CatChatNetwork
MATCH (p1:Players)-[c:Communicates]->(p2:Players)
WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
RETURN
  p1.Name AS Sender,
  p2.Name AS Receiver,
  c.Message,
  -- Resolving structured metadata from ObjectRef
  p1.ProfilePictureUrl.uri AS SenderProfilePic
ORDER BY Message DESC;

Observe messages like "Operation Fishbowl is a go" and "Diverting funds to the central tuna reserve." You can see how BigQuery Property Graphs allow you to analyze communications enriched with unstructured data (GCS Image references using ProfilePictureUrl.uri).

If you follow the GCS link in the results, you will see the image of the player:

This analytical query further compares the chat patterns and pictures between the members of the fraud ring.

Before you can run this, declare a multimodal model to generate embeddings of the profile pictures stored in the Cloud Storage bucket. This model connects through the connection created in the initial setup, so you will also grant Vertex AI user permissions to the technical user attached for that connection.

Replace the «PROJECT_ID» with your project ID.

GRANT `roles/aiplatform.user`
ON PROJECT `<<PROJECT_ID>>`
TO "connection:<<PROJECT_ID>>.us.unicorn-connection";

You can now create the connection.

CREATE OR REPLACE MODEL `game_analytics.multimodal_model`
  REMOTE WITH CONNECTION `us.unicorn-connection`
  OPTIONS (ENDPOINT = 'multimodalembedding@001');

If this fails due to a permission error (i.e.,"The [e-mail] does not have the permission to access or use the endpoint..."), wait a few minutes until the permissions propagate and try again.

The query below uses the AI.GENERATE_EMBEDDING function to go through the pictures in the storage bucket and create embeddings. These embeddings are then compared using a COSINE_DISTANCE, so we get a good unerstanding of how similar the chat logs and profile pictures are.

-- BigQuery Property Graph: Tracing communication patterns in chat logs
-- AND calculating distance between auto-embedded chat message and profile picture
-- BigQuery Property Graph: Tracing communication patterns
-- AND identifying similarity AMONG the fraudsters themselves
WITH GraphResults AS (
  SELECT *
  FROM GRAPH_TABLE(
  game_analytics.CatChatNetwork
    MATCH (p1:Players)-[c:Communicates]->(p2:Players)
    WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
    RETURN
      p1.Name AS Sender,
      c.Message,
      p1.ProfilePictureUrl.uri AS SenderProfilePic,
      c.MessageEmbedding.result AS MessageEmbedding
  )
),
UniquePics AS (
  SELECT DISTINCT SenderProfilePic AS uri FROM GraphResults
),
PicEmbeddings AS (
  SELECT embedding, uri
  FROM AI.GENERATE_EMBEDDING(
    MODEL game_analytics.multimodal_model,
    (
      SELECT OBJ.MAKE_REF(uri, 'us.unicorn-connection') as content, uri
      FROM UniquePics
    )
  )
),
CatData AS (
  -- Distinct list of players (excluding Pixel) with their embeddings and HTTPS Pic URLs
  SELECT DISTINCT
    g.Sender,
    g.MessageEmbedding,
    g.Message,
    p.embedding AS PicEmbedding,
    REPLACE( g.SenderProfilePic, 'gs://sample-data-and-media/spanner-bq-fraud-heist/profile_pics/', 'https://storage.mtls.cloud.google.com/sample-data-and-media/spanner-bq-fraud-heist/profile_pics/') AS SenderProfilePic
  FROM GraphResults g
  LEFT JOIN PicEmbeddings p ON g.SenderProfilePic = p.uri
  WHERE g.Sender != 'Pixel'
    AND g.MessageEmbedding IS NOT NULL
    AND p.embedding IS NOT NULL
)
SELECT
  c1.Sender AS Fraudster_A,
  c2.Sender AS Fraudster_B,
  c1.SenderProfilePic AS Pic_A,
  c2.SenderProfilePic AS Pic_B,
  c1.Message,
  -- Compare chat messages between Fraudster A and B
  COSINE_DISTANCE(c1.MessageEmbedding, c2.MessageEmbedding) AS MessageDistance,
  -- Compare profile pictures between Fraudster A and B
  COSINE_DISTANCE(c1.PicEmbedding, c2.PicEmbedding) AS PictureDistance
FROM CatData c1
CROSS JOIN CatData c2
WHERE c1.Sender < c2.Sender -- Avoid self-comparison and duplicate pairs (A-B and B-A)
  AND c1.SenderProfilePic <> c2.SenderProfilePic
ORDER BY PictureDistance ASC, MessageDistance ASC
LIMIT 10;

If you open the profile pictures, you will notice the similarity in how the clan members present themselves.

Visualize the fraud ring

You can use notebooks and Python Cell Magic to visualize the fraud ring. This allows us to easily visualize the graph results. For more information about this, refer to the documentation for visualisation.

In BigQuery Studio, click on More > Notebook > Empty Notebook.

🗒️ If using notebooks for the first time, you will be asked for a region. We have been using US in this lab, so you should pick a region within the US multi-region. You may also need to enable the Notebooks API.

Paste the following into a code cell:

!pip install bigquery-magics==0.12.1

Use the + Code button to create a new cell and paste the following:

%%bigquery --graph
GRAPH game_analytics.CatChatNetwork
MATCH p=(p1:Players)-[c:Communicates]-(p2:Players)
WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
RETURN TO_JSON(p) AS full_path

Click Run all. After about a minute, you should see a graph visualization of the communication network.

7. Clean Up

To avoid incurring charges to your Google Cloud account for the resources used in this codelab, delete the resources you created.

Delete the Spanner Instance

gcloud spanner instances delete game-instance

Delete the BigQuery Dataset

bq rm -r -f -d game_analytics

Alternatively, Delete the Project

If you created a new project for this lab, you can delete the entire project:

gcloud projects delete <YOUR_PROJECT_ID>

8. Congratulations!

Congratulations! You have successfully built a real-time fraud defense shield using Spanner and BigQuery.

You learned how to:

• Use BigQuery continuous queries to push real time insights to Spanner.
• Use Spanner Graph to trace financial relationships.
• Use Spanner vector search for similarity queries on unstructured data.
• Use BigQuery Graph to trace communication networks.

What's next?

• Explore Spanner Graph documentation.
• Find more code examples in the Spanner Graph GitHub repository.
• Learn more about BigQuery Graph.
• Check out BigQuery continuous queries.