Data Platform IntegrationsConnect with your data warehouses and analytics platforms
Comprehensive integration guides for Snowflake, BigQuery, Databricks, and other popular data platforms.
Data Platforms
Overview
Configuration and examples
Data Platform Integration Benefits
- ✓Seamlessly connect your data warehouses and analytics platforms
- ✓Real-time data processing and AI-powered insights
- ✓Support for Snowflake, BigQuery, Databricks, and more
- ✓Enterprise-grade security and compliance
Quick Setup
Get started in minutes with our pre-built connectors and configuration wizards.
Scalable Architecture
Built to handle enterprise-scale data volumes with automatic scaling and optimization.
Snowflake
Configuration and examples
Snowflake Integration
Connect Litends AI directly to your Snowflake data warehouse for real-time analytics and ML predictions.
Configuration Example
import litends
# Configure Snowflake connection
snowflake_config = {
"account": "your-account.snowflakecomputing.com",
"user": "your-username",
"password": "your-password",
"warehouse": "COMPUTE_WH",
"database": "YOUR_DB",
"schema": "PUBLIC"
}
# Initialize connection
client = litends.DataPlatformClient("snowflake", snowflake_config)
# Run ML predictions on your data
results = client.predict(
table="customer_data",
model="churn_prediction",
features=["age", "spending", "last_login"]
)BigQuery
Configuration and examples
Google BigQuery Integration
Leverage Google Cloud's BigQuery for scalable data analytics with Litends AI capabilities.
Setup Instructions
import litends
from google.oauth2 import service_account
# Configure BigQuery connection
credentials = service_account.Credentials.from_service_account_file(
"path/to/service-account-key.json"
)
bigquery_config = {
"project_id": "your-project-id",
"credentials": credentials,
"location": "US"
}
# Initialize connection
client = litends.DataPlatformClient("bigquery", bigquery_config)
# Execute ML queries
query = """
SELECT *
FROM ML.PREDICT(MODEL `your-project.dataset.model`,
(SELECT * FROM `your-project.dataset.input_table`))
"""
results = client.query(query)Databricks
Configuration and examples
Databricks Integration
Connect to Databricks for unified analytics and machine learning workflows.
Connection Setup
import litends
# Configure Databricks connection
databricks_config = {
"server_hostname": "your-workspace.cloud.databricks.com",
"http_path": "/sql/1.0/warehouses/your-warehouse-id",
"access_token": "your-access-token"
}
# Initialize connection
client = litends.DataPlatformClient("databricks", databricks_config)
# Run distributed ML workloads
results = client.spark_ml_pipeline(
input_table="delta.customer_features",
pipeline_stages=[
"vector_assembler",
"random_forest_classifier"
],
output_table="delta.predictions"
)Ready to connect your data platform?
Start integrating your data warehouse or analytics platform with Litends AI for powerful insights and ML capabilities.