Getting Started with BrainPredict Data

Get up and running with BrainPredict Data in just 10 minutes. This guide covers account setup, API integration, and your first AI-powered data quality assessment.

Step 1: Create Your Account

Starter (): 1-10 licenses, all 29 AI models, 100% of features, Intelligence Bus integration
Professional (): 11-25 licenses, all 29 AI models, 100% of features, Intelligence Bus integration
Enterprise (): 26-50 licenses, all 29 AI models, 100% of features, Intelligence Bus integration
Custom (51+ licenses): Contact sales for custom pricing, volume discounts, dedicated account manager

All plans include a Custom quote for your specific needs. Payment method required (credit card, SEPA, or bank transfer).

Step 2: Get Your API Key

Navigate to Portal → Settings → API Keys and generate a new key:

# Your API key will look like this:
bp_data_live_1234567890abcdef1234567890abcdef

# Keep it secure - never commit to version control!

Step 3: Install SDK

Install the BrainPredict Data SDK in your preferred language:

# Python
pip install brainpredict-data

# Node.js
npm install @brainpredict/data

# Java
mvn install brainpredict-data

# PHP
composer require brainpredict/data

Step 4: Make Your First API Call

Let's assess data quality using the Data Quality Scorer AI model:

# Python
from brainpredict import DataClient

client = DataClient(api_key="bp_data_live_xxx")

# Assess data quality
assessment = client.data_quality_scorer.assess({
    "dataset_id": "clients_table",
    "columns": ["email", "phone", "address", "created_at"],
    "row_count": 150000,
    "sample_data": [
        {"email": "john@example.com", "phone": "+1234567890", "address": "123 Main St", "created_at": "2024-01-15"},
        {"email": "invalid-email", "phone": "123", "address": "", "created_at": "2024-02-20"}
    ]
})

print(f"Overall quality score: {assessment['quality_score']}%")
print(f"Issues found: {assessment['issues_count']}")
print(f"Recommendations: {assessment['recommendations']}")

Response:

{
  "quality_score": 72.5,
  "confidence": 96.8,
  "issues_count": 3,
  "issues": [
    {"type": "invalid_email", "count": 1250, "severity": "high"},
    {"type": "missing_address", "count": 3400, "severity": "medium"},
    {"type": "invalid_phone", "count": 890, "severity": "medium"}
  ],
  "recommendations": [
    "Apply email validation rules",
    "Implement address enrichment",
    "Standardize phone number format"
  ],
  "estimated_fix_time": "2-3 hours"
}

Step 5: Connect Your Data Platform

Integrate with your data platform for automatic data sync:

# Snowflake Integration
client.integrations.connect_snowflake({
    "account": "your-account.snowflakecomputing.com",
    "username": "your-username",
    "password": "your-password",
    "warehouse": "COMPUTE_WH",
    "database": "PROD_DB"
})

# Databricks Integration
client.integrations.connect_databricks({
    "workspace_url": "https://your-workspace.databricks.com",
    "access_token": "dapi_xxx",
    "cluster_id": "cluster-xxx"
})

# Informatica PowerCenter Integration
client.integrations.connect_informatica({
    "server_url": "https://your-informatica-server.com",
    "username": "your-username",
    "password": "your-password",
    "domain": "your-domain"
})

Supported integrations: Informatica PowerCenter, Talend Data Integration, Apache NiFi, Microsoft SSIS, IBM DataStage, Oracle Data Integrator, Pentaho, Fivetran, Snowflake, Databricks, AWS Glue, Azure Data Factory, Google Cloud Dataflow, Apache Spark, dbt, Airflow, Prefect, Collibra, Alation, and more.

DataQualityAI (94.5% accuracy)

Analytics Setup Recommendations

For optimal data collection and analysis, implement these tracking enhancements:

Google AnalyticsBasic setup

→ Enhanced e-commerce, event tracking

CRMNone

→ Implement HubSpot/Pipedrive

Marketing AutomationBasic

→ Full funnel tracking

Product AnalyticsNone

→ Implement Mixpanel/Amplitude

Support TicketingBasic

→ Integrate with CRM

Step 6: Run Data Volume Assessment (Optional)

Before subscribing, download our free Data Volume Assessor tool to determine the right pricing tier:

# Download the tool
wget https://brainpredict.ai/downloads/data_volume_assessor.py

# Run assessment (100% privacy-preserving - no data leaves your premises)
python3 data_volume_assessor.py --database postgres --host localhost --port 5432

# Output:
# Total Records: 2.4M
# Total Tables: 45
# Recommended Tier: Professional (1-5M records)
# Estimated Monthly Cost:

The tool analyzes your database size locally and recommends the optimal pricing tier. Zero data transmission - all analysis happens on your premises.