Integration Methods

BetIntel.ai offers multiple integration methods to seamlessly connect with various data sources, ensuring that businesses can efficiently access and analyze their data. These integration methods cater to diverse technical environments and operational needs, providing flexibility for different types of users.

⚠️ Personal identifiable information such as email, name, surname, social security number, mobile number are not within the scope of the integration. Such data cannot be stored Betintel.ai.

Direct Connection Integration

Overview

Direct Connection integration allows BetIntel.ai to connect directly with a company’s data warehouse or database, ensuring data retrieval and processing is conducted directly on your infrastructure without the need to export data to Betintel.ai data storage. This option is generally advisable for medium to large enterprises processing terabytes of data, or organisations with stricter data policies.

Supported Databases

• SQL-based Databases: MySQL, PostgreSQL, Oracle, Microsoft SQL Server and others.
• NoSQL Databases: MongoDB (limited support)
• Cloud Databases: Google BigQuery, Amazon Redshift, Snowflake, Databricks, Azure SQL Database and others.

Custom connectors to data stores not listed above can be created during the integration phase.

Key Benefits

• Retain your data on your infrastructure
• No need for intermediate storage layers
• Secure direct querying with access controls
• Utilise Betintel.ai local cache for increased performance
• Limit parallelism on Betintel.ai to control your data storage costs

Integration Process

1. Database Credentials Setup – The administrator provides secure credentials.
2. Connection Configuration – BetIntel.ai connects to the database via encrypted channels.
3. Schema Mapping – Tables, attributes, data access groups and key metrics are mapped for Natural Language querying.
4. Interpretation Optimisation – Performance tuning ensures the efficient understanding of English Natural Language queries.

Security Considerations

• Encrypted connections (SSL/TLS) for secure communication.
• Brands row-level security (RLS) ensures users only see relevant brand data. By default, Betintel.ai provides a filter feature that enables only brand data pertaining to specific users to be displayed. Enabling RLS is optional.
• Data masking and anonymization must be discussed before integration.

API-Based Integration (pull)

Overview

API-based integration enables BetIntel.ai to fetch data via REST or GraphQL APIs, allowing businesses to leverage existing web services for seamless data extraction. This method of integration is recommended for small-sized organisations or organisations who do not have a data warehouse or database at their disposal.

Supported API Types

• REST APIs (JSON, XML support)
• GraphQL APIs

Key Benefits

• Scheduled and predictable data extraction
• Supports any data formats
• Allows integration with multiple third-party platforms
• Control API hit frequency to control infrastructure performance and costs

Integration Process

1. Access – API keys, documentation and credentials are to be supplied to Beintel.ai.
2. ETL – Data extraction, transformation and loading of data into Betintel.ai data storage (including historical data up to 2 years of data).
3. Scheduling & Automation – Data retrieval API calls for periodic updates.

Security Considerations

• Token-based authentication
• IP whitelisting
• Data encryption during transmission

API-Based Integration (push)

Overview

API-based integration that enables the customer to push data via REST APIs to Betintel.ai. This method of integration is recommended for small-sized organisations or organisations who do not have a data warehouse or database at their disposal and who would prefer to have near real-time data available on Betintel.ai.

Supported API Types

• REST APIs (JSON)

Key Benefits

• Real-time data (if events are pushed in real-time)
• Predefined data structures

Integration Process

1. Access – API keys, documentation and credentials are supplied to the customer.
2. Integration – All APIs are integrated and  historical data (up to 2 years of data) is pushed to Betintel.ai.
3. Scheduling & Automation – Data can be pushed to the API in real-time as events occur, or scheduled in a batch format.

Security Considerations

• API key
• IP whitelisting
• Data encryption during transmission
• Rate limiter and API monitoring

ℹ️ Technical information about API push integration is available in the Resource Centre, accessible only to logged-in BetIntel.ai users.

BetIntel.ai provides robust and flexible integration options, including direct database connections, API-based integrations, and ETL processes. Each method ensures secure and optimized data access, catering to different business needs and operational environments. Choosing the right integration method depends on factors such as data volume, frequency of updates, and security requirements.