Arbutus Data Connectors

What Arbutus Data Connectors do

Arbutus Data Connectors provide access from the Arbutus Analytics platform to a wide range of enterprise systems, databases, and cloud-based data sources.

These connectors are not a separate standalone application. They are included within Arbutus Analyzer and Arbutus Hub, and are used whenever organisations need to connect Arbutus to specific source systems.

This allows users to work directly with data held in operational systems, databases, and other structured sources, without relying on manual exports or unnecessary intermediate steps.

How Arbutus Data Connectors are used

Arbutus Data Connectors are used when organisations need to access data from systems such as ERP platforms, relational databases, cloud applications, or other business systems.

Typical use cases include:

• Accessing source data for audit and assurance testing
• Connecting to enterprise systems such as SAP or SQL Server
• Bringing together data from multiple platforms for analysis
• Supporting scheduled data access through Arbutus Hub
• Reducing reliance on manual exports and file preparation

Because the connectors are available within Analyzer and Hub, they allow organisations to use the same analytical approach across a wide variety of source systems.

What this looks like

In practice, users select the relevant connector for the system they need to access, configure the connection, and then use the resulting data within Arbutus Analyzer or Arbutus Hub.

From a technical perspective, these connectors operate as ODBC-compatible drivers installed within the environment, allowing Arbutus to access external data sources in a consistent way while the connector handles the specifics of the underlying system.

This means that source data can be queried, filtered, joined, and analysed within the broader Arbutus environment, while still remaining under the organisation’s own control and security model.

Depending on the source system and use case, access may be used interactively for analysis or as part of recurring and scheduled routines.

Included within the Arbutus platform

Arbutus Data Connectors are included as part of the core Arbutus environment and are used through:

• Arbutus Analyzer, for direct access and analysis of source data
• Arbutus Hub, for sharing resources, scheduling procedures and managing analytics centrally

This means organisations do not need to treat them as a separate platform component. Their relevance depends on whether access to a particular source system is required.

Supported source systems

Arbutus Data Connectors support a wide range of systems and data platforms, including examples such as:

• SAP and SAP HANA
• SQL Server, Oracle, PostgreSQL, and MySQL
• Salesforce, Workday, and NetSuite
• Snowflake, Databricks, and Google BigQuery
• SharePoint, JIRA, and REST APIs

The list of supported connectors continues to evolve over time. A more complete and up-to-date overview of available connectors and configuration options can be found on the Arbutus website or in the product documentation.

Who uses Arbutus Data Connectors

Arbutus Data Connectors are commonly used by:

• Internal audit and compliance teams needing direct access to source data
• Fraud investigators working across multiple systems
• Data analysts combining information from different platforms
• Organisations seeking more consistent and repeatable access to operational data

They are particularly valuable where reliable access to source data is essential for testing, monitoring, or repeatable analysis.

A guided evaluation approach is available to assess how Arbutus Analytics can be applied in your environment.

→ Learn more about evaluation

How Sepia Solutions can help

Sepia Solutions supports organisations in using Arbutus Data Connectors through services such as:

• Installation and configuration
• Training
• Workshops
• Coaching
• Consultancy
• Automation and development
• Ongoing support

This may include helping organisations determine which connectors are relevant, configure access to source systems, and integrate connected data into broader analytical procedures.