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Data & Analytics

Remizen + Databricks Integration

Bring expense data into broader analysis through established data pipelines and governance.

This describes a possible workflow, not an active or official connection.

Connect Remizen with Databricks

Databricks is used for reporting and analysis. Explore spend analysis within data engineering and analytics workflows. Any connection would need to be designed, validated, and made available before teams could use it.

Expense management with Databricks

For organizations that use Databricks, a potential workflow could focus on making reviewed spending easier to analyze alongside other business data. The right approach depends on the records available, your internal policies, and how your team reviews spending today.

How it works

  • Scope a proposed Databricks use case with the people who review spending: Consider expense data in analytical pipelines.
  • Plan how to analyze spend with other curated datasets using the relevant metric definitions, access controls, refresh schedules, and data quality, and decide who would own each handoff.
  • Before implementation, validate the proposed process to review governance for financial data processing against your approval policies.

Workflows

  • Consider expense data in analytical pipelines
  • Analyze spend with other curated datasets
  • Review governance for financial data processing

Data and workflow considerations

  • Review metric definitions, access controls, refresh schedules, and data quality before defining a Databricks workflow.
  • Determine whether Databricks data needed for making reviewed spending easier to analyze alongside other business data may be shared, and how long it should be retained.
  • Test exceptions and manual review paths before relying on any proposed connection.