Say we have an enterprise with:

• a group of databases that runs the business (i.e. operational data plane)
• a group of analysts to analyze business patterns to boost revenue (i.e. analytical data consumers)

The consumers may analyze directly off from the operational data as depicted below.

The problems with this approach are:

• a consumer need may affect the operational data plane (e.g. An analytical consumer wants to know the number of times each user logged in. This requires adding a column to track the number of logins. This column isn’t needed for business. Additional columns like this will bloat the operational data plane)
• managing private data is difficult

The solution is to introduce a separate data plane solely used for analysis.

The 2 Types of Data

• operational data plane - sits in databases behind business capabilities, has a transactional nature, keeps the current state, and serves the needs of the applications running the business
• analytical data plane - is a temporal and aggregated view of the facts of the business over time, often modeled to provide retrospective or future-perspective insights; it trains the ML models or feeds the analytical reports