Data Transformation

Turn raw events into meaningful metrics

Turn raw events into meaningful metrics

As processes and toolsets change, simply storing commercial data isn’t enough. Teams need it cleaned, categorised, and turned into insights that can trigger action. Planhat does this transformation inside the platform. Formula fields calculate across fields and records, and Calculated Metrics create live time-series trails. All of this this can be interpreted and categorised with the help of natively available LLMs. The adapted data can then be funnelled to your automations, workflows, and other processes.

01

Dynamic trend analysis

Use calculated metrics to turn imported events and daily changes into rolling ratios and trends - product adoption curves, ticket resolution velocity, revenue development, or any custom trail you need.

02

Rollups across records

Create formula fields to pull and aggregate data from anywhere in the model (e.g. number of open tickets, total value of opportunities, latest support escalation) and surface it on the company or wherever you need it.

03

Normalisation and scoring

Clean, weight, and combine data points (using native LLM categorisation or your own logic) so you can compare apples-to-apples and build scores like churn risk, health, or ICP fit that drive action.

Discover the full power of Data Transformation

Discover the full power of Data Transformation

Discover the full power of Data Transformation

FAQ

FAQ

FAQ

What does Data Transformation actually do with raw data before it reaches Planhat workflows?

How does Data Transformation make automation more reliable at scale?

How does transformation connect a data pattern to an immediate operational response?

How does the transformation layer manage overwhelming data volume in complex environments?

How does Data Transformation contribute to trustworthy AI outputs?