Sources
Collect incidents and service requests
Product / Case Study
Service Ops Data Platform
From raw incident signals to clear operational decisions — local-first, modular and analytically reliable.
STATUSCore platform implemented · Extensions in review
Service teams see tickets but often miss the causes behind volume, backlog, SLA risk and resolution times. The platform turns operational events into consistent data models and decision-ready metrics.
01
What we built
Ingests incidents and service requests into a structured data foundation
Transforms raw records into tested analytics marts
Makes SLA risk, backlog, categories, teams and channels measurable
Runs locally and can extend into cloud analytics
02
Why it is hard
Separates raw storage, transformation and analytics cleanly
Automated data quality and CI protect metrics from silent errors
Architecture can grow from PostgreSQL to Snowflake or Databricks
03
How it works
Ingest
Load and validate operational records
Raw store
Keep an auditable raw-data layer
Transform
Apply tested business logic
Analytics marts
Build decision-ready data models
Decision layer
Surface SLA, backlog and risk signals
04
Where it applies
IT service management and operations analytics
SLA and backlog control
Modernising fragmented reporting estates
PythonPostgreSQLdbtDockerGitHub ActionsSnowflakeDatabricksPower BI
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