Augmented analytics
Augmented analytics applies AI to automate data preparation, insight discovery and explanation — shifting analysts from building queries to validating and interpreting.
Definition
Augmented analytics is the use of AI and machine learning to automate parts of the analytics workflow — data preparation, insight discovery, visualisation choice and narrative explanation — so that people spend their time on interpretation rather than on assembly. Conversational BI is the interface layer of the same idea: asking questions in plain language.
Why it matters
- The dashboard backlog is a structural problem: demand for answers grows faster than the team that builds them.
- Explainability has become the deciding factor — an insight nobody can justify is not usable in a regulated decision.
- Automation without governance simply produces wrong answers faster.
How BlueHomer implements it
BlueHomer drafts analytics from governed data: it samples what you have, proposes dashboards, KPI scorecards and insight views, and learns presentation preferences over time — while publication runs through a formal approval trail and every artifact carries its lineage.