DATA ANALYSIS & BI_
Focus your reporting and analytics layer — not chart soup
Parallaxis data analysis and BI turns trusted data into decisions operators can defend: frame → define → model → narrate → act. Dashboards and insight packs with shared definitions, visible caveats, and owners — so the room stops arguing about which number is true.
Every engagement builds a reporting and analytics layer: Frame → Define → Model → Narrate → Act. Tap the stages on the right.
Analytics layer_
Trusted data becomes decisions operators can defend. Tap a stage — frame through act.
Frame_
Stage 01 / 05
Name the decision question
Lock the question leaders actually ask — before anyone opens a blank dashboard.
- Questions
- Owners
Full lens_
- 01 Frame
- 02 Define
- 03 Model
- 04 Narrate
- 05 Act
Defined metrics + narratives — not chart soup
- 01Frame questionsDecisions leaders actually ask
- 02Define metricsShared grain and exclusions
- 03Model & narrateViews with caveats visible
- 04Act & hand offOwners and follow-up cadence
02 · SLIDEWARE VS ANALYTICS LAYER_
Same questions. Two very different packs.
Toggle Dashboard slideware vs the analytics layer — watch where decisions die or complete.
Same constraint_
“The board wants last week’s numbers by Monday — and every team charts a different revenue.”
Toggle path — layer morphs_
Path nodes_
Open BI tool, invent charts
In focus_
Copy last quarter’s pack
In focus_
Published metric definitions
Never reached_
Caveats on every view
Never reached_
Decision owners + cadence
Stops here_
Outcome_
Chart soup
Pretty tiles, undefined metrics, and debates about which number is true. No decision sticks.
03 · METRIC CONFIDENCE_
Confidence dies when definitions are hoped
Toggle metric pressures — confidence score and outcome update live.
Metric pressures_· Toggle what blurs the lens
Confidence score_
54/100
2 pressures active_
Outcome_
Fragile pack
Some clarity exists, but vanity metrics or stale refresh still derail the room.
04 · QUESTION PROBE_
Probe the question before you chart it
Tap a decision question — see metrics, grain, caveats, and how the answer is used.
Decision questions_· Tap to probe
Are we on track for revenue?_
Board pack: booked vs target this month.
Metrics_
- Booked revenue
- Pipeline weighted
- Target gap
Grain_
Month · company · currency local
Caveats_
Excludes one-time professional services unless finance toggles them on.
Decision use_
Hold / accelerate hiring; reforecast by Friday.
05 · INSIGHT HANDOFF_
What a data analysis and BI engagement leaves behind
Open a chapter — frame through act. Vocabulary the owning team runs next.
Insight pack chapters_
5 chapters- Question inventory and owners
- Non-goals (vanity packs cut)
- Cadence for each decision
In scope_
- Reporting and analytics layer: frame → define → model → narrate → act
- Dashboards and insight packs on trusted data
- Ops handoff so definitions and owners stay clear
Out of scope_
- Warehouse transforms and freshness pipelines (see Data Engineering)
- System-to-system data sync layers (see Data Integration)
- Product squads without an insight constraint (see Product Engineering)
FIT_
Is Data Analysis & BI the right next step?
Self-qualify — we work best when decisions need shared definitions on trusted data.
Good fit_
- Leaders ask recurring questions and disagree on which number is true
- You have (or are building) trusted data — and need packs people will act on
- Someone can own definitions and cadence after handoff
Not yet_
- Systems do not sync yet (see Data Integration) or the warehouse is not trusted (see Data Engineering)
- You are still choosing what to measure with no decision owners (start with Landscape Sketch)
- You only want product features shipped by a squad (see Product Engineering)
NEXT STEP_
Ready to build a reporting and analytics layer for your decisions?
Map your systems — or talk through the pack that keeps sparking debates. We will confirm questions, definitions, data readiness, and whether engineering or integration should land first.
Common questions
Our data analysis and BI engagements run frame → define → model → narrate → act. We ship dashboards and insight packs with shared definitions, visible caveats, and owners — not chart soup.