A 30/60/90 day plan structures a data or AI leader's first quarter into three phases: foundation (days 0–30), build (days 31–60), and intelligence (days 61–90). Ours goes further — every deliverable is mapped to five architecture pillars and tracked in a single live master file, so you always know what shipped, what's next, and where the architecture stands. No Jira, no Confluence, just weekly clarity.
Below is a sample 30-day delivery plan — the same structure we run for every client. Each of our five architecture pillars carries its own set of deliverables for the 30, 60 and 90-day phases, and the developers simply update them as they go. The result is an agile, lean engagement where the artefacts are the status report.
Notion and Figma artefacts for every client, phase and pillar live in one master file you can open any time — no tool-hopping.
Weekly stand-up snapshots replace ticket admin. The deliverables update in place, so progress is always current.
We use AI to keep implementation agile, lean and efficient — getting you to reliable advanced analytics faster.
The first 90 days define a data leader's tenure. Whether you are a newly appointed Chief Data Officer, a VP of Data or AI stepping into a transformation mandate, or an executive sponsoring a modernization effort, the same problem appears in week one: everyone wants results, nobody agrees on sequence, and the existing architecture was built for a different era. A generic first-quarter plan tells you to "listen, plan, execute." This roadmap tells you what to actually ship, in what order, across the five pillars every data organization stands on — architecture and modeling, governance and integrity, cloud infrastructure and cost, AI and analytics readiness, and BI and reporting maturity.
Days 0–30 — Foundation. The first month is about making the invisible visible. You leave it with a medallion architecture blueprint, a mapped source-system landscape, live bronze ingestion for your priority systems, a data product catalog and document registry, a provisioned cloud landing zone with a cost baseline, an AI readiness scorecard, and a KPI dictionary. Thirty days in, you can show your board a picture of the estate that did not exist before — and a costed, sequenced plan for what comes next.
Days 31–60 — Build. The second month converts the blueprint into working assets: silver conformed models with data-quality tests, the first gold tables for your priority domains, enforced access controls, cost guardrails, the first predictive model, and core executive dashboards. This is the phase where stakeholders stop asking what the data team is doing — the dashboards answer for you.
Days 61–90 — Intelligence. The final month hardens everything for the long run: a published semantic layer, star schemas across domains, production model serving with drift monitoring, optimized cloud spend, and a full handover pack with runbooks and training. By day 90 the platform is AI-ready and the organization can run it without us standing next to it.
Every deliverable above is tracked in one live master file, updated in place as the team ships — which means your weekly status report writes itself, and your leadership always sees progress in the artefacts rather than in slideware.
Sample shown: the first 30 days for a DirecTV foundation engagement. Each pillar below lists what lands by day 30.
These are the working artefacts behind the 30-day plan, rebuilt here as live views. In a real engagement each one is a Notion or Figma file linked inside the client master file — opened in seconds for any weekly stand-up.
stg_raw_subscriberFivetran → Snowflake · CRM · hourlystg_raw_viewershipACR events · 68M HH · streamingstg_raw_billingBilling platform · txn level · dailystg_raw_ad_impressionsDSP + ad server · impression logint_subscriber_baseDeduped · tenure · churn flagint_viewership_aggSession rollup · affinity indexint_billing_cleanLTV calc · ARPU · payment healthint_ad_performanceCampaign rollup · reach · frequencydim_subscriber_360OBT · segment · LTV tier · churnfact_subscriber_eventsStar schema · all event typesfact_ad_performanceMVPD KPIs · reach/freq/lift/CPMdim_content_catalogGenres · networks · metadata| Data Product | Layer | Owner | Status |
|---|---|---|---|
subscriber_360 | Gold | Data Eng | Live |
ad_performance | Gold | Analytics | Build |
viewership_agg | Silver | Data Eng | Live |
content_catalog | Gold | Data Eng | Planned |
billing_clean | Silver | Data Eng | Live |
This snapshot uses sample DirecTV data for demonstration. In a live engagement, every cell links to the real Notion or Figma artefact in the client master file — the ERD and architecture blueprint are standardised per client and updated as the team ships.
A 30/60/90 day plan structures a new data or AI leader's first quarter into three phases: building the foundation (days 0–30), building models, governance and dashboards (days 31–60), and delivering intelligence — AI-ready, optimized, and handed over (days 61–90). One Big Table's methodology provides a pre-built framework for each phase, mapped to five architecture pillars.
By day 30 the foundation is in place: a medallion architecture blueprint, a source system map, bronze ingestion for the priority source systems, a document registry and data product catalog, a provisioned cloud landing zone with a cost baseline, an AI readiness scorecard, and a KPI dictionary with dashboard wireframes.
Chief Data Officers, VPs of Data or AI, and transformation leads at mid-market and enterprise organizations — especially leaders in their first 90 days who need to show structured progress fast, and executives sponsoring a data modernization effort who want visibility without ticket-tool overhead.
Everything lives in a single live master file. Each deliverable is a Notion or Figma artefact linked from the file, updated in place by the team as they ship. Weekly stand-up snapshots replace ticket administration — the artefacts are the status report. No Jira, no Confluence.
Yes. The five pillars are stack-agnostic. The same phased structure runs on Snowflake, Databricks, or Microsoft Fabric, and adapts to your ingestion tooling, BI platform, and governance requirements. The pillar deliverables are re-scoped to your architecture during the discovery session.
Book a discovery chat and we'll map a sample 30/60/90 plan against your own architecture pillars.
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