Learning Paths
Guided journeys by role and goal — built from stories, series, tools, and glossary terms.
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GDPR Foundations
Personal data, purpose, PII levels, data-subject rights and DPIA handoff — the operable foundation before pillars and compliance essentials.
3 steps
PII in 5 steps
After GDPR Foundations: from classification and masking to DSDR — the shortest solid entry into personal data governance.
5 steps
DQ with dbt
From tests and history to a cockpit — data quality as an operating discipline, not a one-off audit.
4 steps
Modernize the warehouse
Modern data warehouse with grain, products, and governance — without greenfield romanticism.
4 steps
Binom Governance — the concept
The thesis in 90 minutes: eight operable pillars, weight by size, one function card, one decision brief — before foundations or a stack deep dive.
3 steps
Quality foundations
DQ vs contract vs proof — when gates apply, before dbt ops and hygiene paths start.
3 steps
Metadata foundations
Metadata ≠ catalog ≠ dashboard ≠ semantic — entry before the operating model and OpenMetadata depth.
3 steps
Metrics foundations
BI decisions, semantic store and shared model — before trusted-metrics ops and KPI intake.
3 steps
Governance foundations
Pillars, roles, and the hub as a workbench — before certificates and frameworks kick in.
8 steps
Compliance essentials
GDPR, EU digital regulations, and ISO for data-governance projects — summary, not legal advice.
4 steps
First decision in the function
One Friday question, one product, owner or vacancy, export one page — then STOP. No harvest.
3 steps
Finance landscape
Close, ledger vs management accounting, forecast handoff, internal controls, audit and segregation of duties — before KPIs and tools are debated.
3 steps
HR landscape
Workforce contracts, purpose binding, masking, DSDR and analytics allowlist — privacy and ownership for HR data.
3 steps
Channel sales landscape
Two-tier account grain, deal registration vs pipeline, rebate ≠ booking — on the sales hub, not under partner sharing.
2 steps
Metadata operating model
From “what is metadata” to product ops — catalog, lineage, and automation as control levers.
5 steps
Sales landscape
CRM fields with decision value, pipeline gates, forecast versioning, and closed-won handoff.
3 steps
Marketing landscape
Consent and preferences, campaign products, attribution ownership, and marketing-to-sales handoff.
3 steps
Banking & insurance landscape
Regulatory reporting, model risk, DORA ICT, incident evidence, outsourcing and data residency — authority before supervisory proof.
3 steps
IT family landscapes
Bundle path for the five IT child landscapes — pick the child card, then isolation, contract, grant, asset, or SLO.
2 steps
Data platform landscape
Custodian ≠ owner, runtime contract, isolation, inventory, and publish gate.
3 steps
Data engineering landscape
Contract before transform, DQ owner path, semantics handoff, and breaking change.
3 steps
Hardware landscape
Serial grain, install-base, quote-to-delivery, warranty/RMA, and refresh — before a CMDB dump replaces the device list.
3 steps
Governance project intake
Stack inventory, authority matrix, and gap register — before the pilot flow starts.
7 steps
IT security landscape
Sponsor before grant, recert, secrets, and evidence pack.
3 steps
Operations landscape
Exception lists, service levels and operational ownership — before KPI chaos and shadow ops.
3 steps
Manufacturing landscape
Plant, OT/IT and quality data — ownership before control-data and KPI debates; OEM slice: vehicle data after SOP.
3 steps
Workplace IT landscape
Employee asset, MDM vs identity, CMDB grain, refresh/exit.
3 steps
Healthcare landscape
Patient identity, purpose binding and sharing — privacy and authority first.
4 steps
IT operations landscape
Tool SLO, change/incident evidence, service boundary, handoff to the platform.
3 steps
Public sector landscape
Registers, once-only and transparency — without purpose conflicts or records/analytics mix-ups.
3 steps
Partner landscape
Onboarding, scope drift and reviews — contracts before partner data scales.
3 steps
Trusted metrics
KPI definition, owner, and change process — so numbers stop diverging across tools and meetings.
5 steps
Governance delivery pilot
Prioritize source, lock scope and KPIs, mart design and controls — through signoff.
6 steps
Governance sales enablement
Partial scope, trust claim, one function card, skim the delegation table, fill the customer guide — then stop. No trust claim, no Placement. No Cloudera deep dive, no intake marathon.
4 steps
Governance delivery service
Attach the SKU: Parts 6+7 in full, one landscape card. Intake or pilot only as a follow-on link — platform paths stay outside.
3 steps
Field sales — selling governance
Optional after enablement: conversation arc, objections, when which SKU. No Cloudera, no intake. Trust claim stays mandatory.
4 steps
Governance AfterSales
Take the guide, fill the handoff pack, stop. No intake, no stack. Name, first review, kill or renewal.
3 steps
Close the gaps
The missing pieces as diagnosis — prioritize ownership, metadata, DQ, metrics, access, and lifecycle.
4 steps
Extended domain landscapes
Retail/commerce, ESG, extended functions, M&A and insurance claims — domain landscapes without a dedicated single path.
3 steps
Corridor for follow-on work
Read the series, pick the project moment, fill freeze/leave-open, export the Join Pack — then STOP. Sales does not fill the pack.
4 steps
software/product landscape
Experiment register, telemetry purpose, promotion, share, feature boundary.
3 steps
Find, do not expose
Read the series, cut three layers, export the visibility contract — then STOP. Preference does not legalise analytics.
4 steps
Partner: use per company
Read the series, name entity on feeds, write one local row and kill line. Group paper is a frame, not a grant.
3 steps
Governance by function
Governance by function: entry, typical decisions, interfaces, and evidence.
2 steps
The file is not the dashboard
Name four objects, refuse one warehouse decision, split Vorgang-ID from the stats grain.
3 steps
Governance operations
Exceptions, recertification, evidence, and lifecycle — operating after the pilot.
3 steps
Hold one KPI
Name the decision, fill a card with an owner, put calculation in the semantic layer. A formula is not a KPI.
3 steps
Retail / commerce landscape
Retail / commerce landscape: entry, typical decisions, interfaces, and evidence.
2 steps
Test before the next agent tool
Golden traces, block/waive/pass, retest on scope change. Eval is a release, not a workshop.
3 steps
ERP on-prem to SaaS
Lift the same ERP line: authority, identifier map, comparison pack, consumer cutover, sunset. On-prem and SaaS are not the same source.
5 steps
ESG / sustainability landscape
ESG / sustainability landscape: entry, typical decisions, interfaces, and evidence.
2 steps
Legal / compliance landscape
Legal / compliance landscape: entry, typical decisions, interfaces, and evidence.
2 steps
Risk landscape
Risk landscape: entry, typical decisions, interfaces, and evidence.
2 steps
AI foundations
Basics, risks, and governance for AI — before RAG and agents meet unmanaged metadata.
8 steps
Customer service landscape
Customer service landscape: entry, typical decisions, interfaces, and evidence.
2 steps
Data Owner entry
Short entry into Data Owner: mandate, boundaries, collaboration, and next foundations.
2 steps
Data Steward entry
Short entry into Data Steward: mandate, boundaries, collaboration, and next foundations.
2 steps
Procurement landscape
Procurement landscape: entry, typical decisions, interfaces, and evidence.
2 steps
Data Product Owner entry
Short entry into Data Product Owner: mandate, boundaries, collaboration, and next foundations.
2 steps
Data Architect entry
Short entry into Data Architect: mandate, boundaries, collaboration, and next foundations.
2 steps
Data Custodian entry
Short entry into Data Custodian: mandate, boundaries, collaboration, and next foundations.
2 steps
Data Consumer entry
Short entry into Data Consumer: mandate, boundaries, collaboration, and next foundations.
2 steps
Control data ops
Pull inline, Excel and entitlement matrices out of apps — placement, DIY stewardship, and hierarchies as products.
3 steps
Redundancy ops
Outsource duplicated meaning from tools — inventory, patterns, dual-run, and scorecard.
3 steps
Access & security ops
Access rules, masking, and policy operations — so security does not live only in slides and tickets.
3 steps
Deletion ops
Deletion that sticks — scope, strategy, platform path, backups, and evidence including restore recurrence.
3 steps
Data hygiene ops
Inventory, score, retire orphans, zombies and shadow assets — and prevent them with gates.
3 steps
Authoritative truth (SSOT bridge)
SSOT as decision purpose, not a slogan — bridging control data, redundancy, products, and hygiene.
3 steps
Data junk before AI
Bridge hygiene and deletion to AI prep: clean corpora, set fitness gates, stop PII, and remediate incidents — including machine unlearning.
3 steps
Mail & documents before AI
Enterprise content as an estate: classification and hold, purpose binding, attachments, deletion across the index, and evidence — before mail and docs feed AI.
3 steps
Sanctioned AI ops
Close shadow AI; run Act ops, cards, synthetic/poisoning gates, RAG eval, agent HITL, and cost/lineage scorecard.
4 steps
Workplace AI governance
AUP and path rules, literacy, GenAI vendor gates, Copilot tenant controls, and workplace scorecard — close shadow AI from the positive side.
3 steps
AI assurance ops
Impact pack, fairness gates, red-team cadence, GPAI roles, post-market, and assurance scorecard.
3 steps
AI rights & media
Rights register, output claims, multimodal paths, deepfake/authenticity, and evidence pack.
3 steps
Embedded AI surfaces
Code assist in SDLC, BI Copilot gates, GenAI routing/residency, surface inventory, and scorecard.
3 steps
End-to-end governance
Architecture, dbt meta, raw automation, and masking as one control chain — not isolated tools.
3 steps
Simplest viable stack
Choose the simplest solid architecture — before bronze/silver/gold or tool lists take over the debate.
3 steps
Cloudera CDP governance
Governance entry on Cloudera CDP: choose the starting point, treat Ranger/Atlas/Hive as the operating surface, add Kafka, document tools and stack — without mistaking tooling for authority.
6 steps
Argonos governance
Governance entry on Argonos: fit beyond BIG 5, start story, operating boundary, multi-platform and evidence — without mistaking sovereignty for authority.
5 steps
Governance help hub
Use the platform as a work chain: tours, Advisor, stories, learning paths, tools, language/roles, radar — and start a first sprint.
5 steps
Cloudera CDP reporting year
Year roadmap CDP Lakehouse / dbt / Power BI: understand the landscape, A–Z prototype, governance & app factory — parallel to the Databricks path.
3 steps
Acceptance gates on the artefact
Status lives on the artefact, not in ticket chat. Separate draft, reviewed, approved, and evidence.
4 steps
Operate catalog search
Synonyms, stale hits, and ranking are operating work. Clicks are not authority.
4 steps
Keep governance decision records
The brief is not minutes. Review date, expiry, and change without losing history.
4 steps
Retirement across artefacts
Retire table, metric, dashboard claim, and AI corpus separately — the same A logic.
4 steps
Consumer feedback loop
A misread dashboard is triaged; the owner decides; catalog and BI carry the fix.
4 steps
Hold operating metrics
The board pack is one page. Size, hat, and function — not a headcount cockpit.
4 steps
Operate co-determination
Works council is consulted. Evidence before the employee load. A no needs a return path.
4 steps
Hold ethics beside compliance
Compliant can still be unfair. Population, reasoned no, not a values poster.
4 steps
BI publish deep dive
One semantic, one app: stage, refresh A, reduction adapter. Workspace admin is not data owner.
3 steps
Dashboard and report design deep dive
One surface for one decision: type, scan or sheet or alert, design gate before promotion.
3 steps
Chart choice deep dive
Task before the chart picker: type, bans per surface, honest scale, field before promotion.
3 steps
Governance app deep dive
One grain from the DQ tools, outcome KPIs, one semantic, three adapters, surface gate.
3 steps
Sales enablement: Banking and insurance
Industry-specific entry for governance as a service in Banking and insurance.
2 steps
Sales enablement: Healthcare
Industry-specific entry for governance as a service in Healthcare.
2 steps
Sales enablement: Public sector
Industry-specific entry for governance as a service in Public sector.
2 steps
Sales enablement: Finance and controlling
Industry-specific entry for governance as a service in Finance and controlling.
2 steps
Sales enablement: Manufacturing
Industry-specific entry for governance as a service in Manufacturing.
2 steps
Sales enablement: Retail and commerce
Industry-specific entry for governance as a service in Retail and commerce.
2 steps
Sales enablement: Software and product development
Industry-specific entry for governance as a service in Software and product development.
2 steps
Cert + project in parallel
When several certificates run beside delivery: a shared companion plan for exercises, evidence, and transfer — so learning does not detach from the project.
3 steps
dbt cert companion
You are taking the official dbt certification — this path and sprint plan accompany you week by week: learn → labs → exam → transfer into the project.
4 steps
Fabric / Power BI cert companion
You are heading for DP-600 (Fabric Analytics Engineer) and/or PL-300 (Power BI Data Analyst) — this path and sprint plan accompany learning, labs, and the exam.
4 steps