> ## Documentation Index
> Fetch the complete documentation index at: https://docs.databakery.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Usecases

# Introduction

Databakery is at the crossroads of several potential needs and use cases: its ease of use, sleek UI, and extensibility make Databakery interesting in many cases beyond pure tech players.

| Persona                      | Type                         | Primary Goal                                         |
| ---------------------------- | ---------------------------- | ---------------------------------------------------- |
| Data Owner / Domain Owner    | Business senior              | Own and govern a data domain                         |
| Data Steward                 | Business / Data              | Define, maintain, document data                      |
| Data Architect               | IT / Platform                | Model domains, flows, lineage                        |
| Data Engineer                | Technical                    | Implement and industrialize data pipelines           |
| Data Analyst / BI            | Data-savvy business          | Find, understand, and reuse data                     |
| Data Scientist / ML Engineer | Technical / Analytics        | Discover, qualify, and trust data for models         |
| Compliance / Risk Officer    | Compliance, Legal, Risk      | Prove compliance, control risk                       |
| Product Owner / PM Data      | Product / Business           | Prioritize and track data use cases                  |
| CDO / Data Governance Lead   | Data leadership              | Drive governance maturity and adoption               |
| Consulting Partner / Manager | External consulting          | Standardize data discovery & governance at clients   |
| M\&A / Strategy Consultant   | Strategy / Corporate finance | Use data as asset in deals, carve‑outs, integrations |
| PE / Investor Ops Partner    | Private equity / Value crea. | Track data value & risks across portfolio            |

# Usecase details

## Functional Data & Domain Cartography

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data owner</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data steward</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data architect</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">CDO</div>
</div>

<br />

Define a business domain map (Sales, Marketing, Finance, Claims, Pricing, etc.) with ownership, key KPIs, and core systems.

Maintain a functional catalog of business objects (Customer, Contract, Claim, Campaign, Product, Policy, Store…) with attributes, business rules, and linked quality rules.

Map roles and responsibilities (Owner, Steward, Custodian) per domain/object, with RACI and governance workflows.

Capture data contracts and expectations at domain boundaries (SLAs, freshness, quality thresholds, security constraints).

<br />

## Shared Vocabulary

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data steward</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data analyst</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Product owner</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Business teams</div>
</div>

<br />

Build a business glossary of terms, definitions, calculation rules, examples, and links to dashboards/metrics.

Manage synonyms, homonyms, and translations (e.g. Customer vs. Client vs. Account Holder) to reduce ambiguity.

Connect business terms to technical assets (tables, columns, views, APIs) and consuming assets (reports, KPIs, ML features).

Govern changes to definitions through proposals, reviews, approvals, and version history.

<br />

## Business Data Lineage

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data architect</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data engineer</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data steward</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Compliance</div>
</div>

<br />

Visualize business-level lineage (e.g. Prospect → Campaign Audience → Campaign → Lead → Opportunity → Sale) across systems and processes.

Perform impact analysis: “If we change this calculation or pipeline, which KPIs, reports, APIs, and domains are impacted?”

Provide a business-friendly complement to technical lineage, helping non-technical stakeholders understand end‑to‑end flows.

Identify single points of failure and over‑complex chains (too many hops, too many transformations) across domains.

<br />

## Governance, Risk & Compliance

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Compliance officer</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Risk manager</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">CDO</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data steward</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Legal teams</div>
</div>

<br />

Map sensitive data (PII, financial, health, confidential) with classification, legal basis, retention policies, and access rules.

Trace regulatory coverage (GDPR, SOX, HIPAA, IFRS, sector regulations) through policies, domains, and assets.

Produce audit-ready views: lineage, responsibilities, quality rules, access controls, exceptions, and review history.

Track risk register items tied to specific data domains / assets, with mitigation actions and owners.

<br />

## Data Quality & Trust

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data steward</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data engineer</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data analyst</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data owner</div>
</div>

<br />

Document data quality rules at business-object and attribute level (completeness, validity, consistency, timeliness).

Expose data quality scores and trends in the catalog/graph views, to guide consumers towards trustworthy assets.

Link data issues / incidents (tickets, defects, anomalies) to domains, attributes, and pipelines, with status and workflow.

Enable user feedback loops: analysts and business users can flag data problems directly from analytics tools and follow resolution.

<br />

## Data Discovery for Consumers

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data analyst</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">BI developer</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data scientist</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Product manager</div>
</div>

<br />

Provide a search and exploration experience across domains, terms, tags, data products, and KPIs.

Surface “ready-to-use” data products (certified tables/views, semantic models, APIs, ML datasets) with SLA, owner, and usage guidelines.

Show usage context: who consumes this asset, which dashboards / models rely on it, popularity and endorsements.

Help users compare alternative sources (two “customer” tables, two “revenue” definitions) and pick the right one.

<br />

## Program & Governance Management

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">CDO</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data governance lead</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">PMO</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data office</div>
</div>

<br />

Dashboard governance maturity: domain coverage, documentation completeness, steward engagement, adoption metrics.

Track role activity and gaps: domains without owners, inactive stewards, unassigned critical assets.

Monitor key governance initiatives (e.g. “finance data clean‑up”, “customer 360 build‑out”) with links to affected domains and lineage.

Provide governance OKRs/KPIs (e.g., catalog completeness, certified data product coverage, time to find/understand data).

<br />

## Project Support & Change Management

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data architect</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Product owner</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Product manager</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data engineer</div>
</div>

<br />

Use DataBakery as the standard discovery tool for new projects: understand domains, existing rules, data products, and debt before designing solutions.

Conduct impact analysis for projects: cloud migration, BI replatforming, system replacement, new product rollout.

Capture target architectures (domains, flows, responsibilities) and link them to current state for “as‑is / to‑be” comparisons.

Support change management by communicating data-related changes visually to business stakeholders.

<br />

## AI & LLM Governance

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">AI product owner</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">ML engineer</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">ML Ops</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Compliance</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">CDO</div>
</div>

<br />

Catalog ML/AI datasets (training, validation, test, monitoring) with sources, lineage, sensitivity, and owners.

Describe LLM/RAG assets: prompt templates, retrieval collections, embedding indexes, feature sets, and their upstream domains.

Map regulatory and ethical constraints on AI (allowed vs forbidden data, consent, bias risks) onto domains and AI assets.

Track model dependencies: which data domains and policies are behind each model, to support audits and risk assessment.

<br />

## Collaboration & Communication

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-primary text-white dark:text-black">All</div>
</div>

<br />

Enable discussions and comments on domains, concepts, rules, and data products, with mentions and notifications.

Provide playbooks / usage guides attached to domains and data products (best practices, known pitfalls, sample queries).

Use DataBakery as a central communication hub between business and IT for any topic that touches data.

Capture and share decision logs (why a definition changed, why we deprecated a data source, etc.).

<br />

## DataBakery for Consulting

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Consulting partner</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Manager</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data architect consultant</div>
</div>

<br />

Target Consulting Firms & Integrators.

Use DataBakery as a standard discovery & governance accelerator across all client engagements.

Onboard project teams faster by providing a structured, visual map of the client’s domains, systems, and data products.

Maintain reusable blueprints (domain models, lineage patterns, governance templates) that can be instantiated at each client.

Support adoption of heavy catalog tools (Collibra, Alation, Atlan, etc.) by offering a lighter, business‑friendly sandbox for early governance work.

<br />

## DataBakery for M\&A / Strategy

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">M\&A / Strategy consultant</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Corporate Development</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">PE / Investor Ops</div>
</div>

<br />

Mergers, Acquisitions, Carve‑outs.

Pre‑deal / Due Diligence use cases:

* Run data due diligence: map domains, systems, qualities, and risks of the target in a structured way (beyond a generic data room).

* Assess data maturity & risk of the target: fragmentation, duplication, lack of ownership, regulatory exposure.

* Highlight data-centric value levers and synergies (customer analytics, pricing, cross‑sell, operational optimization).

Post‑merger / Post‑acquisition use cases:

* Build a unified domain map across both entities (or across group and target) to identify overlaps and gaps.

* Drive application and data rationalization: decide which CRM/DWH/MDM or data products to keep, merge, or decommission.

* Design the target data operating model: domains, owners, stewards, central vs local responsibilities.

* Plan and track integration / carve‑out roadmaps from a data perspective: which domains and flows to merge, split, or migrate, in which order.

<br />

## DataBakery for Transformation

<div class="flex gap-1 -mt-2">
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Transformation lead</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Change manager</div>
  <div class="rounded-lg text-xs font-semibold px-2 bg-black text-white dark:bg-white dark:text-black">Data governance transformation lead</div>
</div>

<br />

Use DataBakery to tell the story of data to executives: domain maps, before/after views, critical journeys.

Orchestrate governance roll‑out: track progress on roles activation, documentation, and domain coverage.

Support training and onboarding: give new hires or new teams a navigable, visual map of the organization’s data landscape.