Where to go next — choose your role Path

If you made it this far, you've handled D.Hub's four core results — collection · dataset · chart · scenario — by hand. The next step is to pick the role Path that fits you. This lesson is a brief tour of the six available Paths.

Choose from six role Paths

Each Path's short pitch for its first lesson is listed below. Step into whichever pulls you most. This Path's progress is automatically saved, so you can always come back via the Welcome — continue learning panel.

Choose the first Path by your most frequent work; if you cover several roles, return for another Path later.

flowchart TB
    accTitle: Choose a role Path after Essentials
    accDescr: Choose Analyst, Data Engineer, FDE, Ontology Modeler, Admin, or Agent Builder according to whether your primary work is analysis, data supply, solution delivery, semantic modeling, governance, or AI automation.
    work{What is your primary work?}
    work -->|Analysis and visualization| analyst[Analyst Path]
    work -->|Ingestion and automation| engineer[Data Engineer Path]
    work -->|End-to-end customer solution| fde[FDE Path]
    work -->|Entity and relation modeling| ontology[Ontology Modeler Path]
    work -->|Users, permissions, policies| admin[Admin Path]
    work -->|LLM tools and approvals| agent[Agent Builder Path]

Analyst Path — 40 min, 6 lessons

Find data, see patterns through visualization, share results. First lesson: Analyst's main work areas — re-draws portal's four surfaces from the analyst's vantage and pins down the division of Collections · Dashboard · Search · AI Assistant.

Pick this if: your day-to-day work is analyzing data to produce answers.

Data Engineer Path — 50 min, 6 lessons

Ingest, transform, and automate. First lesson: Data engineer's main work areas — the split between connectors · pipelines · code nodes · scheduling, and the first judgment call for when to write a code node versus when standard nodes suffice.

Pick this if: your day-to-day work is supplying and automating data.

FDE Path — 50 min, 6 lessons

Build a customer-facing D.Hub solution from end to end. First lesson: Collection management — create the workspace boundary and add the datasets, code, knowledge, and pipelines the solution will use. Later lessons connect ontology, pipelines and dashboards, models and agents, tools and knowledge, deployment, and validation.

Pick this if: you are a Forward Deployed Engineer or product developer who connects data and AI capabilities into a working solution for a customer environment.

Ontology Modeler Path — 55 min, 6 lessons

Model your data as entities and relations in a graph. First lesson: Ontology overview — how entities, relations, and graph instances differ, and how defining a model differs from loading its instances.

Pick this if: you design the semantic model of your data, or sit in the modeling role that bridges analysts and engineers.

Admin Path — 45 min, 6 lessons

Permission model · SSO · FGAC · audit trails. First lesson: Permission model at a glance — how collection roles become the minimum inherited role on sub-assets and how higher resource-specific grants work.

Pick this if: you operate users · groups · policies, or own permission governance during early adoption.

Agent Builder Path — 55 min, 6 lessons

Design agent workflows that unpack natural-language input into tools and decisions. First lesson: Agent overview — the three axes (tools · actors · intent classification) and HITL (Human-in-the-Loop) — the first safety pattern.

Pick this if: your work integrates LLMs into automation flows, or you're building AI-driven decision scenarios in the early adoption stage.

When you sit across roles

Three common transition orders:

1. Analyst → Engineer — When you started in analytics but want to transform data yourself.
2. Engineer → Ontology Modeler — Once pipelines are second nature and you want to design the semantic model.
3. Engineer → FDE — When you want to expand individual data workflows into a complete customer solution and take it through deployment.
4. Admin → Agent Builder — From governance into responsibility for AI adoption.

Progress is tracked independently per Path, so running multiple in parallel works fine.

Wrap-up

This Essentials Path ends here. In 30 minutes, you walked through D.Hub's map + first result + a complete scenario tour. Take the next Path for depth.

Great job.