ODA User Guide

Data Studio

Operating model, permissions, and UI orientation for ODA Data Studio.

Data Studio is Optra's operational authoring and execution hub for building metadata-driven data products. It brings together workspace organization, semantic modeling, and job orchestration in one place so teams can move from raw source data to governed, business-ready outputs without switching tools. In practical terms, Data Studio is where users structure work, define reusable business meaning, and run pipelines with visibility into status, timing, and run outcomes.

At runtime, Data Studio is account-scoped and role-aware. The application loads only the workspaces, layers, and jobs in the currently selected account, then applies permission checks before exposing authoring actions. This matches how the platform behaves in code: listing APIs and LiveViews filter by account context, and create/edit/publish capabilities are controlled by user role. The result is a governed collaboration model where teams can safely build and operate pipelines across shared environments.

Primary Areas

Workspaces

Organize projects and team-owned domains.

Semantic Layers

Govern business meaning with versioned definitions.

Jobs

Schedule, run, and monitor operational execution.

Role Model

  • manage_data: create/edit Workspaces, Projects, and Jobs.
  • administrator: create/edit/publish Semantic Layers.
  • Reader roles: view/search with write actions hidden.

Navigation Routes

  • /data-accelerator
  • /data-accelerator/semantic-layers
  • /data-accelerator/jobs

UI Overview

The Data Studio UI is centered on a responsive left sidebar that keeps navigation, search, and account controls in one place. You can collapse the sidebar for more workspace area, then expand it again without leaving your current page. This gives users a consistent navigation model across Workspaces, Semantic Layers, and Jobs.

Sidebar Navigation

The left sidebar is the primary navigation surface for ODA. In expanded mode, it shows labels and icons; in collapsed mode, it shows icons only. The sidebar includes:

  • Ask Optra for AI-assisted guidance (availability depends on account configuration).
  • Search for cross-platform discovery of assets and records.
  • Data Studio links to Workspaces, Semantic Layers, and Jobs.
  • Profile and notifications controls at the bottom for settings, account switching, and sign out.

Account Menu and Notifications

The bottom of the sidebar contains user-level controls:

  • Profile menu: open Settings, switch accounts, and sign out.
  • Notifications: review system alerts, job updates, and platform messages.
  • Unread state: badges indicate pending notifications that need attention.

Page Surfaces

Workspaces: displays Recents, search, sortable tables, and personal stars for fast workspace access.

Semantic Layers: shows governance-focused banners, search, version-aware tables, and admin-only create/publish actions.

Jobs: splits execution management into All Jobs and Runs, with filters for status and timing visibility.

Responsive Behavior

The sidebar and page layout are responsive by design, so users can keep navigation accessible while prioritizing content space. This behavior is consistent across desktop and compact views and supports day-to-day authoring without losing orientation in the app.

Workspaces

Workspaces are the primary organizational container in Data Studio. They group related projects so teams can manage data initiatives by domain, product line, or business unit while keeping context and ownership clear. The UI supports both rapid discovery and day-to-day navigation through recents, search, sort, and personal starring, so frequently used workspaces and projects are easy to return to.

Operationally, Workspaces are not just folders; they are account-bound entities that anchor project lifecycle actions. When a workspace is opened, Data Studio resolves its related projects, recent activity, and user-specific stars, then updates this view dynamically as users search, sort, create, or edit descriptions. This gives teams a stable collaboration surface for organizing ingestion, transformations, and downstream delivery work.

How to Create a Workspace

To create a workspace, follow the below-mentioned steps:

  1. Open Data Studio > Workspaces from the left sidebar.
  2. Click Create in the top-right corner of the Workspaces page.
  3. In the Create new workspace modal, enter a workspace Name (required).
  4. Optionally enter a Description to help other users understand the workspace purpose.
  5. Click Save to create the workspace.

After creating or when browsing existing workspaces, use the Search workspaces... field on the right side of the page to quickly find the desired workspace by name.

Inside a Workspace: Projects, Search, Create, and Import

Once a workspace is created, open it to view all projects that belong to that workspace. The workspace page shows recent projects and a project library list, so you can quickly continue existing work.

Use the Search projects... field on the right side of the workspace page to find your desired project by name.

To create a project inside a workspace, follow the below-mentioned steps:

  1. Open the target workspace from Data Studio > Workspaces.
  2. Click Create in the top-right corner of the workspace page.
  3. In the Create new project modal, enter a project Name (required).
  4. Optionally enter a project Description.
  5. Click Save to create the project.

To import a project inside a workspace, follow the below-mentioned steps:

  1. Open the target workspace from Data Studio > Workspaces.
  2. Click Import in the top-right corner of the workspace page.
  3. In the Import Project modal, drag and drop your YAML export file, or click Choose File to browse locally.
  4. Select a supported file type (.yaml or .yml).
  5. Confirm the import to add the project into the workspace.

Semantic Layers

Semantic Layers define the business-ready meaning of data by modeling entities, metrics, dimensions, and relationships in a governed structure. This is the semantic contract between technical pipelines and business consumption: instead of every team reinterpreting tables independently, the platform centralizes definitions so reporting and analytics stay consistent across use cases.

In Data Studio, semantic modeling follows a versioned workflow with draft and published states, aligned with the ODA guidance on governed pipeline operations. Authors can evolve models in draft versions, manage entities and table relationships, and publish explicit versions when ready. The UI and backend enforce strong governance: only administrator-level users can create, edit, or publish layers, and deletion is blocked when a layer is referenced by active projects. This protects downstream consumers while still allowing controlled model evolution.

How to Create and Publish Semantic Layers

To create and publish semantic layers, follow the steps below.

  1. Open Data Studio > Semantic Layers.
  2. Click Create (admin only).
  3. The form starts with an auto-generated untitled name + timestamp.
  4. Enter/update Layer name and Description.
  5. Click Save.
  6. You are taken to the semantic layer editor page.

Manage Versions and Publish

To manage versions and publish semantic layers, follow the steps below.

  1. In a layer, open version menu (Version).
  2. Add a draft version when needed.
  3. Edit entities/tables in draft.
  4. Click Publish and optionally set version bump.
  5. Published versions become available as Published with vX.Y.Z.

Delete Behavior

To understand deletion behavior and constraints, follow the steps below.

  1. Click trash icon on index row.
  2. If the layer is not referenced by projects, delete confirmation appears.
  3. If used by projects, an error modal lists projects using it and delete is blocked.

What the System Does Behind the Scenes

Behind the scenes, the system:

  1. Lists semantic layers by account and optional search term.
  2. Computes latest published version per layer.
  3. Seeds a new layer with an initial draft VersionLayer.
  4. Copies entities/columns/FK relationships when creating new draft versions.
  5. Restricts create/edit/publish/delete to administrator role.

Jobs

Jobs are the execution and orchestration layer of Data Studio. They package pipeline intent into runnable units that can be triggered manually or on schedule, with optional notifications and tags for logical grouping. This mirrors ODA's operational model where tagging, scheduling, and monitoring are central to managing end-to-end data pipelines.

From a system perspective, the Jobs experience is split into configured jobs and execution history (runs). The All Jobs view focuses on job definitions, ownership, trigger mode, and latest run health, while the Runs view provides run-by-run observability with status, timestamps, duration, and searchable history. Data Studio continuously reconciles job metadata with latest pipeline activity so operators can quickly detect failures, review logs, and take corrective actions without leaving the platform.

How to Configure and Run Jobs

To configure and operate jobs, follow the steps below.

  1. Open Data Studio > Jobs.
  2. Stay on All Jobs tab.
  3. Click Create.
  4. Fill in required fields: Name, Project, and Tags.
  5. Optionally enable: Schedule, Notifications, and Run job on creation.
  6. Click Create.

Run and Monitor Jobs

To run and monitor jobs, follow the steps below.

  1. Click any row to open job details modal.
  2. Overview tab shows project, tags, schedule, created time.
  3. Click Run Now for immediate execution.
  4. Runs tab shows run history/status.
  5. Settings tab lets editable users pause/resume/remove schedule and manage notifications.

Use Runs Tab (Global)

To use the global Runs tab, follow the steps below.

  1. Switch to Runs tab.
  2. Search by run attributes.
  3. Adjust date range.
  4. Click a run row to open run log modal.

What the System Does Behind the Scenes

Behind the scenes, the system:

  1. Lists jobs scoped to your account.
  2. Joins each job with latest pipeline run for quick status.
  3. Applies filters (q, limit, offset, date window for runs).
  4. On create/update, validates role (manage_data) and persists changes.
  5. If schedule is active, schedules worker jobs; if paused/removed, cancels queued schedules.
  6. Run Now inserts a pipeline run record and enqueues worker execution.

Purpose

This guide explains how users interact with the ODA Data Studio area in Optra, with special focus on:

  • Workspaces
  • Semantic Layers
  • Jobs

It is based on the current UI and server-side behavior in this codebase.

Who Can Do What

  • Users with manage_data can create/edit Workspaces, Projects, and Jobs.
  • Users with administrator role can create/edit/publish Semantic Layers.
  • Reader users can still view pages, search, and inspect records, but create/edit actions are hidden.

How To Reach Data Studio

  1. Sign in and select your account from the left panel.
  2. In the left navigation under Data Studio, open one of these pages: Workspaces, Semantic Layers, or Jobs.

Routes used by the app:

  • /data-accelerator
  • /data-accelerator/semantic-layers
  • /data-accelerator/jobs

Practical User Flow (End-to-End)

  1. Create a Workspace.
  2. Open workspace and create/import a Project.
  3. Create Semantic Layer (admin), model entities, publish a version.
  4. In project transformations, map to semantic layer where needed.
  5. Create Job with relevant tags and optional schedule.
  6. Track run results in Jobs > Runs and job modal run history.

Common Questions

Why do I not see the Create button?

  • You likely have reader-level access.
  • Workspaces/Jobs create actions need manage_data.
  • Semantic Layers create/publish needs administrator.

Why is semantic layer delete blocked?

  • The layer is used by one or more projects.
  • The app intentionally prevents deleting in-use semantic models.

Why does Ask Optra say chat is not enabled?

  • The selected account does not have chat enabled.
  • Contact your administrator to enable this feature.

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