Build the first DP-700 reader slice

README.md

@@ -11,10 +11,12 @@ reproducing Microsoft Learn pages.
 
 ## Project status
 
-The project is in its first foundation milestone. The repository currently
-provides separate public reader and private administration application
-factories, environment-validated settings, automated boundary tests, and CI.
-Reader features and DP-700 content will be added through the public roadmap.
+The project is in its first reader milestone. The repository provides separate
+public reader and private administration application factories, a validated
+exam-agnostic book contract, the current DP-700 outline, sanitized Markdown
+rendering, a responsive reader shell, automated boundary tests, and CI. Reader
+preferences, local progress, annotations, and offline support remain roadmap
+work.
 
 ## Architecture boundary
 
@@ -62,6 +64,10 @@ project is not affiliated with or endorsed by Microsoft. Microsoft owns its
 learning material; this project links to authoritative sources and publishes
 original study-oriented writing under the repository license.
 
+The DP-700 manifest records the official skills blueprint effective July 21,
+2026. See [`docs/content-model.md`](docs/content-model.md) for stable identifier,
+ordering, and source-mapping rules.
+
 ## Contributing and security
 
 Work is tracked through GitHub issues and reviewed pull requests. Read

content/published/dp700/book.yaml

@@ -0,0 +1,137 @@
+id: dp700
+exam_code: DP-700
+title: Implementing Data Engineering Solutions Using Microsoft Fabric
+blueprint_effective_date: 2026-07-21
+blueprint_url: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700
+sources:
+  - id: dp700-study-guide
+    title: Official DP-700 study guide
+    url: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700
+domains:
+  - id: implement-manage
+    title: Implement and manage an analytics solution
+    weight: "30–35%"
+    chapters:
+      - id: workspace-settings
+        slug: workspace-settings
+        title: Configure Microsoft Fabric workspace settings
+        content_path: workspace-settings.md
+        status: draft
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: implement.workspace.spark, title: Configure Spark workspace settings}
+          - {id: implement.workspace.domain, title: Configure domain workspace settings}
+          - {id: implement.workspace.onelake, title: Configure OneLake workspace settings}
+          - {id: implement.workspace.airflow, title: Configure Apache Airflow workspace settings}
+      - id: lifecycle-management
+        slug: lifecycle-management
+        title: Implement lifecycle management in Fabric
+        content_path: lifecycle-management.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: implement.lifecycle.version-control, title: Configure version control}
+          - {id: implement.lifecycle.database-projects, title: Implement database projects}
+          - {id: implement.lifecycle.deployment-pipelines, title: Create and configure deployment pipelines}
+      - id: security-governance
+        slug: security-governance
+        title: Configure security and governance
+        content_path: security-governance.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: implement.security.workspace-access, title: Implement workspace-level access controls}
+          - {id: implement.security.item-access, title: Implement item-level access controls}
+          - {id: implement.security.data-access, title: "Implement row-level, column-level, object-level, and folder/file-level access controls"}
+          - {id: implement.security.masking, title: Implement dynamic data masking}
+          - {id: implement.security.sensitivity, title: Apply sensitivity labels to items}
+          - {id: implement.security.endorsement, title: Endorse items}
+          - {id: implement.security.audit, title: Implement and use Microsoft Fabric audit logs}
+          - {id: implement.security.onelake, title: Configure and implement OneLake security}
+      - id: orchestration
+        slug: orchestration
+        title: Orchestrate processes
+        content_path: orchestration.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: implement.orchestration.choose-tool, title: "Choose between Dataflow Gen2, a pipeline, and a notebook"}
+          - {id: implement.orchestration.triggers, title: Design and implement schedules and event-based triggers}
+          - {id: implement.orchestration.patterns, title: "Implement orchestration patterns with notebooks and pipelines, including parameters and dynamic expressions"}
+  - id: ingest-transform
+    title: Ingest and transform data
+    weight: "30–35%"
+    chapters:
+      - id: loading-patterns
+        slug: loading-patterns
+        title: Design and implement loading patterns
+        content_path: loading-patterns.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: ingest.loading.full-incremental, title: Design and implement full and incremental data loads}
+          - {id: ingest.loading.dimensional, title: Prepare data for loading into a dimensional model}
+          - {id: ingest.loading.streaming, title: Design and implement a loading pattern for streaming data}
+      - id: batch-data
+        slug: batch-data
+        title: Ingest and transform batch data
+        content_path: batch-data.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: ingest.batch.store, title: Choose an appropriate data store}
+          - {id: ingest.batch.transform-tool, title: "Choose between Dataflows Gen2, notebooks, KQL, and T-SQL for data transformation"}
+          - {id: ingest.batch.shortcuts, title: Create and manage OneLake shortcuts}
+          - {id: ingest.batch.mirroring, title: Implement mirroring}
+          - {id: ingest.batch.pipelines, title: Ingest data by using pipelines}
+          - {id: ingest.batch.languages, title: "Transform data by using PySpark, SQL, and KQL"}
+          - {id: ingest.batch.denormalize, title: Denormalize data}
+          - {id: ingest.batch.aggregate, title: Group and aggregate data}
+          - {id: ingest.batch.data-quality, title: "Handle duplicate, missing, and late-arriving data"}
+      - id: streaming-data
+        slug: streaming-data
+        title: Ingest and transform streaming data
+        content_path: streaming-data.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: ingest.streaming.engine, title: Choose an appropriate streaming engine}
+          - {id: ingest.streaming.native-shortcut, title: Choose between native tables and OneLake shortcuts in Real-Time Intelligence}
+          - {id: ingest.streaming.acceleration, title: Choose between Query acceleration for OneLake shortcuts and standard OneLake shortcuts in Real-Time Intelligence}
+          - {id: ingest.streaming.eventstreams, title: Process data by using Eventstreams}
+          - {id: ingest.streaming.spark, title: Process data by using Spark structured streaming}
+          - {id: ingest.streaming.kql, title: Process data by using KQL}
+          - {id: ingest.streaming.windows, title: Create windowing functions}
+  - id: monitor-optimize
+    title: Monitor and optimize an analytics solution
+    weight: "30–35%"
+    chapters:
+      - id: monitor-items
+        slug: monitor-items
+        title: Monitor Fabric items
+        content_path: monitor-items.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: monitor.items.ingestion, title: Monitor data ingestion}
+          - {id: monitor.items.transformation, title: Monitor data transformation}
+          - {id: monitor.items.semantic-refresh, title: Monitor semantic model refresh}
+          - {id: monitor.items.alerts, title: Configure alerts}
+      - id: resolve-errors
+        slug: resolve-errors
+        title: Identify and resolve errors
+        content_path: resolve-errors.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: monitor.errors.pipeline, title: Identify and resolve pipeline errors}
+          - {id: monitor.errors.dataflow, title: Identify and resolve Dataflow Gen2 errors}
+          - {id: monitor.errors.notebook, title: Identify and resolve notebook errors}
+          - {id: monitor.errors.eventhouse, title: Identify and resolve Eventhouse errors}
+          - {id: monitor.errors.eventstream, title: Identify and resolve Eventstream errors}
+          - {id: monitor.errors.tsql, title: Identify and resolve T-SQL errors}
+          - {id: monitor.errors.shortcut, title: Identify and resolve OneLake shortcut errors}
+      - id: optimize-performance
+        slug: optimize-performance
+        title: Optimize performance
+        content_path: optimize-performance.md
+        source_ids: [dp700-study-guide]
+        objectives:
+          - {id: monitor.optimize.lakehouse, title: Optimize a Lakehouse table}
+          - {id: monitor.optimize.pipeline, title: Optimize a pipeline}
+          - {id: monitor.optimize.warehouse, title: Optimize a data warehouse}
+          - {id: monitor.optimize.realtime, title: Optimize Eventstreams and Eventhouses}
+          - {id: monitor.optimize.spark, title: Optimize Spark performance}
+          - {id: monitor.optimize.query, title: Optimize query performance}

content/published/dp700/chapters/batch-data.md

@@ -0,0 +1,14 @@
+# Ingest and transform batch data
+
+<!-- block-id: placeholder-orientation -->
+This chapter will connect store selection, ingestion mechanisms, transformation languages, and data-quality handling into an end-to-end batch design.
+
+## Planned study work
+
+- Choose among shortcuts, mirroring, and pipeline copies.
+- Compare Dataflows Gen2, notebooks, KQL, and T-SQL.
+- Handle duplicate, missing, and late-arriving records explicitly.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/lifecycle-management.md

@@ -0,0 +1,14 @@
+# Implement lifecycle management in Fabric
+
+<!-- block-id: placeholder-orientation -->
+This chapter will connect version control, database projects, and deployment pipelines into one reviewable DEV-to-production lifecycle.
+
+## Planned study work
+
+- Compare Git integration with deployment pipelines.
+- Trace how database project changes are built and reviewed.
+- Practice selecting the correct promotion mechanism for a scenario.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/loading-patterns.md

@@ -0,0 +1,14 @@
+# Design and implement loading patterns
+
+<!-- block-id: placeholder-orientation -->
+This chapter will model full, incremental, dimensional, and streaming loads as choices driven by source behavior, latency, correctness, and recovery needs.
+
+## Planned study work
+
+- Compare watermarks, change tracking, and full reloads.
+- Prepare facts and dimensions for reliable loading.
+- Design a recoverable streaming ingestion path.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/monitor-items.md

@@ -0,0 +1,14 @@
+# Monitor Fabric items
+
+<!-- block-id: placeholder-orientation -->
+This chapter will develop an evidence path across ingestion, transformation, semantic model refresh, and actionable alerts.
+
+## Planned study work
+
+- Identify the correct monitoring surface for each item.
+- Correlate upstream ingestion with downstream refresh behavior.
+- Configure alerts around operationally meaningful conditions.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/optimize-performance.md

@@ -0,0 +1,14 @@
+# Optimize performance
+
+<!-- block-id: placeholder-orientation -->
+This chapter will separate storage layout, orchestration, compute, and query optimization so that each performance change is tied to measured evidence.
+
+## Planned study work
+
+- Diagnose before selecting an optimization.
+- Compare Lakehouse, warehouse, Spark, and real-time tuning levers.
+- Validate improvements against a repeatable workload.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/orchestration.md

@@ -0,0 +1,14 @@
+# Orchestrate processes
+
+<!-- block-id: placeholder-orientation -->
+This chapter will compare Dataflow Gen2, pipelines, and notebooks, then develop schedules, event triggers, parameters, and dynamic orchestration patterns.
+
+## Planned study work
+
+- Select an orchestration tool from workload constraints.
+- Trace parameters through a multi-step pipeline.
+- Compare scheduled and event-driven execution.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/resolve-errors.md

@@ -0,0 +1,14 @@
+# Identify and resolve errors
+
+<!-- block-id: placeholder-orientation -->
+This chapter will use a consistent diagnose-isolate-correct-verify loop across pipelines, Dataflows Gen2, notebooks, Eventhouse, Eventstreams, T-SQL, and shortcuts.
+
+## Planned study work
+
+- Map common failures to their best diagnostic evidence.
+- Separate configuration, identity, data, and runtime causes.
+- Turn recurring failures into regression checks.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/security-governance.md

@@ -0,0 +1,14 @@
+# Configure security and governance
+
+<!-- block-id: placeholder-orientation -->
+This chapter will distinguish workspace, item, data, and OneLake security boundaries, then connect them to labels, endorsements, masking, and audit evidence.
+
+## Planned study work
+
+- Build a role-and-scope decision table.
+- Compare row, column, object, and file-level controls.
+- Work through governance scenarios without conflating discovery and authorization.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/streaming-data.md

@@ -0,0 +1,14 @@
+# Ingest and transform streaming data
+
+<!-- block-id: placeholder-orientation -->
+This chapter will compare streaming engines, Real-Time Intelligence storage choices, Eventstreams, Spark structured streaming, KQL, and window semantics.
+
+## Planned study work
+
+- Select an engine from latency and processing requirements.
+- Compare native tables with standard and accelerated shortcuts.
+- Reason about tumbling, hopping, and sliding windows.
+
+## Source
+
+See the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700).

content/published/dp700/chapters/workspace-settings.md

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+# Configure Microsoft Fabric workspace settings
+
+<!-- block-id: orientation -->
+Workspace settings are control points. They shape how a team uses compute, organizes ownership, reaches shared data, and schedules orchestration. For the exam, focus on **who controls a setting, what scope it affects, and what operational consequence follows**.
+
+## Start with the boundary
+
+<!-- block-id: boundary-model -->
+A workspace is a collaboration and security boundary, but not every behavior is controlled at workspace scope. Some defaults inherit from capacity or tenant administration. Before changing a setting, identify the governing scope and whether the workspace administrator can override it.
+
+| Setting family | Primary concern | Exam question to ask |
+| --- | --- | --- |
+| Spark | Compute defaults and runtime behavior | Does this change the workspace default or only one session? |
+| Domain | Business ownership and discovery | Is the workspace assigned to the correct data domain? |
+| OneLake | How data is exposed and accessed | Does the change affect access, discoverability, or data movement? |
+| Apache Airflow | Managed orchestration configuration | Who owns connections, schedules, and operational monitoring? |
+
+## A practical decision sequence
+
+<!-- block-id: decision-sequence -->
+1. Identify the required outcome: performance, governance, access, or orchestration.
+2. Locate the narrowest administrative scope that owns the behavior.
+3. Check inheritance and override rules before changing a default.
+4. Validate the effect with a representative workload rather than assuming the setting is isolated.
+5. Record the operational owner and a rollback path.
+
+## Exam distinction
+
+<!-- block-id: exam-distinction -->
+Do not treat all workspace settings as interchangeable toggles. Spark settings primarily influence compute behavior; domain assignment communicates business organization; OneLake settings influence the shared data plane; and Apache Airflow settings support managed workflow orchestration. A scenario usually gives clues about **scope**, **owner**, and **effect**.
+
+## Active recall
+
+<!-- block-id: active-recall -->
+- Which settings would you examine first when every notebook in a workspace starts with an unsuitable Spark default?
+- Why is assigning a workspace to a domain different from granting access to the workspace?
+- What evidence would you collect before changing a setting that may affect multiple workloads?
+
+## Source
+
+<!-- block-id: official-source -->
+Use the [official DP-700 study guide](https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-700) as the authoritative skills outline. This chapter is original study-oriented writing and will be expanded with setting-specific Microsoft Learn sources in the content-authoring milestone.

docs/content-model.md

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+# Book content model
+
+Study Reader separates authored chapters from application code. A published
+book is a directory containing `book.yaml` and a `chapters/` directory of
+Markdown files.
+
+## Stable identifiers
+
+- Book, domain, chapter, source, and objective identifiers MUST be lowercase,
+  human-readable, and stable after publication.
+- Chapter slugs MUST be unique within a book and MUST remain stable when a title
+  changes.
+- Objective identifiers SHOULD describe their hierarchy, such as
+  `ingest.streaming.windows`.
+- An explicit `<!-- block-id: durable-name -->` marker assigns a durable anchor
+  to the next top-level Markdown block. Authors SHOULD use explicit block IDs
+  for important passages that may receive bookmarks, highlights, or notes.
+- Blocks without explicit markers receive deterministic section-and-position
+  identifiers. Those fallbacks survive ordinary wording edits but MAY change if
+  blocks are inserted or reordered in the same section.
+
+## Ordering
+
+YAML list order is authoritative. Domain order follows the official skills
+outline. Chapter order follows the subdomains within each domain. Objective
+order follows the bullet order in the effective official blueprint. The reader
+MUST NOT infer order from identifiers or filenames.
+
+## Sources and ownership
+
+Every chapter MUST map to at least one source declared in its book manifest.
+The manifest records the official blueprint URL and effective date. Additional
+chapter-specific sources will record retrieval dates and hashes in the refresh
+milestone.
+
+Microsoft Learn remains authoritative for Microsoft exam objectives and product
+behavior. Markdown chapters MUST contain original study-oriented writing and
+MUST NOT reproduce Microsoft Learn pages wholesale.
+
+## Validation
+
+Pydantic rejects duplicate identifiers, duplicate slugs, broken source
+references, invalid paths, and unknown manifest fields. Content tests confirm
+that every planned chapter file exists and maps at least one objective and one
+source. Rendering tests verify sanitized HTML, stable anchors, external-link
+behavior, and a reviewed golden fixture.