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Bibliography and Resources

A selective list of references this section is based on, grouped by theme, with what each one contributes and the file in this section it relates to.

Guide≈ 8 min readPartly checkedPartial checkThe main facts were checked by searching the cited sources. The items below still need checking before relying on them.To re-check
  • Éditions courantes de DAMA-DMBOK, PRINCE2 et OWASP LLM Top 10 non revérifiées ; calendrier de l’AI Act (omnibus numérique) non définitivement confirmé, la page renvoie déjà à la source.
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Reading
In brief
  • A selective list of references this section is based on, grouped by theme, with what each one contributes and the file in this section it relates to.
  • No web links are provided: addresses change and I cannot verify them all; search for the exact title. Publication dates are only mentioned when they are certain; otherwise, “current edition to be verified.”
  • References are cited by name; always consult the latest version of a standard or online documentation (as of 2026-10).
On this page

Level: 🟢→🔴

Project management and methods#

Reference Type What it contributes In this section
The Scrum Guide (2020 edition, by Ken Schwaber and Jeff Sutherland) Official guide, short Reference definition of Scrum: roles, events, artifacts, commitments; check whether a more recent edition exists (as of 2026-10) Scrum, the framework (Scrum Guide 2020), Scrum in Practice
The Manifesto for Agile Software Development (2001) and its twelve principles Foundational text The four values and twelve principles of agility Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOps…)
A Guide to the Project Management Body of Knowledge (PMBOK Guide), Project Management Institute Framework Project management vocabulary and processes; eighth edition published by PMI in November 2025, current edition to be verified Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
PRINCE2 (AXELOS / PeopleCert) Method Stage-based governance, roles, and continuous business justification; current edition to be verified Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
Kanban — Kanban: Successful Evolutionary Change for Your Technology Business, David J. Anderson Book Kanban as a change method: visualize, limit work in progress, manage flow Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOps…)
The Principles of Product Development Flow, Donald G. Reinertsen Book Queue economics, batch size, cost of delay: theoretical foundation of flow Project Management Fundamentals
The Mythical Man-Month, Frederick P. Brooks Jr. Classic book Why adding people to a late project makes it later; limits of estimation Project Management Fundamentals
Peopleware, Tom DeMarco and Timothy Lister Classic book The human factor, work environment, team productivity PI Matrix — team
Team Topologies, Matthew Skelton and Manuel Pais Book Team organization around flow, cognitive load, interaction modes Choosing Your Method and Hybridizing

Continuous delivery, DevOps, and measurement#

Reference Type What it contributes In this section
Accelerate, Nicole Forsgren, Jez Humble, and Gene Kim Book, research-based The four delivery metrics (deployment frequency, lead time for changes, change failure rate, time to restore service) and their links to performance CI/CD: Continuous Integration and Continuous Delivery, Maturity Matrix — Software Development (code DL)
DORA reports (State of DevOps, DevOps Research and Assessment) Annual reports Evolution of practices and performance classes; exact values change, consult the most recent edition DL Matrix — CI/CD
Continuous Delivery, Jez Humble and David Farley Book Deployment pipeline, automated tests, reliable deployment CI/CD: Continuous Integration and Continuous Delivery
The Phoenix Project and The DevOps Handbook (Gene Kim and co-authors) Novel and handbook The “three ways”: flow, feedback, continuous learning CI/CD for data: foundations, datamarts, pipelines, and reports
Site Reliability Engineering (Google, O'Reilly editions) Book Service level objectives (SLOs), error budget, incident management DL Matrix — observability
Refactoring (Martin Fowler) and Clean Code (Robert C. Martin) Books Safe rewriting techniques, code readability DL Matrix — code quality
Working Effectively with Legacy Code (Michael C. Feathers) Book Introducing tests into existing code without breaking it DL Matrix — technical debt

Tools: version control and tracking#

Reference Type What it contributes In this section
Pro Git, Scott Chacon and Ben Straub Book, freely available online The reference for understanding Git in depth: object model, branches, merges, history Git In Depth
Official Git documentation Documentation Command manual pages; version to consult depends on the installation Git In Depth
Microsoft Learn documentation — Azure DevOps (Azure DevOps Services and Azure DevOps Server) Documentation Repositories (TFVC and Git), boards, pipelines, work item tracking; features must be rechecked based on the deployed version (as of 2026-10) Azure DevOps Server (formerly TFS) In Depth, TFVC In Depth
Microsoft Learn documentation — Team Foundation Version Control Documentation tf commands, workspaces, branches, TFVC merges TFVC In Depth
Jira documentation (Atlassian) Documentation Projects, workflows, boards, integration; to be checked according to edition Jira In Depth and Alternatives
Trunk Based Development (community reference site) Resource Trunk-based development, short branches, feature flags Branching Strategies

Data: modeling, governance, lifecycle#

Reference Type What it contributes In this section
The Data Warehouse Toolkit, Ralph Kimball and Margy Ross Book The reference for dimensional modeling: star schema, conformed dimensions, facts, slowly changing dimensions BI Matrix — semantic model, PD Matrix — modeling
The Data Warehouse Lifecycle Toolkit, Ralph Kimball and co-authors Book Data warehouse lifecycle: requirements, architecture, development, deployment Methods Specific to Data Projects
Building the Data Warehouse, W. H. Inmon Book Normalized enterprise data warehouse approach, compared with the dimensional approach Methods Specific to Data Projects
Data Vault (Dan Linstedt) Method Modeling with hubs, links, and satellites, suited to historization and integration of multiple sources PD Matrix — modeling
DAMA-DMBOK (Data Management Body of Knowledge, DAMA International) Framework Data management framework: governance, quality, metadata, security; current edition to be verified (a 2nd edition exists) PD Matrix
CRISP-DM 1.0 (Cross-Industry Standard Process for Data Mining, 2000) Process guide Six-phase cycle for data mining projects: business understanding, data understanding, preparation, modeling, evaluation, deployment Methods Specific to Data Projects
General Data Protection Regulation (GDPR) Regulatory text European legal framework for personal data; to be read in the official version, with guidance from the data protection officer PD Matrix — security and compliance
Data Management at Scale, Piethein Strengholt, and Data Mesh, Zhamak Dehghani Books Large-scale data architecture; domain-owned data products PD Matrix — governance

Power BI, Fabric, and SQL Server#

Reference Type What it provides In section
Microsoft Learn documentation — Power BI Official documentation Semantic models, DAX, RLS, deployment, capacities, administration; everything changes frequently, check the page date (status 2026-10) Cross-Cutting Power BI Good Practices
Microsoft Learn documentation — Microsoft Fabric (OneLake, lakehouse, warehouse, Direct Lake, mirroring) Official documentation Fabric architecture; several features change status (preview, general availability): verify again before making a decision OneLake + SaaS mobile apps: overview, Comparison — OneLake / Fabric vs Managed SQL Server for Power BI Reporting
Microsoft Learn documentation — Azure SQL Database, Azure SQL Managed Instance, and SQL Server Official documentation Service tiers, high availability, security, compatibility SQL Server in SaaS — Overview
Microsoft Learn documentation — Power BI Project (PBIP) and TMDL format Official documentation Text-based project format, model and report versioning BI Matrix — industrialization
SQLBI (Marco Russo and Alberto Ferrari) Reference site, books, and training DAX, modeling, optimization; The Definitive Guide to DAX is the reference book; DAX Studio and Tabular Editor are common tools in the ecosystem BI Matrix — DAX
Guy in a Cube (video channel), Power BI community Community resources Feedback and lessons learned on Power BI and Fabric; cross-check with official documentation Cross-Cutting Power BI Good Practices
Microsoft Learn documentation — Power BI: capacity planning and Capacity Metrics Official documentation Capacity consumption tracking and sizing BI Matrix — operations
SQL Server — Query Performance Tuning, Grant Fritchey Book Execution plans, statistics, T-SQL query optimization (edition to verify) BI Matrix — performance

Maturity and measurement#

Reference Type What it provides In section
CMMI (Capability Maturity Model Integration, CMMI Institute) Maturity model History of five-level maturity models; this Academy draws inspiration from it without reproducing it Maturity Matrices — Principle, Anatomy, and Comparison
Goodhart’s Law (common wording: “when a measure becomes a target, it ceases to be a good measure”) Principle Foundation for safeguards against misuse of indicators Self-Assessment with Maturity Matrices
How to Measure Anything, Douglas W. Hubbard Book Measuring what seems intangible; uncertainty and the value of information Project Metrics and Reporting
Thinking, Fast and Slow, Daniel Kahneman Book Cognitive biases in estimation and judgment, useful for understanding calibration Self-Assessment with Maturity Matrices — calibration

AI: responsible use#

Reference Type What it provides In section
European regulation on artificial intelligence (“AI Act”) Regulatory text European legal framework by risk level; phased implementation timeline, verify at the source (status 2026-10) Cross-Functional Summary — AI Contribution
NIST AI Risk Management Framework Framework Managing AI-related risks: govern, map, measure, manage Cross-Functional Summary — AI Contribution
OWASP — Top 10 for applications based on large language models Resource Risks specific to generative AI applications (prompt injection, information disclosure); the list is updated, check the version Cross-Functional Summary — AI Contribution
Assistant vendor documentation (terms of service, data policy) Documentation Data retention, use for training, location: to be reviewed for each selected tool Cross-Functional Summary — AI Contribution — confidentiality

How to use this list#

  • Beginner: Pro Git (if Git), The Scrum Guide (if Scrum), Microsoft Learn Power BI documentation for the fundamentals.
  • Practitioner: Accelerate, The Data Warehouse Toolkit, SQLBI for DAX, Azure DevOps documentation for TFVC and pipelines.
  • Expert: DAMA-DMBOK, Site Reliability Engineering, Team Topologies, regulatory texts (GDPR, AI regulation) with support from legal.
✅ Good practice

Date your reviews. For any online documentation (Microsoft Learn, Atlassian, AI vendors), note the reading date in your notes: content evolves, and this is the only way to explain later why a decision was made.

⚠️ Pitfall

Symptom: a rule applied by the team no longer matches current documentation (performance class, service level, license). Cause: a value read in an old book or report was frozen in place. Remedy: for any threshold or feature name, verify the most recent source before writing it into a policy.

🤖 AI

An assistant can help find and summarize references, but it sometimes invents plausible titles, authors, dates, or links. Verify each reference in a reliable source (publisher catalog, official website) before citing it.

See also#

✻ Written by Claude Sonnet 5.5