

- Description
- Un dictionnaire ancien ouvert sur deux pages d'entrΓ©es et de traductions
- Source
- auteur non indiquΓ© Β· original page
- Licence
- PD Public domain
Glossary
This glossary defines more than 90 terms related to project management, development, source control, data, and BI. Each entry provides a short definition (π’) and linksβ¦
In brief
This glossary defines more than 90 terms related to project management, development, source control, data, and BI. Each entry provides a short definition (π’) and links to the file that explores it in depth (π‘/π΄). Acronyms are listed under their usual form. When a term has variants (Scrum βmasterβ or βfacilitator,β Import mode or DirectQuery), the definition uses common usage.
Level: π’βπ΄
A#
- Agile β Family of iterative approaches based on the Agile Manifesto (2001): deliver early and often, adapt to change, collaborate with the customer. It is not a method but a mindset applied through Scrum, Kanban, XPβ¦ β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- ALM (Application Lifecycle Management) β Management of an application's lifecycle: requirements, planning, code, testing, delivery, operations, within an integrated toolchain. Azure DevOps is a typical example. β Azure DevOps Server
- Artifact (Scrum) β Transparency object in the Scrum framework: Product Backlog, Sprint Backlog, and Increment, each tied to a commitment (Product Goal, Sprint Goal, Definition of Done). β Scrum, the framework (Scrum Guide 2020)
- Azure DevOps Server β Successor to Team Foundation Server (TFS): the on-premises installable version of Azure DevOps (work items, Git/TFVC repositories, pipelines, tests, artifacts). β Azure DevOps Server (ex-TFS) in Depth
- Partial achievement β Progress on a maturity milestone at 0, 0.5, or 1, which allows rating a level without requiring perfection. β RATING
B#
- Backlog β Ordered list of remaining work (Product Backlog: the product; Sprint Backlog: the current sprint). The order reflects value and risk, not age. β Scrum in Practice
- Big bang (delivery) β Go-live all at once, with no stages. Maximum risk, difficult rollback; opposite of incremental delivery. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- BI (Business Intelligence) β Set of techniques that transform operational data into decision indicators: warehouse, semantic model, reports. β BI Development Matrix
- Branch β Parallel development line in a version control system; in Git it is a simple lightweight pointer, in TFVC a logical copy of the folder. β Branching Strategies
- Burndown / burnup β Charts of remaining work (burndown) or completed work (burnup) over time; burnup makes scope changes visible. β Project Metrics and Reporting
- Build β Automated compilation and assembly step; for data, generation of a dacpac, an installation kit, or a report project. β CI/CD: Continuous Integration and Continuous Delivery
C#
- Cadence β Regular rhythm of events or deliveries (two-week sprint, monthly release). β Scrum in Practice
- Capacity (Fabric / Power BI) β Reserved compute resource (SKU F; P being phased out; A/EM) that runs models, notebooks, and pipelines; its sizing governs performance and cost. β Cost, Licensing, and Capacity (BI)
- Waterfall β Sequential lifecycle: requirements, design, implementation, testing, delivery. Effective when needs are stable and the cost of error is high. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- CD (Continuous Delivery / Deployment) β Continuous delivery: every validated change is deployable on demand (delivery) or automatically deployed (deployment). β CI/CD: Continuous Integration and Continuous Delivery
- Changeset (TFVC) β Atomic batch of changes stored in TFVC, numbered in increasing order; approximate equivalent of a commit, but centralized. β TFVC in Depth
- CI (Continuous Integration) β Frequent integration of everyone's work into a shared branch, validated by automated build and tests. β CI/CD: Continuous Integration and Continuous Delivery
- CMMI β Process maturity model with levels (1 to 5), predecessor of maturity matrices; distinct from the matrices in this section, which measure outcomes. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- Commit β Snapshot saved in Git, identified by a hash and a parent; the unit of history. β Git In Depth
- Data contract β Explicit agreement between producer and consumer on the schema, semantics, freshness, and quality of a dataset. β Data Sources and Contracts
- Change management β Human support for a change (training, communication, sponsors); a condition for report adoption. β Adoption and Change Management
- CRISP-DM β Data mining lifecycle in six phases (business understanding, data understanding, preparation, modeling, evaluation, deployment), version 1.0 from 2000. β Methods Specific to Data Projects
- V-model β Waterfall variant where each design phase has a symmetric testing phase. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- Cycle time β Duration between the actual start of work on an item and its completion; not to be confused with lead time. β Project Metrics and Reporting
D#
- dacpac β SQL Server data-layer package (database schema) used to compare and deploy declaratively. β CI/CD for data: foundations, datamarts, pipelines, and reports
- DAX (Data Analysis Expressions) β Formula language for the tabular model (Power BI, Analysis Services): measures, calculated columns, calculated tables. β DAX Measures and Calculations
- Data lineage β See Lineage.
- Data warehouse / warehouse β Integrated, historized database organized by subject, dedicated to analysis. β Modeling and Architecture
- Datamart β Thematic subset of a warehouse, often modeled as a star schema, serving a business domain (sales, readings). β Modeling and Architecture
- Dataflow Gen2 β Low-code Power Query transformation in Fabric that writes to a lakehouse or a warehouse. β OneLake β architecture
- DataOps β Application of DevOps practices (versioning, testing, CI/CD, monitoring) to data pipelines. β Lead Time and Industrialization (DataOps)
- Definition of Done (DoD) β Shared criteria that make an item βdoneβ (tested, reviewed, documented, deployable); commitment of the Increment. β Scrum, the framework (Scrum Guide 2020)
- Definition of Ready (DoR) β Conditions for an item to enter a sprint (clear, estimated, testable); useful practice but absent from the Scrum Guide. β Scrum in Practice
- Technical debt β Future cost caused by present shortcuts (duplicated code, missing tests, outdated documentation). β Technical Debt and Maintainability
- DevOps β Culture and practices that bring development and operations closer to deliver fast and reliably: automation, fast feedback, shared responsibility. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- Direct Lake β Power BI/Fabric mode that reads Delta files directly from the lakehouse in OneLake, without import; the SQL endpoint variant can fall back to DirectQuery. β OneLake β architecture
- DirectQuery β Mode where each visual queries the source live: maximum freshness, performance dependent on the source. β Comparison β OneLake / Fabric vs Managed SQL Server for Power BI Reporting
- DORA (metrics) β Four delivery performance measures from DORA research (book Accelerate): deployment frequency, lead time for production, change failure rate, time to restore; the DORA 2024 model adds deployment rework rate and refers to time to restore after a failed deployment. β Project Metrics and Reporting
- DSDM β Agile method with variable scope and fixed time (time-boxing). β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
E#
- ELT / ETL β Extract, transform, load (ETL) or extract, load, transform in the target (ELT). The latter dominates with cloud engines. β Data Layer and ETL
- Epic β Large body of work broken down into user stories across multiple sprints. β Scrum in Practice
- Estimation (story points) β Relative effort assessment, not in hours; used for forecasting, not for evaluating people. β Planning and Estimation (PLA)
- Star (schema) β Dimensional model: one fact table surrounded by dimensions; foundation of any solid semantic model. β Semantic Model
- Eventstream β Fabric feature for capturing and routing real-time event streams. β OneLake β architecture
F#
- Fabric (Microsoft Fabric) β Microsoft's unified SaaS analytics platform (OneLake, lakehouse, warehouse, pipelines, Power BI, real time). Evolving offering (status 2026-10): check GA/preview status for each feature. β OneLake + SaaS Mobile Apps: Overview
- Feature flag β Switch that enables or disables a feature without redeploying; decouples deployment and release. β CI/CD: Continuous Integration and Continuous Delivery
- Merge (merge) β Integration of changes from one branch into another; the difficulty lies in conflicts, especially in model files. β Git In Depth
- Flow (flow, Kanban) β Continuous movement of work; managed through work-in-progress limits and throughput. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
G#
- VCS (version control system) β See SCM. A system that keeps file history and coordinates parallel work (Git, TFVC). β Overview of Version Control Systems
- Git β Distributed VCS: each clone contains the full history; lightweight branches, frequent merges. β Git In Depth
- Data governance β Roles, rules, and processes that ensure data ownership, quality, security, and compliant use. β Data Governance and Organization
- Gated check-in β TFVC control where check-in is accepted only if a build succeeds. β TFVC in Depth
H#
- Hybrid (method) β Deliberate combination of predictive and agile elements (waterfall framing, iterative delivery). β Choosing Your Method and Hybridizing
- Hotfix β Urgent fix applied to a production version, then carried over to the development branch. β Branching Strategies
I#
- Generative AI / LLM β Language models used as assistants (code, SQL, DAX, documentation, review). Real gains, real limits: hallucinations, privacy. β Cross-Functional Summary β AI Contribution
- Idempotence β Property of a process that, when rerun, produces the same result; foundation of safe load replay. β CI/CD for data: foundations, datamarts, pipelines, and reports
- Import (mode) β Mode where data is copied into the in-memory model: fast in use, refresh must be scheduled. β Comparison β OneLake / Fabric vs Managed SQL Server for Power BI Reporting
- Increment β Concrete, usable outcome, accumulated at the end of a sprint. β Scrum, the framework (Scrum Guide 2020)
- Iteration β Short work loop that produces a verifiable outcome (sprint, timebox). β Project Management Fundamentals
J#
- Milestone (maturity) β Precise, verifiable criterion for a matrix level, with its stable identifier (e.g., PI-RSK-3.2). β RATING
- Jira β Atlassian ticket and project tracking tool, highly configurable. β Jira In Depth and Alternatives
K#
- Kanban β Flow management method: visualize work, limit work in progress, measure, improve. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- Kimball (method) β Dimensional modeling approach (The Data Warehouse Toolkit): business processes, grain, dimensions, facts. β Modeling and Architecture
- Installation package β Versioned, replayable set of scripts that installs or updates a database for a client. β Source Control for Data: SQL and Power BI
- KPI β Key performance indicator; useful only with a definition, a source, and an owner. β Project Metrics and Reporting
L#
- Lakehouse β Architecture that combines the flexibility of a file lake with the transactional tables of a warehouse (Delta tables). β OneLake + SaaS mobile apps: architecture
- Lead time β Total time between request and delivery; measures what the customer perceives. β Project Metrics and Reporting
- Lean β Philosophy from industry: eliminate waste, decide at the last responsible moment, deliver fast. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- Lineage β Traceability of data from source to visual: where it comes from, what it went through. β Metadata, Lineage, and Documentation
- Lineage tag β Internal identifier of a Power BI model object; changing it breaks the link with reports. β Versioning and Industrialization of Reports
M#
- Maturity matrix β Themes Γ five levels grid; each level is defined by a promise and verifiable milestones. β Maturity Matrices β Principle, Anatomy, and Comparison
- Medallion (bronze/silver/gold) β Layered lakehouse organization: raw, cleaned, analysis-ready. β OneLake + SaaS mobile apps: architecture
- Merise β French information systems design method (MCD, MLD, MPD). β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- Metadata β Data about data: definitions, owners, types, lineage. β Metadata, Lineage, and Documentation
- Mirroring (Fabric) β Continuous replication of an operational database to OneLake, without writing a pipeline. β SQL Server in SaaS β architecture
- Semantic model β Business layer of a Power BI report: tables, relationships, hierarchies, measures, security. β Semantic Model
- MTTR β Mean time to restore after an incident; resilience metric. β Observability and Reliability
- MVP (minimum viable product) β Smallest version that allows learning from the market; not to be confused with a throwaway prototype. β Project Management Fundamentals
N#
- Maturity level β From 1 to 5: each level describes an observable outcome, not a means. β RATING
- NFR (non-functional requirements) β Performance, security, availability, accessibility: often forgotten during framing. β Scope and Requirements Management (PER)
O#
- OneLake β Fabricβs single logical data lake, in open Delta/Parquet format, βOneDrive for data.β β OneLake + SaaS Mobile Apps: Overview
- OKR β Objectives and key results: framework for aligning priorities. β Governance and Steering (GOU)
P#
- PaaS / SaaS β Managed platform (Azure SQL Database: you manage data, not the server) versus complete software (Power BI service, Fabric). β SQL Server in SaaS β overview
- PBIP / TMDL β Power BI project format in text files (PBIP) and model description language (TMDL): versionable and mergeable. β Versioning and Industrialization of Reports
- Pipeline (data) β Orchestrated chain that moves and transforms data. β CI/CD for data: foundations, datamarts, pipelines, and reports
- PMBOK β PMI project management guide: processes, performance domains. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- Power BI β Microsoft BI suite: Desktop (authoring), service (publishing), semantic model, reports. β Cross-Cutting Power BI Good Practices
- PRINCE2 β Project management method structured by stages, roles, and continuous business justification. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
- Product Owner β Accountable for product value and Product Backlog ordering. β Scrum, the framework (Scrum Guide 2020)
- Pull request β Request to merge a Git branch with code review. β Git In Depth
Q#
- Data quality β Fitness of data for use: accuracy, completeness, consistency, freshness, uniqueness, validity. β Data Quality
- Quality gate β Automatic threshold to pass (tests, coverage, static analysis) before proceeding. β CI/CD: Continuous Integration and Continuous Delivery
R#
- Rebase β Rewriting a Git branch onto another base to linearize history. β Git In Depth
- Acceptance testing β Delivery validation by the business: for data, reconciliation of figures against a reference. β Acceptance testing and business validation
- Refactoring β Improving code structure without changing behavior. β Code Quality
- Retrospective β Scrum event for improving how the team works. β Scrum in Practice
- GDPR β European regulation for personal data protection: minimization, legal basis, data subject rights. β Security, Privacy, Compliance
- RLS (Row-Level Security) β Row-level security: a user sees only rows in their scope (region, customer). β RLS Security and Access
- RUP β Rational Unified Process: iterative method driven by use cases. β Predictive Methods (waterfall, V-model, spiral, RUP, PMBOK, PRINCE2, Merise, CMMI)
S#
- SAFe β Agile scaling framework (trains, PI Planning). β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- SCD (Slowly Changing Dimension) β Dimension historization technique (type 1: overwrite; type 2: version). β Modeling and Architecture
- SCM β Source Code Management, synonymous with VCS. β Overview of Version Control Systems
- Scrum β Sprint-based agile framework, three accountabilities (Product Owner, Scrum Master, Developers), five events, three artifacts. β Scrum, the framework (Scrum Guide 2020)
- Scrum Master β Ensures the effectiveness of the framework and the team, not a project manager. β Scrum in Practice
- SFA (Sales Force Automation) β Sales force automation application, a typical source for this section's common thread. β OneLake + SaaS Mobile Apps: Overview
- Shape Up β Six-week cycle method with betting and βappetite.β β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- Shelveset (TFVC) β Set-aside of uncommitted changes, shareable for review. β TFVC in Depth
- Shortcut (OneLake) β Shortcut that exposes external data in OneLake without copying it. β OneLake + SaaS mobile apps: architecture
- Sprint β Fixed-length period (one month max) that produces an increment. β Scrum, the framework (Scrum Guide 2020)
- SSDT β SQL Server Data Tools: versionable database projects, dacpac generation. β Source Control for Data: SQL and Power BI
- Branching strategy β Convention for branch usage (trunk-based, GitFlow, release branches). β Branching Strategies
T#
- TDD β Test-Driven Development: write the test before the code. β Testing
- TFVC β Team Foundation Version Control: Microsoftβs centralized VCS, optional locks, changeset-based history. β TFVC in Depth
- Trunk-based development β Daily integration into a main branch, very short-lived branches. β Branching Strategies
U#
- User story β Need expressed from the userβs point of view, with acceptance criteria. β Scrum in Practice
V#
- Velocity β Quantity of items (points) completed per sprint; a team forecasting tool, never for cross-team comparison. β Project Metrics and Reporting
- Lock-in β Dependency on a vendor that increases exit costs; an architecture selection criterion. β Comparison β OneLake / Fabric vs Managed SQL Server for Power BI Reporting
W#
- WIP (Work In Progress) β Work in progress: started but unfinished items; limiting it reduces lead times. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
- Work item β Azure DevOps work item (task, bug, user story). β Azure DevOps Server (ex-TFS) in Depth
X#
- XP (Extreme Programming) β Agile engineering practices: TDD, pair programming, continuous integration, refactoring. β Agile and Lean Methods (Manifesto, Kanban, XP, Lean, Shape Up, DSDM, SAFe, DevOpsβ¦)
See also#
- Rating: Reading Ratings, Scores, and the Legend Β· Reading Paths Β· Portal
- Bibliography and Resources
β» Written by Claude Sonnet 5.5