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Tools: Version Control Systems, Planning, and Oversight

This section covers the tools that support a project's traceability: version control systems (VCS), planning and tracking, metrics, AI.

Guide≈ 3 min readCheckedCheck doneFacts, figures and references were checked against the sources cited in the page.Written with AI assistance; sources are cited at the bottom of the page. An error? Report it via clement13.net.Reading
In brief
  • This section covers the tools that support a project's traceability: version control systems (VCS), planning and tracking, metrics, AI.
  • The first half (files 01 to 06) covers version control in depth: concepts, Git, TFVC, comparison, branching strategies, application to SQL and Power BI data.
  • The second half (07 to 12) covers planning, Azure DevOps, Jira, metrics, AI, and tool comparison.
  • Illustrative anonymous thread: a SQL Server datamart fed by a field sales force automation (SFA) application, with multilingual Power BI reports, versioned in TFVC and delivered as installation kits.
  • The /5 scores are contextual expert assessments: see RATING.
On this page
  1. Files in this section
    1. Version control (files 01 to 06)
    2. Planning, oversight, AI (files 07 to 12)
  2. Where to start
  3. Reading path by profile
  4. Version control in one page
  5. Frequently asked questions
  6. Links with the rest of this section
  7. See also

Level: 🟢→🔴

Files in this section#

Version control (files 01 to 06)#

File Content Level
01 — Version Control Systems Overview Concepts (centralized/distributed, locking/merging), history CVS → Git, objects, hashing, snapshots vs deltas, how to choose 🟢→🟡
02 — Git In Depth Object model, index, refs, reflog, merge/rebase/cherry-pick, bisect, hooks, LFS, partial clone, secrets, pitfalls, AI 🟢→🔴
03 — TFVC In Depth Workspaces, changesets, shelvesets, branches, policies, tf.exe, .tfignore, sustainability 🟢→🔴
04 — Git vs TFVC Rated comparison, scenarios, migration with history, coexistence, step-by-step plan 🟡→🔴
05 — Branching Strategies Trunk-based, GitFlow, GitHub Flow, branches by version, TFVC Main/Dev/Release, ratings by context 🟡→🔴
06 — VCS and SQL / BI data Versioning SQL (state vs migration), PBIP/PBIR/TMDL, encodings, .gitattributes, kits, tags 🟡→🔴

Planning, oversight, AI (files 07 to 12)#

File Content
07 — Planning tools Overview of planning and tracking tools
08 — Azure DevOps / TFS in depth Boards, Repos, Pipelines, Artifacts, Test Plans, administration
09 — Jira and alternatives Jira and market alternatives
10 — Project metrics and reporting Velocity, flow, DORA, dashboards
11 — AI and tools AI applied to project tooling
12 — Tool comparison Rated overview

Where to start#

You are… Start with Then
Junior, never trained on a VCS 01 (novice sections) 02 🟢 sections
TFVC developer who needs to “move to Git” 04 02, 05
Git developer inheriting a TFVC repository 03 04
BI/SQL developer who wants proper versioning 06 05
Team lead / architect 04 and 05 01 “choosing” section

Reading path by profile#

01 Overview02 Git03 TFVC04 Git vs TFVC05 Branches06 SQL and BI
Hover over or tap an element to read its details.

An express 90-minute path for an already experienced reader: the “Expert” sections of 03 (sustainability status), all of 04 (comparison and migration plan), then the “Versioning Power BI” and “Encodings” sections of 06.

Version control in one page#

A VCS answers four questions: who changed what, when, and why. It also lets you roll back, work as a team without overwriting each other, and deliver a specific version (a tag, a label, a release branch). In a data project, three specifics change the general answer:

  1. The “sources” are mixed in nature: SQL scripts, semantic models (TMDL), report definitions (JSON), PowerShell scripts, documentation, and sometimes binaries.
  2. Encoding and line endings matter: a corrupted accent in a multilingual label is a defect delivered to the client.
  3. Deployment is not a git pull: you deliver replayable installation kits, which requires idempotence and version traceability (see CI/CD for Data: Databases, Datamarts, Pipelines, and Reports).
💡 Expert tip

Tool choice (Git, TFVC) matters less than the discipline around it: branch conventions, reviews, release tags, commit hygiene. A disciplined team on TFVC outperforms a ruleless team on Git.

Frequently asked questions#

  • Is TFVC “dead”? No, but Git gets the investment and is recommended for new projects (status 2026-10, details in 03).
  • Can Git be used locally on top of a TFVC repository? Yes, this is a real coexistence practice, with limitations: see 04.
  • How do you version Power BI? PBIP format (TMDL + PBIR), see 06.
  • What does AI do for VCS? Commit messages, review, history explanation, conflict assistance: AI sections in 02, 04, and 06.

Links with the rest of this section#

See also#

Next: 01 — Version Control Systems Overview →

✻ Written by Claude Sonnet 5.5