T0–T5 — Environment, SQL, PostgreSQL & DBeaver

These blocks build the minimum relational/workstation fluency needed for later Meridian labs. They are deliberately narrower than a database administrator or Data Engineer curriculum.

T0 — Workstation & Environment Literacy

Why: You need to understand where files/scripts live, how commands run, what a working directory is, and how a reproducible project is organized before technical labs become useful.

Learn

Windows paths vs project-relative paths.
Basic PowerShell navigation and file/folder commands.
VS Code: open folder/workspace, edit/save files, integrated terminal, extensions at a basic level.
Environment variables and why credentials should not be hard-coded.
File extensions and basic encoding awareness.
Difference between source files, generated outputs, evidence, and backups.

Readiness proof

Create a small project folder from scratch, navigate it in PowerShell, open it in VS Code, create/edit/run a simple text/script file, and explain where inputs and outputs live.

Stop boundary

Do not turn this into Windows administration, shell scripting specialization, or DevOps.

T1 — SQL Foundations I

Why: SQL is the strongest general technical priority because a governance/data-management professional needs to inspect structured data directly rather than rely only on screenshots or reports.

Learn

Tables, rows, columns and basic relational vocabulary.
SELECT and column selection.
WHERE filtering and comparison/logical operators.
Sorting and limiting results.
Null awareness and IS NULL / IS NOT NULL.
Basic distinct-value inspection.
Simple computed expressions/aliases.

Governance/Data Management uses

Inspect what data actually exists.
Verify whether required values are missing.
Test whether documented definitions match stored values.
Gather evidence before proposing a governance/quality response.

Readiness proof

Write a query from a blank editor that selects a requested subset of Meridian records using columns, filters, null tests, sorting and readable aliases; explain every clause.

Stop boundary

Do not chase vendor-specific optimization or advanced procedural SQL.

T2 — SQL Foundations II

Why: Governance questions often cross tables and require counts, comparisons, and relationships.

Learn

Primary-key / foreign-key meaning.
Inner and outer joins at practical depth.
GROUP BY and common aggregates.
HAVING vs WHERE at practical level.
Basic subquery/CTE literacy where it improves readability.
Duplicate detection patterns.
Referential-integrity inspection.
Basic views as reusable query interfaces.

Governance/Data Management uses

Reconcile systems/sources.
Check whether referenced records exist.
Compare counts across business definitions.
Find duplicate candidates.
Produce transparent evidence for quality/governance decisions.

Readiness proof

Join at least two Meridian tables, explain the grain before and after the join, aggregate results correctly, and diagnose a deliberately incorrect join that inflates counts.

Stop boundary

Do not move into query-plan tuning, warehouse engineering, or advanced SQL feature collecting merely for breadth.

T3 — SQL for Data Management

Timing: learned after Chapters 5–6 and before Chapter 7, not necessarily in the initial pre-Chapter-5 gate.

Why: Extends SQL from reading data to bounded governance/quality/security evidence and controlled relational changes.

Learn

Practical DDL: schemas/tables/keys/constraints.
Basic INSERT/UPDATE/DELETE with safe predicates and validation.
Transactions at a conceptual/practical level: begin, test, commit/rollback.
Views for controlled exposure/standardized logic.
Users/roles/privileges at the depth needed for Chapter 7 lab work.
Validation queries before/after changes.

Readiness proof

Create a small relational structure, enforce a meaningful constraint, make a controlled transaction, validate the result, and explain how the constraint/view/role supports a Data Management objective.

Stop boundary

Do not become a production DBA or database-security administrator.

T4 — PostgreSQL Practical Fluency

Why: PostgreSQL is the lab DBMS used to make relational structures, constraints, roles, views, transactions, operational behavior and warehouse objects real.

Learn

Connect to a local database and identify database/schema/table boundaries.
Create/use schemas and tables.
Understand data types at practical depth.
Apply primary/foreign keys and common constraints.
Inspect object definitions/metadata.
Work with views and basic transactions.
Use lab-safe roles/permissions when the chapter calls for them.
Back up/rebuild enough to make the training environment reproducible.

Readiness proof

Rebuild a small Meridian schema from source DDL, inspect the created objects, run validation queries and explain how the physical implementation maps to the logical design.

Stop boundary

No production clustering, replication administration, internals, deep tuning, HA engineering or large-scale operational specialization.

T5 — DBeaver Workbench Fluency

Why: DBeaver provides a visual workbench for examining relational objects and metadata while still keeping SQL visible.

Learn

Create/manage the lab connection.
Navigate database/schema/table/view objects.
Inspect columns, keys, constraints and DDL.
Open SQL editor and execute selected statements safely.
Inspect result sets and row counts.
Export bounded result evidence when needed.
Distinguish GUI convenience from the underlying database object/query.

Readiness proof

Given an unfamiliar Meridian table, use DBeaver to identify its schema, columns, key relationships and DDL; then write a query that validates something meaningful about the data.

Stop boundary

Do not treat GUI clicking as mastery. The learner must be able to explain the underlying database object and SQL logic.

Gate relationship

Before Chapter 5, the integrated 00C route requires the early foundation set T0 + T1 + T2 + T4 + T5 + T9 (Git). T3 is added before Chapter 7.

Source: Technology Competency Roadmap; Detailed Technology Competency Reference; 00C technology-gate logic.