Episode Details
Back to Episodes
Beyond SELECT: Why T-SQL Still Shapes Modern Data Strategy
Published 1 month, 3 weeks ago
Description
Most organizations believe modern platforms like Microsoft Fabric made SQL optional. This episode explains why that belief is dangerously wrong. T-SQL didn’t disappear—it moved upstream, into the layer where cost overruns, security drift, performance incidents, and audit findings are created long before anyone notices them. “Beyond SELECT” doesn’t mean beyond SQL; it means beyond responsibility. This episode reframes T-SQL as what it really is in modern data platforms: a contract language for enforcing intent—truth, access boundaries, and predictable compute—in systems that otherwise drift into entropy. If your cloud costs feel random, your dashboards disagree, or your security model depends on “temporary exceptions,” this episode explains why. What You’ll Learn 1. Why “Beyond SELECT” Is About Responsibility, Not Features Modern data stacks optimize for convenience and throughput, not intent. Without explicit relational contracts—schemas, constraints, permissions, and validation—data becomes negotiable, not deterministic. 2. How SQL Actually Executes (and Why It Breaks Expectations) SQL reads like English but executes like a compiler. Understanding true execution order explains:
- Why TOP doesn’t make queries cheaper
- Why joins multiply cost
- Why filtering late creates invisible IO bills
- Estimated vs actual plans
- Why scanned vs returned rows matter
- How spills, sorts, and join choices predict incidents
- Dirty data silently loads
- Fixes spread into Power BI, DAX, Power Query
- Multiple “truths” emerge
- Why parameter sniffing creates “random” slowdowns
- How cached plans turn historical samples into policy
- Trade-offs between recompilation, plan generalization, and branching
- Least privilege erodes
- Audit answers become vague
- Temporary access becomes permanent
- Trust erodes
- Performance degrades
- Audits become theater
- Indexing fixes access-path problems
- Partitioning enforces storage-level discipline
- Query tuning stops working and redesign is required
- Why AI-generated SQL accelerates entropy
- Common AI failure modes (non-sargable filters, bad joins, SELECT *)
- How execution plans become acceptance gates for AI output