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SKU/Artículo: AMZ-B0G37Z3KKK
MASTERING T-SQL IN SQL SERVER: THE COMPLETE DATABASE GUIDE: QUERY, DEVELOP, AND BUILD AI APPLICATIONS WITH T-SQL. NATIVE VECTOR SEARCH, JSON, REGULAR EXPRESSIONS, AND PRODUCTION DATABASE DEVELOPMENT
Format:
Hardcover
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.70 kg
0.70 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Build faster, safer, and more capable SQL Server systems by mastering modern T-SQL from core querying through AI-ready vector search.Many developers can write queries that work, but struggle when data grows, workloads mix OLTP and reporting, and new requirements like JSON, regex text processing, and semantic search arrive. The result is fragile code, slow performance, and features that are hard to ship confidently.This guide helps you move past that ceiling. You will learn how SQL Server executes T-SQL, how to model real systems, and how to write production queries that stay correct and predictable under pressure, including native vector search workflows for AI applications.select filter sort and paginate results with clear intent and stable performancewrite reliable joins subqueries and apply patterns for real retrieval problemsuse grouping aggregation and window functions for analytics and reportingchoose data types that protect correctness and improve execution plansbuild expressions and conditional logic that stay readable and sargablework confidently with dates times and time series functionsdesign stored procedures and user defined functions for reusable logiccontrol transactions isolation levels and concurrency in multi user systemshandle errors with try catch throw and xact safe patternsread execution plans design indexes and use query store to spot regressionsapply intelligent query processing and handle parameter sensitive plansmodel schemas that survive growth including partitioning and archival strategiesclean parse and validate text with string functions and native regex supportstore vectors run exact and approximate similarity search and index embeddingsdesign embedding tables that connect semantic results to business dataprepare chunked data implement semantic search and build rag pipelines with external modelssecure databases with authentication authorization row level security and auditingprotect data with encryption backup restore and high availability planningmanage the database lifecycle with dacpacs testing and ci cd for sql server and azure sqlavoid common query and schema anti patterns and ship with a production checklistThroughout the book you will find working T-SQL patterns and scripts that you can adapt directly into your own projects, from day to day querying to vector based semantic search.Grab your copy today and start writing T-SQL that holds up in production and supports modern AI features.
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S/ 410.18
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S/ 164.06
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