SQL
Advanced queries, analytics, execution plans, and performance tuning for massive retail datasets.
Published Guides
SQL Performance Tuning and Optimization: A Comprehensive Guide
Master SQL performance tuning techniques, execution plans, bind variables, and indexing strategies to optimize database queries. A complete guide to Oracle SQL performance optimization for developers and DBAs.
Data Modeling & Database Design Best Practices
Master relational data modeling, database design principles, normalization rules (1NF, 2NF, 3NF), Star Schemas, slowly changing dimensions (SCD), and the Entity-Attribute-Value (EAV) anti-pattern. A complete architectural guide for software engineers.
SQL Advanced: Window Functions, Ranking, Running Totals & CTEs
Master advanced SQL analytics — Window Functions (OVER, PARTITION BY), ranking functions (ROW_NUMBER, RANK, DENSE_RANK, NTILE), LAG/LEAD for period comparisons, running totals and moving averages with SUM/AVG OVER, and Common Table Expressions (CTE & Recursive CTE) with real-world Oracle and PostgreSQL examples.
SQL Intermediate: Joins, Aggregates, Subqueries, Functions, Views & Indexes
Master intermediate SQL concepts in one comprehensive guide — covering all JOIN types, aggregate functions (COUNT/SUM/AVG/MIN/MAX), GROUP BY, HAVING, subqueries, UNION/INTERSECT/EXCEPT, CASE statements, COALESCE/NULLIF/NVL, string/date/math functions, SQL Views, and Indexes. Packed with Oracle, MySQL, and PostgreSQL examples.
SQL Foundations: The Complete Beginner's Guide
Master SQL from zero — covering What is SQL, data types, DDL (CREATE/ALTER/DROP), DML (INSERT/UPDATE/DELETE), SELECT, WHERE, ORDER BY, DISTINCT, LIKE/IN/BETWEEN, NULL handling, operators, LIMIT, aliases, comments, and essential functions. Oracle, MySQL, and PostgreSQL examples throughout.
RC:OMS
Multi-channel order management with double-entry inventory ledger. Amazon, Flipkart, Shopify, WooCommerce — one source of truth.
Launch demo →RC:Storefront
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Visit Storefront →RC:Pulse
AI-powered retail analytics and demand forecasting — built natively on top of your RC:OMS and Storefront data.
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