SQL & Data Warehousing.
From theory to practice.

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Thread SQL & Data Warehousing 3 weeks ago

How do Window Functions (`ROW_NUMBER()`, `RANK()`, `LEAD()`, `LAG()`) improve complex analytical SQL queries?

Window functions compute rankings, offsets, and cumulative metrics in one pass, cutting I/O and eliminating self‑joins.

Rajesh Sharma Score 20

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Thread SQL & Data Warehousing 3 weeks ago

What is Data Vault 2.0 modeling and how does it compare to Kimball Dimensional Modeling?

Data Vault 2.0 captures raw events in Hubs/Links/Satellites for auditability, while Kimball builds star schemas for fast analytics; choose based on audit needs vs query speed.

Gaurav Bhasin Score 24

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Thread SQL & Data Warehousing 3 weeks ago

How to optimize SQL query execution plans for sub-second responses on multi-million row tables?

Combine covering/filtered indexes, proper MAXDOP, and targeted hints after profiling to achieve sub‑second queries on multi‑million‑row tables.

Aravind Patel Score 20

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Thread SQL & Data Warehousing 3 weeks ago

What are Slowly Changing Dimensions (SCD Type 1 vs Type 2 vs Type 3) in data warehouses?

Type 1 overwrites rows, Type 2 inserts versioned rows, and Type 3 keeps a single prior value in extra columns.

Rahul Sharma Score 20

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Thread SQL & Data Warehousing 3 weeks ago

How to write modular, testable data transformation pipelines using dbt (data build tool)?

Compose reusable dbt models, tests, and macros for modular, testable pipelines, then run incrementally with schema validation.

Ishaan Patel Score 20

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Thread SQL & Data Warehousing 3 weeks ago

What is the role of Data Lakes (Parquet, Delta Lake, Iceberg) alongside Data Warehouses?

Data lakes store raw data cheaply and provide versioned, schema‑on‑read access, while warehouses deliver fast, curated analytics on curated models.

Rajesh Sharma Score 20

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Thread PostgreSQL & Query Optimization 3 weeks ago

How do you interpret PostgreSQL `EXPLAIN (ANALYZE, BUFFERS)` query execution plans?

Interpreting PostgreSQL `EXPLAIN (ANALYZE, BUFFERS)` involves analyzing actual runtime statistics, buffer usage, and planner estimates to pinpoint query bottlenecks and I/O inefficiencies.

Gaurav Bhasin Score 24

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Thread PostgreSQL & Query Optimization 3 weeks ago

When should you use B-Tree, GIN, GiST, and BRIN indexes in PostgreSQL databases?

Choose B-Tree for general equality/range, GIN for full-text/array/JSONB containment, GiST for spatial/range types and k-NN, and BRIN for large, naturally ordered tables.

Aravind Patel Score 20

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Thread PostgreSQL & Query Optimization 3 weeks ago

How to optimize PostgreSQL autovacuum settings to prevent transaction ID wraparound and table bloat?

Optimize PostgreSQL autovacuum by tuning `autovacuum_vacuum_scale_factor`, `autovacuum_vacuum_threshold`, `autovacuum_freeze_max_age`, and `autovacuum_max_workers` globally and with table-specific overrides to prevent transaction ID wraparound and table bloat.

Rahul Sharma Score 20

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Thread PostgreSQL & Query Optimization 3 weeks ago

How to use declarative table partitioning in PostgreSQL 16 to accelerate historical time-series queries?

Leverage PostgreSQL 16's declarative `RANGE` partitioning on time-series data to accelerate historical queries by enabling efficient partition pruning, reducing I/O, and streamlining data management.

Ishaan Patel Score 20

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Thread PostgreSQL & Query Optimization 3 weeks ago

How to eliminate N+1 database query bottlenecks in Laravel applications using eager loading?

Eliminate N+1 query bottlenecks in Laravel by using Eloquent's `with()` method for eager loading, which fetches all associated data in a minimal number of optimized queries, significantly reducing database load and improving application performance.

Rajesh Sharma Score 20

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Thread PostgreSQL & Query Optimization 3 weeks ago

What is PgBouncer connection pooling and why is it necessary for high-concurrency web apps?

PgBouncer provides essential connection pooling for PostgreSQL, proxying connections to efficiently manage and reuse them, significantly reducing overhead and boosting scalability for high-concurrency web applications.

Gaurav Bhasin Score 24

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Thread Snowflake & BigQuery Pipeline 3 weeks ago

How do Snowflake Virtual Warehouses and BigQuery slots differ in cost and auto-scaling scaling models?

Snowflake uses per‑second credit warehouses with auto‑suspend and multi‑cluster scaling, while BigQuery bills slot‑seconds and scales via flex slots.

Aravind Patel Score 20

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Thread Snowflake & BigQuery Pipeline 3 weeks ago

How to implement zero-copy cloning and micro-partitioning in Snowflake for dev/staging environments?

Zero-copy cloning in Snowflake enables instant, space-efficient creation of dev/staging environments directly from production data without duplicating storage.

Rahul Sharma Score 20

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Thread Snowflake & BigQuery Pipeline 3 weeks ago

What are Partitioning and Clustering in BigQuery, and how do they reduce query costs by 90%?

BigQuery Partitioning segments tables by a column, while Clustering sorts data within partitions, both reducing query costs and improving performance by minimizing data scans, often by 90%.

Ishaan Patel Score 20

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