data
Practical resources about data for software engineers.
86 results
Understanding Data Processing in Software Engineering
Every application eventually deals with data — parsing user input, serializing objects for APIs, validating form submissions, or transforming records between formats. Getting data handling right is what separates fragile scripts from production-grade systems.
This collection covers practical recipes and patterns for working with JSON, CSV, XML, YAML, and custom formats. You will find copy-paste solutions for common tasks like flattening nested objects, sanitizing user input, generating slugs, and formatting dates across Python, Java, and JavaScript.
Recursive CTEs for Hierarchical Data Queries
How to query hierarchical data with recursive Common Table Expressions in SQL, covering tree...
Truncate Text
How to truncate text with ellipsis and word boundaries in Python, Java, and JavaScript.
URL Encoding
Encode and decode URLs, query parameters, and path segments safely across Python, JavaScript, and...
URL Encoding and Decoding
Master URL encoding in JavaScript and other languages with encodeURI, encodeURIComponent, plus-safe...
UUID Generation in Python, JavaScript, and Java
Generate universally unique identifiers (UUIDs) for database keys, session tokens, and resource...
UUID Generation: v4, v7, and ULID Comparison
Compare UUID v4, v7, ULID, and nanoid for generating unique identifiers with different tradeoffs in...
Validate JSON Schema
How to validate JSON data against schemas in Python, Java, and JavaScript.
Implement ACID Transactions in PostgreSQL
How to use PostgreSQL transactions to ensure Atomicity, Consistency, Isolation, and Durability for...
How to Use Elasticsearch Aggregations (With Examples)
Use Elasticsearch aggregations for faceted search, metrics, and time-series analytics. Step-by-step...
Export Data to CSV and Excel Files
How to export structured data to CSV and Excel files efficiently.
RAG Hybrid Search Pattern
Combine keyword (BM25) and semantic (vector) search to improve retrieval accuracy in RAG pipelines....
Batch-to-Streaming Bridge: One Lake for Both Pipelines
Merge batch ETL and real-time streaming into one queryable data lake. Lambda architecture with...
CDC Pattern: Stream Database Changes to Downstream
How to stream database changes to downstream consumers with CDC. Covers log-based CDC, Debezium,...
Data Lineage Tracking: Track Origin End-to-End
How to track data origin and transformations end-to-end. Covers column-level lineage, OpenLineage,...
ETL Extract-Transform-Load
How to build ETL pipelines with extract, transform, and load stages. Covers staging tables,...
Idempotent Load: Re-run Data Loads Safely Without Duplicates
How to re-run data loads safely without duplicates. Covers deduplication keys, MERGE upserts, load...
Schema Registry Evolution
How to manage schema versions for streaming pipelines with a schema registry. Covers Avro, backward...
Data Migration Runbook Template with Rollback Steps
Use this data migration runbook template to plan safe migrations. Includes pre-migration checks,...
Complete Guide to Kafka Stream Processing
Build real-time event streaming pipelines with Kafka. Covers producers, consumers, Kafka Streams,...
Data Lake vs Data Warehouse — Architecture Guide
A practical guide to Data Lake architecture: structured vs unstructured storage, lakehouse...
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