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Digital Planet
Digital Planet
Apr 21, 2026 · Industry Insights

Why Fake Data Plagues FMCG and How Tech & Management Can Fix It

The fast‑moving consumer goods sector is drowning in fabricated numbers caused by KPI pressure, lack of differentiated targets, and weak oversight, but a combination of five‑in‑one codes, AI verification, closed‑loop system integration, open communication, and accountable leadership can restore data integrity and enable true digital transformation.

AI verificationDigital TransformationFMCG
0 likes · 12 min read
Why Fake Data Plagues FMCG and How Tech & Management Can Fix It
37 Interactive Technology Team
37 Interactive Technology Team
Jan 14, 2026 · Frontend Development

Hidden Zero‑Width Characters: How They Sabotage Front‑End Apps and How to Detect Them

Zero‑width characters are invisible Unicode symbols that can silently break form validation, URL parsing, and data storage in web applications, but with proper detection, visualization, and input‑filtering techniques developers can mitigate these hidden risks and even use them for legitimate purposes.

DebuggingUnicodedata integrity
0 likes · 6 min read
Hidden Zero‑Width Characters: How They Sabotage Front‑End Apps and How to Detect Them
Lobster Programming
Lobster Programming
Jul 28, 2025 · Databases

How MySQL’s Double Write Buffer Prevents Partial Write Failures

This article explains why MySQL data pages can suffer partial write failures during crashes, how the mismatch between InnoDB and OS page sizes contributes to the problem, and how the Double Write Buffer mechanism safeguards data integrity by providing a recoverable copy of each page.

Database RecoveryDouble Write BufferInnoDB
0 likes · 7 min read
How MySQL’s Double Write Buffer Prevents Partial Write Failures
ITPUB
ITPUB
May 23, 2025 · Databases

Why Storing 2 Billion Phone Numbers Requires VARCHAR(20) Over INT/BIGINT

When designing a database for billions of phone numbers, using INT or BIGINT leads to overflow, data‑integrity loss, and inefficient queries, while VARCHAR(20) preserves formatting, supports international extensions, simplifies validation, and avoids common development pitfalls.

Database designSQLdata integrity
0 likes · 10 min read
Why Storing 2 Billion Phone Numbers Requires VARCHAR(20) Over INT/BIGINT
Architect
Architect
May 17, 2025 · Databases

Storing 2 Billion Phone Numbers: Why VARCHAR(20) Is Preferable to INT/BIGINT

The article explains why using a VARCHAR(20) column to store billions of phone numbers is safer and more flexible than INT or BIGINT, covering range limits, data integrity, query convenience, interview expectations, and common pitfalls such as insufficient field length, charset issues, missing indexes, and lack of encryption.

BIGINTSQLdata integrity
0 likes · 10 min read
Storing 2 Billion Phone Numbers: Why VARCHAR(20) Is Preferable to INT/BIGINT
Deepin Linux
Deepin Linux
Nov 1, 2024 · Fundamentals

Will Data Be Lost When a Process Crashes During File Write?

This article examines the conditions under which data may be lost when a Linux process crashes while writing a file, explaining page cache behavior, the roles of stdio versus system calls, dirty page handling, write‑back mechanisms, and strategies such as fflush, fsync, and direct I/O to ensure data integrity.

Linuxdata integrityfile I/O
0 likes · 22 min read
Will Data Be Lost When a Process Crashes During File Write?
Java Architecture Stack
Java Architecture Stack
Sep 25, 2024 · Databases

When to Use NOT NULL vs NULL in Database Design: Practical Guidelines

This article explains when to use NOT NULL versus NULL in relational database schemas, covering required fields, optional columns, unknown‑state representation, foreign keys, performance impact, versioning, data analysis, migration, default values and JSON types, with concrete SQL examples and practical guidance.

JSONSQLdata integrity
0 likes · 13 min read
When to Use NOT NULL vs NULL in Database Design: Practical Guidelines
FunTester
FunTester
May 19, 2024 · Databases

Essential Database Testing Checklist: From CRUD to Performance Optimization

This guide outlines comprehensive database testing practices, covering relational and non‑relational types, CRUD validation, index and view checks, empty‑database scenarios, data integrity, design principles, stress testing, and detailed SQL optimization techniques with concrete examples and code snippets.

Design GuidelinesPerformance TestingSQL Optimization
0 likes · 12 min read
Essential Database Testing Checklist: From CRUD to Performance Optimization
vivo Internet Technology
vivo Internet Technology
Jan 24, 2024 · Big Data

Evolution of Vivo's Trillions-Scale Data Architecture: Dual-Active Real-Time and Offline Computing

Vivo’s trillion‑scale data platform evolved into a dual‑active real‑time and offline architecture that leverages multi‑datacenter clusters, Kafka/Pulsar caching, a unified sorting layer, HBase‑backed dimension tables, and micro‑batch Spark jobs to deliver low‑cost, high‑performance processing, 99.9% availability, and 99.9995% data‑integrity.

Data ArchitectureHBaseOffline Computing
0 likes · 16 min read
Evolution of Vivo's Trillions-Scale Data Architecture: Dual-Active Real-Time and Offline Computing
DataFunTalk
DataFunTalk
Jan 17, 2023 · Information Security

Community Anti‑Cheat Exploration and Practice in Xiaohongshu

This article examines Xiaohongshu's community anti‑cheat efforts, detailing the significance of fraud prevention, the black‑gray industry ecosystem, strategic defense frameworks, system architecture, and practical risk governance and detection methods for data‑inflation attacks.

Securityanti-cheatcommunity
0 likes · 15 min read
Community Anti‑Cheat Exploration and Practice in Xiaohongshu
IT Architects Alliance
IT Architects Alliance
Jan 13, 2023 · Databases

Database Design Fundamentals: Key Concepts, ER Diagrams, and Normal Forms

This article explains fundamental database design concepts, including candidate and primary keys, attributes, relations, ER diagram components, and detailed descriptions of the first, second, third, and BC normal forms with examples and how to resolve insertion, deletion, update, and redundancy anomalies.

Database designER Diagramdata integrity
0 likes · 9 min read
Database Design Fundamentals: Key Concepts, ER Diagrams, and Normal Forms
FunTester
FunTester
Nov 8, 2022 · Databases

Comprehensive Guide to Database Testing: Concepts, Techniques, and Best Practices

Database testing ensures data integrity, security, and quality by validating data mapping, ACID properties, schema, triggers, stored procedures, and field constraints through both manual and automated methods, using SQL queries, CRUD operations, and specialized tools to verify that applications interact correctly with underlying databases.

ACIDSQLTriggers
0 likes · 13 min read
Comprehensive Guide to Database Testing: Concepts, Techniques, and Best Practices
dbaplus Community
dbaplus Community
Oct 3, 2022 · Databases

Why MySQL Unique Indexes Still Allow Duplicates and How to Fix Them

This article explains why a MySQL InnoDB table with a unique index can still contain duplicate rows—especially when indexed columns contain NULL values or when logical deletion is used—and presents several practical strategies, including schema changes and alternative locking mechanisms, to enforce true uniqueness.

Database designLogical DeleteUnique Index
0 likes · 13 min read
Why MySQL Unique Indexes Still Allow Duplicates and How to Fix Them
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 2, 2021 · Fundamentals

Why Data Loss Happens: Hidden Bit Flips and How to Prevent Them

This article explains the concepts of data loss and corruption, defines "data not lost" and "data not wrong", examines common bit‑flip sources in disks, memory, and networks, explores silent CPU errors, and presents design, detection, and recovery strategies for reliable storage systems.

Hardware ReliabilityStorage Systemsbit flip
0 likes · 17 min read
Why Data Loss Happens: Hidden Bit Flips and How to Prevent Them
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 2, 2021 · Fundamentals

Why Data Loss Happens: Hidden CPU Silent Errors and How to Prevent Them

This article explains the concepts of data loss and corruption, outlines common bit‑flip sources in disks, memory, network and CPUs, describes how silent CPU data errors are discovered and verified, and presents multi‑layer design strategies—including redundancy, checksums, logging and recovery—to ensure data is neither lost nor corrupted.

CPU SDEStorage Reliabilitydata integrity
0 likes · 17 min read
Why Data Loss Happens: Hidden CPU Silent Errors and How to Prevent Them
php Courses
php Courses
May 19, 2021 · Databases

Fundamentals of Relational Databases: Key Concepts and Common Questions

This article provides a comprehensive overview of relational database fundamentals, covering common DBMS products, SQL language components, integrity constraints, transactions, locking, views, stored procedures, indexes, normalization, key differences, constraints, optimization techniques, storage engines, and performance strategies for high‑traffic sites.

Database OptimizationRelational DatabaseTransactions
0 likes · 12 min read
Fundamentals of Relational Databases: Key Concepts and Common Questions
Architecture Digest
Architecture Digest
Feb 26, 2021 · Databases

Adding a Column to a Massive MySQL Table Safely

This article explains practical strategies for adding a new column to a MySQL table with tens of millions of rows, including creating a temporary table, copying data, renaming tables, and alternative replica‑based or third‑party methods to avoid long locks and potential crashes.

Large TableSchema Migrationadd column
0 likes · 4 min read
Adding a Column to a Massive MySQL Table Safely
Liangxu Linux
Liangxu Linux
Jan 25, 2021 · Fundamentals

How Journaling File Systems Prevent Data Corruption After Crashes

This article explains why file writes are non‑atomic, illustrates the risks of partial writes, and details how journaling (write‑ahead logging) and its variants—data and metadata journaling—ensure filesystem consistency and performance on Linux systems.

Ext3FilesystemLinux
0 likes · 8 min read
How Journaling File Systems Prevent Data Corruption After Crashes
MaGe Linux Operations
MaGe Linux Operations
Dec 1, 2020 · Fundamentals

Why Journaling Keeps File Systems Safe: Write-Ahead Logging Explained

File systems risk data corruption during power loss or crashes because writes are not atomic, so journaling—recording intended operations in a write‑ahead log before committing them—ensures metadata and user data consistency, with variations like data journaling and ordered (metadata) journaling improving performance and reliability.

Write-Ahead Loggingdata integrityjournaling
0 likes · 6 min read
Why Journaling Keeps File Systems Safe: Write-Ahead Logging Explained
Alibaba Cloud Native
Alibaba Cloud Native
Oct 26, 2020 · Cloud Native

How Nydus Accelerates Container Image Delivery and Boosts Data Security

Nydus, an open‑source container image acceleration service built on Dragonfly, dramatically reduces image download time, enables on‑demand image loading, provides block‑level deduplication and end‑to‑end data integrity verification, and integrates seamlessly with OCI standards and cloud‑native ecosystems.

ContainerNydusOCI
0 likes · 10 min read
How Nydus Accelerates Container Image Delivery and Boosts Data Security
Tencent Cloud Developer
Tencent Cloud Developer
Jul 2, 2020 · Blockchain

An Overview of Blockchain Technology, Value, and Applications by Tencent Cloud

The article explains blockchain as a decentralized, tamper‑proof distributed ledger built from a peer‑to‑peer network, block structure, consensus, cryptography and smart contracts, outlines its evolution from information to value internet, classifies public, consortium and private chains, and details Tencent Cloud’s BaaS platform, Zhixin Chain evidence services, and various technical solutions and use‑cases such as data integrity, supply‑chain traceability and asset tokenization.

BlockchainConsensuscloud blockchain
0 likes · 29 min read
An Overview of Blockchain Technology, Value, and Applications by Tencent Cloud
360 Quality & Efficiency
360 Quality & Efficiency
Oct 17, 2019 · Fundamentals

Why URL Encoding Is Essential for Reliable Web Requests

This article explains why URLs and their parameters must be encoded during testing, covering readability, completeness, reserved characters, non‑ASCII symbols, and unsafe characters, and provides practical examples to ensure reliable data transmission and correct parameter parsing.

HTTPURL encodingdata integrity
0 likes · 4 min read
Why URL Encoding Is Essential for Reliable Web Requests
DataFunTalk
DataFunTalk
Jun 6, 2019 · Artificial Intelligence

Design and Machine Learning Practices for Automotive Finance Risk Control

This article outlines the end‑to‑end design of automotive finance risk‑control processes, discusses key data integrity and customer segmentation considerations, and details machine‑learning modeling practices—including logistic regression, decision trees, GBDT, XGBoost, LightGBM and CatBoost—along with an automated platform to streamline model development and deployment.

Credit ScoringGBDTXGBoost
0 likes · 17 min read
Design and Machine Learning Practices for Automotive Finance Risk Control
Aikesheng Open Source Community
Aikesheng Open Source Community
May 6, 2019 · Databases

How MySQL Finally Supports CHECK Constraints and Why It Matters for Data Integrity

This article explains why MySQL lacked CHECK constraints for years, demonstrates the data quality issues caused by missing checks, shows how to work around them with unsigned types, and provides step‑by‑step examples of using the new CHECK constraint in MySQL 8.0.16+ while highlighting its absence in earlier versions.

CHECK constraintDomain integritySQL
0 likes · 6 min read
How MySQL Finally Supports CHECK Constraints and Why It Matters for Data Integrity
Architects' Tech Alliance
Architects' Tech Alliance
Jun 23, 2018 · Fundamentals

ZFS File System: Architecture, Features, and Variants

This article reviews the history of Sun and Solaris, explains ZFS’s core design as a combined file system and volume manager, and details its key features such as metadata integrity, copy‑on‑write, snapshots, clones, storage pools, RAID‑Z, caching, compression, deduplication, and tunability.

Copy-on-WriteRAID-ZZFS
0 likes · 11 min read
ZFS File System: Architecture, Features, and Variants
ITPUB
ITPUB
Mar 3, 2017 · Fundamentals

What Really Happens to Files and Disks During a Power Outage?

When power is lost mid‑write, the write command, device caches, and ordering become uncertain, and file systems employ various strategies—ranging from ignoring errors to copy‑on‑write and journaling—to mitigate data loss, each with trade‑offs in performance and reliability.

Copy-on-Writedata integrityext4
0 likes · 9 min read
What Really Happens to Files and Disks During a Power Outage?
dbaplus Community
dbaplus Community
Sep 27, 2016 · Databases

Which Tool Best Migrates SQL Server to MySQL? A Detailed Performance Comparison

This article presents a systematic evaluation of four SQL Server‑to‑MySQL migration tools—SQLyog, Navicat Premium, Mss2sql, and DB2DB—covering usability, speed, memory usage, data integrity, trial limitations, and additional features to help developers choose the most reliable solution for large‑scale database migrations.

Performance TestSQL ServerTool comparison
0 likes · 12 min read
Which Tool Best Migrates SQL Server to MySQL? A Detailed Performance Comparison
ITPUB
ITPUB
Aug 14, 2016 · Databases

14 Essential MySQL Security Practices to Protect Your Data

This guide outlines essential MySQL security measures—including removing default accounts, disabling unsafe LOCAL INFILE commands, enforcing strict user role permissions, encrypting sensitive data, ensuring data integrity through replication and backups, and standardizing operational practices—to protect database assets from irreversible breaches.

Database Securityaccess controldata integrity
0 likes · 6 min read
14 Essential MySQL Security Practices to Protect Your Data
Architect
Architect
Jul 30, 2015 · Backend Development

Redis‑Backed Timeline Implementation with MongoDB for a Subscription Feed

This article explains how to implement a scalable timeline for a subscription feed by combining MongoDB storage with a Redis list cache, detailing the data model, query challenges, Redis operations for pushing and trimming statuses, rebuilding strategies, and handling data integrity trade‑offs.

CacheMongoDBQueue
0 likes · 7 min read
Redis‑Backed Timeline Implementation with MongoDB for a Subscription Feed