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data governance

767 articles · Page 3 of 8
Data Integration and Governance
Data Integration and Governance
Mar 5, 2026 · Industry Insights

Why Data Metrics Clash and How Four Steps Can Fix Them

Inconsistent metric definitions cause confusion across finance, sales, and product teams, leading to mistrust and delayed decisions; this article outlines seven common mismatches and a four‑step framework—building a metric dictionary, establishing naming and definition standards, systematizing management, and assigning governance—to unify data metrics across an organization.

Business IntelligenceData QualityMetric Standardization
0 likes · 10 min read
Why Data Metrics Clash and How Four Steps Can Fix Them
Data Integration and Governance
Data Integration and Governance
Mar 4, 2026 · Big Data

9 Quantitative Metrics to Evaluate Your Data Warehouse—A Complete Guide

The article presents nine concrete, formula‑based metrics across completeness, reuse, and compliance dimensions—such as cross‑layer reference rate, summary query ratio, model reuse coefficient, lineage divergence, field description coverage, layering info coverage, domain ownership, naming compliance, and field‑consistency—to objectively assess data‑warehouse health and guide continuous improvement.

completenessdata governancedata warehouse
0 likes · 10 min read
9 Quantitative Metrics to Evaluate Your Data Warehouse—A Complete Guide
Wuming AI
Wuming AI
Mar 2, 2026 · Industry Insights

How China’s New AI Training Data Standard Bridges Data Delivery and Model Performance

The article explains how the newly released "AI Training Data Set Delivery and Quality Acceptance Specification" addresses gaps in existing data‑quality standards by defining a three‑layer acceptance framework, quantitative metrics, and a pre‑negotiated quality‑baseline mechanism to make dataset delivery verifiable and directly supportive of model training goals.

AI data standardsData Qualitydata governance
0 likes · 7 min read
How China’s New AI Training Data Standard Bridges Data Delivery and Model Performance
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Feb 11, 2026 · Artificial Intelligence

Breaking the Data Ceiling: UltraData’s 2.4 TB Tiered Dataset with the Largest L3 Math Library

UltraData presents a five‑level tiered data‑management system (L0‑L4) for large‑language‑model training, releases the world’s largest open L3 mathematics dataset (2.4 TB), validates the approach with extensive MiniCPM‑1.2B experiments showing consistent performance gains across web, multilingual, math and code domains, and opens a suite of governance tools and a community portal.

Mathematics DatasetMiniCPMTiered Data Management
0 likes · 15 min read
Breaking the Data Ceiling: UltraData’s 2.4 TB Tiered Dataset with the Largest L3 Math Library
BanTech Think Tank
BanTech Think Tank
Feb 11, 2026 · Industry Insights

Building High-Quality Data Sets for Commercial Bank AI: Exploration and Practice

The article examines how commercial banks, driven by national policies and AI advances, develop high‑quality data sets—detailing their strategic importance, regulatory background, challenges in systematization, engineering, and operation, and showcasing ICBC’s layered data architecture, knowledge‑engine pipelines, and future data‑driven competitiveness.

AI modelsArtificial IntelligenceKnowledge Engineering
0 likes · 13 min read
Building High-Quality Data Sets for Commercial Bank AI: Exploration and Practice
Amazon Cloud Developers
Amazon Cloud Developers
Feb 4, 2026 · Artificial Intelligence

From ChatBI to a Multi‑Agent Analytics Platform: A Practical Amazon‑Snowflake Architecture

The article examines why single‑agent ChatBI solutions fall short in enterprise settings and presents a three‑layer, multi‑agent architecture—interaction, orchestration, and execution—built with Amazon Quick Suite, Amazon Bedrock AgentCore, and Snowflake Cortex AI, detailing routing, synchronous/asynchronous processing, semantic modeling, and deployment recommendations.

Amazon Bedrock AgentCoreAmazon Quick SuiteMulti-Agent Architecture
0 likes · 15 min read
From ChatBI to a Multi‑Agent Analytics Platform: A Practical Amazon‑Snowflake Architecture
Data Integration and Governance
Data Integration and Governance
Jan 26, 2026 · Industry Insights

Is Digitalization a Tech Problem or a Management Problem?

The article argues that digitalization is neither purely a technology issue nor a management issue, illustrating how technology can build platforms, automate workflows, and generate reports, while management must define business rules, data standards, and responsibilities to ensure successful transformation.

Process Automationbusiness-IT alignmentdata governance
0 likes · 9 min read
Is Digitalization a Tech Problem or a Management Problem?
Smart Sea Tide
Smart Sea Tide
Jan 23, 2026 · Industry Insights

Digital Portrait of Data Governance: Measuring User Experience and Architecture Quality

The article proposes a “digital portrait” framework for data governance, outlining concrete metrics to evaluate user experience across external customers, internal users, management, and technical staff, as well as architecture quality indicators such as model reuse, data distribution, standard stability, and asset coverage.

architecture qualitybig datadata governance
0 likes · 10 min read
Digital Portrait of Data Governance: Measuring User Experience and Architecture Quality
ITPUB
ITPUB
Jan 20, 2026 · Databases

Boost Data Warehouse Efficiency with Proven Naming Conventions

A well‑defined naming convention for data‑warehouse tables reduces chaos, improves maintainability, speeds up queries, and cuts cross‑team collaboration costs, turning raw data into a strategic asset for modern enterprises.

Naming Conventiondata governancedata warehouse
0 likes · 8 min read
Boost Data Warehouse Efficiency with Proven Naming Conventions
Smart Sea Tide
Smart Sea Tide
Jan 20, 2026 · Big Data

How Atlas’s Metadata Storage Model Enables Scalable Hadoop Governance

The article provides a detailed technical analysis of Apache Atlas, describing its core components, type system, JanusGraph‑based graph storage on HBase, the mapping of various metadata types to vertices and edges, and the three‑phase parsing and validation process that together support scalable Hadoop governance.

Apache AtlasHBaseJanusGraph
0 likes · 16 min read
How Atlas’s Metadata Storage Model Enables Scalable Hadoop Governance
Data Integration and Governance
Data Integration and Governance
Jan 14, 2026 · Big Data

Finally, a Clear Guide to Data Architecture

This article explains data architecture from the ground up, covering data sources, storage options such as operational databases, data warehouses and data lakes, ETL processing steps, layered data modeling, service delivery methods, and governance practices to ensure reliable, secure, and business‑driven data management.

Data LakeETLdata architecture
0 likes · 11 min read
Finally, a Clear Guide to Data Architecture
Subtle Storm
Subtle Storm
Jan 9, 2026 · Artificial Intelligence

Compute, Algorithms, Data: Unveiling the AI Era's Golden Triangle

AI success hinges on the interplay of compute, algorithms, and data; the article breaks down each component, highlights common pitfalls such as poor data quality or insufficient compute, and offers practical strategies—from data governance to algorithm system design and cost‑effective compute—to turn AI from usable to truly useful.

AI DeploymentAlgorithm EngineeringArtificial Intelligence
0 likes · 11 min read
Compute, Algorithms, Data: Unveiling the AI Era's Golden Triangle
Data Integration and Governance
Data Integration and Governance
Jan 9, 2026 · Industry Insights

Mastering Data Governance: Standards, Metadata, Master Data, Quality, Security, and Asset Management

The article shares a practical roadmap for building a data governance framework, covering data standards, metadata management, master data management, data quality, security, and asset management, with step‑by‑step methods, real‑world examples, and tools to help teams align definitions, automate checks, and protect sensitive information.

Data AssetData Qualitydata governance
0 likes · 10 min read
Mastering Data Governance: Standards, Metadata, Master Data, Quality, Security, and Asset Management
Data Integration and Governance
Data Integration and Governance
Jan 4, 2026 · Big Data

Unify Data Definitions with an Enterprise Data Model: Core Logic, Steps, and Pitfalls

The article explains why many companies fail with fragmented data models, defines what an enterprise‑level data model is, outlines its four key benefits, and provides a detailed six‑step implementation guide—including scope definition, data investigation, layered architecture, standardization, tool selection, and iterative rollout—to avoid common pitfalls.

Data IntegrationETLbig data
0 likes · 9 min read
Unify Data Definitions with an Enterprise Data Model: Core Logic, Steps, and Pitfalls
Data Integration and Governance
Data Integration and Governance
Dec 31, 2025 · Big Data

Do You Really Understand Data Elements? How to Turn Raw Data into Business Value

The article explains what data elements are, why they matter for efficiency and market competition, and provides a step‑by‑step framework—including data inventory, standardization, governance, and application—to help enterprises transform raw data into valuable, actionable assets while avoiding common pitfalls.

Data AssetEnterprise Databusiness value
0 likes · 9 min read
Do You Really Understand Data Elements? How to Turn Raw Data into Business Value
Data Integration and Governance
Data Integration and Governance
Dec 29, 2025 · Fundamentals

Master Structured, Semi‑Structured, and Unstructured Data: A Beginner’s Guide to Data Governance

The article explains the three core data categories—structured, semi‑structured, and unstructured—illustrates their characteristics with real manufacturing examples, compares suitable storage and processing tools, and outlines three practical principles for effective data integration and governance.

Data IntegrationETLSemi-structured Data
0 likes · 9 min read
Master Structured, Semi‑Structured, and Unstructured Data: A Beginner’s Guide to Data Governance
Woodpecker Software Testing
Woodpecker Software Testing
Dec 25, 2025 · Artificial Intelligence

How AI Testing Platforms Achieve Real-World Efficiency Gains

The article analyzes AI testing platforms, showing how automated test‑case generation, adaptive execution, defect prediction, and a structured rollout process deliver up to 35% higher coverage, 48% faster design, and 40% reduced execution time across finance and e‑commerce case studies.

AI testingadaptive testingdata governance
0 likes · 8 min read
How AI Testing Platforms Achieve Real-World Efficiency Gains
StarRocks
StarRocks
Dec 25, 2025 · Big Data

How dbt, DataOps, and StarRocks Combine to Accelerate Real‑Time Data Modeling

This article explains how dbt drives automated data modeling and governance, how DataOps practices bring agility and control to data projects, and how StarRocks’ lakehouse architecture enables real‑time and batch analytics, illustrated with concrete workflows, version‑control conventions, and enterprise case studies.

Data ModelingDataOpsELT
0 likes · 14 min read
How dbt, DataOps, and StarRocks Combine to Accelerate Real‑Time Data Modeling
Data Integration and Governance
Data Integration and Governance
Dec 23, 2025 · Industry Insights

How to Write an IT Data Team Year‑End Summary That Shows Real Business Value

The article critiques typical data‑team year‑end reports that merely list technical metrics and shows how to restructure them around business‑value narratives, technical‑debt transparency, data‑governance integration, capability mapping, and measurable goals, illustrated with concrete examples and templates.

business valuecapability buildingdata governance
0 likes · 9 min read
How to Write an IT Data Team Year‑End Summary That Shows Real Business Value
Data Integration and Governance
Data Integration and Governance
Dec 19, 2025 · Operations

Six Common Pitfalls in Data Governance and How to Overcome Them

The article identifies six frequent problems in data governance—unclear goals, dispersed responsibility, poor data quality, inconsistent standards, lack of continuity, and neglect of practical application—and provides concrete examples, step‑by‑step remedies, and organizational best practices to help enterprises avoid costly missteps.

Data Qualitybusiness alignmentcontinuous improvement
0 likes · 11 min read
Six Common Pitfalls in Data Governance and How to Overcome Them
Zhuanzhuan Tech
Zhuanzhuan Tech
Dec 17, 2025 · Artificial Intelligence

How AI Powers Automatic Security Tagging in Large‑Scale Data Governance

This article details how a Chinese e‑commerce platform leverages large‑language‑model AI, the open‑source Dify platform, and engineered workflows to automate security tagging of massive data assets, covering data‑governance fundamentals, AI‑driven tagging advantages, technical architecture, prompt engineering, optimization cases, and future roadmap.

AISecurity TaggingWorkflow Automation
0 likes · 25 min read
How AI Powers Automatic Security Tagging in Large‑Scale Data Governance
Smart Sea Tide
Smart Sea Tide
Dec 17, 2025 · Fundamentals

Master Data Management: Theory, Practices, and Real‑World Implementation

This article provides a comprehensive overview of master data management, covering definitions, characteristics, types, relationships with other data, its strategic significance, common implementation challenges, the two‑system‑one‑tool framework, detailed implementation steps, and a concrete project case study.

Data QualityMDMdata governance
0 likes · 20 min read
Master Data Management: Theory, Practices, and Real‑World Implementation
Ray's Galactic Tech
Ray's Galactic Tech
Dec 15, 2025 · Databases

Mastering Database Design: From Core Principles to Modern Distributed Practices

This comprehensive guide walks you through fundamental database design goals, a step‑by‑step lifecycle, nine essential strategies—including normalization, indexing, and security—plus modern distributed and NoSQL considerations, performance tuning, high‑availability tactics, and practical tools for robust data governance.

NoSQLPerformance OptimizationSecurity
0 likes · 11 min read
Mastering Database Design: From Core Principles to Modern Distributed Practices
Data Integration and Governance
Data Integration and Governance
Dec 11, 2025 · Industry Insights

Why Does a Years‑Old Data Middle Platform Still Require Manual Data Requests for Channel Analysis?

The article examines why a three‑year‑old data middle platform still forces analysts to chase data across departments for channel analysis, identifies four root causes—from mismatched definitions to insufficient serviceization—and proposes concrete steps to shift governance upstream, build a business‑focused data product layer, embed quality checks, and treat data as an operable product.

Business IntelligenceData Serviceschannel analysis
0 likes · 9 min read
Why Does a Years‑Old Data Middle Platform Still Require Manual Data Requests for Channel Analysis?
Data Integration and Governance
Data Integration and Governance
Dec 8, 2025 · Fundamentals

Structured, Semi‑Structured, and Unstructured Data: Choosing the Right Storage for IoT Sensor Streams

The article explains the definitions and practical differences of structured, semi‑structured, and unstructured data, compares suitable storage and processing technologies, discusses governance challenges, and offers a step‑by‑step strategy—including a data‑integration tool example—to help IoT projects select the optimal data architecture.

Data StorageIoTSemi-structured Data
0 likes · 10 min read
Structured, Semi‑Structured, and Unstructured Data: Choosing the Right Storage for IoT Sensor Streams
Smart Sea Tide
Smart Sea Tide
Dec 8, 2025 · Big Data

Comprehensive Data Governance Solution for Big Data Platforms

The article outlines a data governance framework for big data platforms that addresses enterprise data standards, quality, and metadata management, detailing three core objectives—standard implementation, quality analysis, and lineage mapping—while providing a PDF roadmap for practical deployment.

Data Qualitybig datadata governance
0 likes · 5 min read
Comprehensive Data Governance Solution for Big Data Platforms
dbaplus Community
dbaplus Community
Dec 7, 2025 · Artificial Intelligence

How AI Agents Can Revolutionize Data Governance: A Step‑by‑Step Blueprint

This article explains how AI agents transform traditional data governance by introducing a four‑layer perception‑decision‑execution‑learning architecture, detailing the required technologies, tool integrations, code examples, deployment steps, team roles, security safeguards, and practical rollout strategies for enterprises seeking automated, intelligent data management.

AI AgentData QualityLangChain
0 likes · 10 min read
How AI Agents Can Revolutionize Data Governance: A Step‑by‑Step Blueprint
Data Integration and Governance
Data Integration and Governance
Dec 5, 2025 · Fundamentals

Finally, a Clear Explanation of Data Modeling

The article explains why inconsistent field definitions across systems stem from a lack of a unified data model, defines data modeling versus data model, outlines the three modeling stages, compares three common modeling approaches—normative, dimensional, and entity—and shows how proper modeling supports data governance, ETL, and analytics.

Data ModelingETLdata governance
0 likes · 12 min read
Finally, a Clear Explanation of Data Modeling
Smart Sea Tide
Smart Sea Tide
Dec 5, 2025 · Big Data

Understanding Data Lineage: Concepts, Characteristics, and Practical Collection Methods

The article explains data lineage as the full‑lifecycle relationships between data objects, outlines its ownership, multi‑source, traceability, and hierarchical traits, illustrates with school and banking examples, and details why lineage is crucial for compliance, impact analysis, security, migration, and self‑service, while reviewing collection techniques.

Data LifecycleData QualityETL
0 likes · 11 min read
Understanding Data Lineage: Concepts, Characteristics, and Practical Collection Methods
Data Integration and Governance
Data Integration and Governance
Dec 3, 2025 · Fundamentals

Eight Core Data Concepts: Elements, Resources, Assets, Digital Assets, Management, Governance, Property Rights, Accounting

The article clarifies eight frequently used data concepts—data element, data resource, data asset, digital asset, data management, data governance, data property rights, and data asset accounting—explaining their definitions, differences, hierarchical relationships, and practical implications for enterprises.

Data Assetdatadata accounting
0 likes · 10 min read
Eight Core Data Concepts: Elements, Resources, Assets, Digital Assets, Management, Governance, Property Rights, Accounting
Data Integration and Governance
Data Integration and Governance
Dec 2, 2025 · Operations

How to Manage Data Assets? The Four Key Steps

The article explains why treating data as an asset matters, distinguishes data asset management from traditional data governance, and outlines four practical steps—inventory, standardization, quality & security, and value realization—to turn raw data into a strategic business resource.

Data Qualitydata asset managementdata catalog
0 likes · 10 min read
How to Manage Data Assets? The Four Key Steps
DataFunSummit
DataFunSummit
Dec 1, 2025 · Artificial Intelligence

Why Palantir’s Ontology Approach Could Transform Enterprise AI – Insights from Industry Leaders

A detailed transcript of a closed‑door forum reveals how Palantir’s ontology methodology, combined with AI agents, addresses data semantics, knowledge governance, and enterprise‑level decision making, while highlighting practical challenges, evaluation frameworks, and the need for strong management and high‑quality data foundations.

Enterprise AIOntologyPalantir
0 likes · 27 min read
Why Palantir’s Ontology Approach Could Transform Enterprise AI – Insights from Industry Leaders
Data Integration and Governance
Data Integration and Governance
Dec 1, 2025 · Fundamentals

Why Data Standards Fail and How to Implement Them in Four Practical Steps

The article explains why data standards often stall, defines the essential elements of a usable standard, and presents a concrete four‑step framework—including team formation, high‑value pilot selection, detailed gap analysis, and joint review—to turn standards into enforceable, business‑driving rules.

Business AnalyticsData IntegrationData Quality
0 likes · 11 min read
Why Data Standards Fail and How to Implement Them in Four Practical Steps
DaTaobao Tech
DaTaobao Tech
Dec 1, 2025 · Artificial Intelligence

How AI Can Automate Repetitive Work: From Simple Tools to Intelligent Agents

This article shares the author's practical experience in using AI to tackle complex repetitive tasks, presenting a reusable methodology that abstracts human actions into a perception‑decision‑execution loop, and demonstrates three automation modes—tool assistant, workflow, and intelligent agent—through real‑world cases in data governance, ticket handling, and baseline operations.

AI automationdata governanceintelligent-agent
0 likes · 23 min read
How AI Can Automate Repetitive Work: From Simple Tools to Intelligent Agents
Data Integration and Governance
Data Integration and Governance
Nov 28, 2025 · Big Data

Why Data Quality Fails and How to Build a High‑Quality Dataset in 4 Steps

The article explains common data‑quality pitfalls—such as inconsistent source entry, multi‑source integration issues, changing business rules, and ETL errors—then defines six concrete quality dimensions and presents a repeatable four‑step workflow, plus practical tool recommendations, for creating reliable datasets.

Data QualityData ValidationETL
0 likes · 11 min read
Why Data Quality Fails and How to Build a High‑Quality Dataset in 4 Steps
Baidu Tech Salon
Baidu Tech Salon
Nov 26, 2025 · Big Data

How Baidu MEG Cut Data Costs: Inside a Big Data Governance Playbook

This article details Baidu's MEG data cost governance practice, covering background challenges, a unified governance framework, health‑score metrics, platform and engine capabilities, concrete compute and storage optimization techniques, achieved results, and future plans for continuous cost reduction.

Cost Optimizationdata governance
0 likes · 23 min read
How Baidu MEG Cut Data Costs: Inside a Big Data Governance Playbook
Data Integration and Governance
Data Integration and Governance
Nov 25, 2025 · Operations

Is Data Governance About Technology? Start with Organizational Roles

The article explains that data governance failures often stem from unclear responsibilities and processes rather than technology, outlines common misconceptions, presents a three‑pillar framework, and offers practical steps—including defining standards, choosing supporting tools, assigning responsibilities, and evaluating results—to build sustainable governance.

Data QualityOrganizational Rolesdata governance
0 likes · 6 min read
Is Data Governance About Technology? Start with Organizational Roles
JD Cloud Developers
JD Cloud Developers
Nov 24, 2025 · Artificial Intelligence

JoyAgent: Open‑Source Enterprise‑Grade Multi‑Agent Platform from JD

The 2025 Open Atom Developer Conference highlighted JD's JoyAgent project, an open‑source, 100% enterprise‑grade multi‑agent platform that excels in AI, data governance, and diagnostic analysis, with detailed features, performance metrics, and deployment experiences shared.

AI platformDiagnostic AnalysisJoyAgent
0 likes · 7 min read
JoyAgent: Open‑Source Enterprise‑Grade Multi‑Agent Platform from JD
DataFunSummit
DataFunSummit
Nov 23, 2025 · Artificial Intelligence

How Large Language Models Are Revolutionizing Banking Data Integration

This article examines the challenges of traditional banking data, explains how large language models can fuse structured and unstructured information, outlines a new data‑centric infrastructure and governance approach, and describes the DiFY platform’s AI‑agent and DataOps capabilities for agile, non‑intrusive integration with core banking systems.

AI AgentsDataOpsbanking data
0 likes · 16 min read
How Large Language Models Are Revolutionizing Banking Data Integration
Smart Sea Tide
Smart Sea Tide
Nov 21, 2025 · Big Data

How to Build a Practical Big Data Platform to Bridge Data Gaps

The article explains why enterprises need a well‑designed data architecture, describes the pain points caused by missing capabilities, and outlines a big‑data platform construction plan that helps businesses treat data as a valuable asset and improve sharing and utilization.

Enterprise Databig datadata architecture
0 likes · 2 min read
How to Build a Practical Big Data Platform to Bridge Data Gaps
Data Integration and Governance
Data Integration and Governance
Nov 19, 2025 · Fundamentals

Are You Building Data Dictionaries the Right Way?

The article explains what a data dictionary is, why it is essential for collaboration, clarity, and security, and provides a step‑by‑step guide—including examples of data items, structures, flows, storage, and processing—to help teams create and maintain effective dictionaries.

Data ModelingData Qualitydata dictionary
0 likes · 8 min read
Are You Building Data Dictionaries the Right Way?
Data Thinking Notes
Data Thinking Notes
Nov 2, 2025 · Artificial Intelligence

Why Data Governance Is the Key to Trustworthy AI in the Large Model Era

The article explains how the rapid rise of large‑model AI has shifted the focus from models to data, outlines the concept and stages of AI‑specific data governance, identifies challenges such as low‑quality data, privacy leaks, bias, and proposes a comprehensive framework of principles, processes, and technologies to ensure high‑quality, secure, and ethical AI deployment.

AIData QualityEthics
0 likes · 40 min read
Why Data Governance Is the Key to Trustworthy AI in the Large Model Era
Big Data Tech Team
Big Data Tech Team
Oct 29, 2025 · Fundamentals

Why Unified Data Modeling Matters: From Conceptual Design to Physical Implementation

The article explains how inconsistent "customer ID" fields across systems stem from a lack of unified data models, defines the difference between data modeling and data models, outlines three modeling stages, and compares three major modeling approaches—normative, dimensional, and entity—highlighting their purposes, processes, and trade‑offs.

conceptual modelingdata governancedatabase design
0 likes · 12 min read
Why Unified Data Modeling Matters: From Conceptual Design to Physical Implementation
DataFunSummit
DataFunSummit
Oct 28, 2025 · Fundamentals

Why Unstructured Data Management Is the Next Frontier for Enterprises

This article explores the evolution, current state, and challenges of enterprise unstructured data management, reviews case studies from traditional firms, Huawei and Ant Group, proposes an ECM‑based reference framework, compares it with structured data governance, and outlines future integration strategies with AI and unified data platforms.

AIbig datadata governance
0 likes · 28 min read
Why Unstructured Data Management Is the Next Frontier for Enterprises
DataFunTalk
DataFunTalk
Oct 26, 2025 · Big Data

How Kuaishou E‑Commerce Built a Data Metric System to Drive Growth

This article explores Kuaishou E‑Commerce’s journey in constructing a comprehensive data metric system, detailing its business context, the necessity of metrics, challenges across data production, querying and usage, practical implementation steps, management practices, and a concluding Q&A.

Data MetricsE-commerce AnalyticsKuaishou
0 likes · 6 min read
How Kuaishou E‑Commerce Built a Data Metric System to Drive Growth
Big Data Tech Team
Big Data Tech Team
Oct 23, 2025 · Industry Insights

How to Build a Reusable, Well‑Designed Data Warehouse Model

This article analyzes why analysts and data engineers clash over non‑reusable data models, presents metrics such as cross‑layer reference rate and model reuse coefficient, and outlines a step‑by‑step framework—including ODS takeover, subject‑domain mapping, dimension consistency, fact‑table integration, development best practices, and tool support—to transform siloed warehouses into a shared data‑platform.

Best Practicesbig datadata governance
0 likes · 15 min read
How to Build a Reusable, Well‑Designed Data Warehouse Model
DataFunTalk
DataFunTalk
Oct 18, 2025 · Big Data

Inside Ant Group’s Big Data Governance: Key Practices and Insights

This article shares Ant Group’s practical experience in large-scale data governance, outlining four main topics—overall governance overview, data quality management, data storage-processing governance, and future considerations—while emphasizing the five critical aspects of architecture, security, compliance, quality, and value that drive effective big-data operations.

Data Qualitydata architecturedata governance
0 likes · 4 min read
Inside Ant Group’s Big Data Governance: Key Practices and Insights
DataFunSummit
DataFunSummit
Oct 14, 2025 · Big Data

How Douyin’s Data Asset Platform Redefines Big Data Lineage

This article introduces Douyin Group’s one‑stop Data Asset Management Platform, explains why the company focuses on data assets rather than raw metadata, and details the evolution, architecture, applications, and future outlook of its comprehensive big‑data lineage system.

Douyinbig datadata asset management
0 likes · 5 min read
How Douyin’s Data Asset Platform Redefines Big Data Lineage
DataFunSummit
DataFunSummit
Oct 12, 2025 · Big Data

How Douyin’s Data Asset Platform Revolutionizes Big Data Lineage

This article introduces Douyin Group’s Data Asset Management Platform, explaining its shift from traditional metadata to comprehensive data assets, detailing the evolution, architecture, and applications of its full‑link big data lineage, and offering strategic guidance for building effective lineage systems.

Data AssetDouyindata governance
0 likes · 5 min read
How Douyin’s Data Asset Platform Revolutionizes Big Data Lineage
DataFunSummit
DataFunSummit
Oct 11, 2025 · Big Data

What Small Banks Can Learn from Cutting-Edge Data Governance Practices

This article shares a data‑governance roadmap for small and medium banks, covering industry pain points, high‑quality data sets, a three‑step governance path, data standards, metadata management, master‑data strategy, business data modeling, a hybrid Greenplum‑Hadoop platform, quality monitoring, and a maturity assessment framework.

bankingbig datadata architecture
0 likes · 21 min read
What Small Banks Can Learn from Cutting-Edge Data Governance Practices
DataFunTalk
DataFunTalk
Oct 6, 2025 · Big Data

What Ant Group Learned: 5 Pillars of Effective Data Governance

Ant Group shares its practical experience in big data governance, outlining five key focus areas—architecture, security, compliance, quality, and value—through four structured sections and detailed discussions on data quality and storage governance, while also exploring future challenges and the economics of data.

Ant GroupData Qualitybig data
0 likes · 4 min read
What Ant Group Learned: 5 Pillars of Effective Data Governance
DataFunSummit
DataFunSummit
Sep 30, 2025 · Artificial Intelligence

How to Govern AI Ethically: Frameworks, Risks, and Real‑World Practices

This article explores AI governance and ethics, outlining five key parts: AI business scenarios, data and AI risks, a comprehensive governance framework, practical implementation steps, and measurable benefits, while also providing expert insights and a Q&A session for deeper understanding.

AI FrameworkAI GovernanceAI risk management
0 likes · 16 min read
How to Govern AI Ethically: Frameworks, Risks, and Real‑World Practices
Alibaba Cloud Observability
Alibaba Cloud Observability
Sep 29, 2025 · Cloud Native

How Alibaba Cloud SLS Soft Delete Enables Instant, Low‑Cost Data Cleanup

This article explains Alibaba Cloud's Log Service (SLS) soft‑delete feature, describing its mark‑and‑filter mechanism, implementation steps, and real‑world scenarios where it replaces costly hard‑delete or ETL solutions with near‑instant, low‑impact data removal for compliance, emergencies, and test‑data contamination.

Alibaba CloudLog ManagementSoft Delete
0 likes · 9 min read
How Alibaba Cloud SLS Soft Delete Enables Instant, Low‑Cost Data Cleanup
DataFunSummit
DataFunSummit
Sep 20, 2025 · Fundamentals

Why Data Governance Fails: Combating Entropy in Integrated Data Systems

This article explains how the natural entropy of massive data sets creates governance challenges, outlines four core obstacles faced by large internet companies, and presents a sustainable, metric‑driven framework—including quality measurement, indicator systems, and future‑oriented operations—to achieve orderly data asset management.

Enterprise DataIndicator Systemdata governance
0 likes · 18 min read
Why Data Governance Fails: Combating Entropy in Integrated Data Systems
DataFunSummit
DataFunSummit
Sep 19, 2025 · Big Data

Unlocking Data Lineage: SQL Bloodline for Discovery, Governance & Protection

This article explains how SQL lineage (bloodline) technology can be leveraged in offline data warehouses to enable precise data discovery, automated tag propagation, fine‑grained data governance, column‑level TTL management, and dynamic masking for data protection, illustrating implementation steps, strategies, and real‑world use cases.

SQL lineagedata discoverydata governance
0 likes · 28 min read
Unlocking Data Lineage: SQL Bloodline for Discovery, Governance & Protection
DataFunTalk
DataFunTalk
Sep 16, 2025 · Artificial Intelligence

Top AI Data Governance & Large Model Innovations: A Comprehensive Catalog

This article presents a curated catalog of cutting‑edge topics covering financial large‑model data governance, proactive metadata systems, data cleaning and compliance technologies, AI‑driven intelligent operations, and generative data analysis solutions, inviting readers to explore the latest AI innovations.

AIdata compliancedata governance
0 likes · 2 min read
Top AI Data Governance & Large Model Innovations: A Comprehensive Catalog
DataFunTalk
DataFunTalk
Sep 15, 2025 · Artificial Intelligence

Unlocking the Future: AI-Driven Data Governance and Large Model Innovations

This article presents a curated catalog of cutting‑edge topics covering AI‑powered data governance, large‑model applications, data cleaning, compliance, lakehouse integration, intelligent operations, and generative analytics, inviting readers to explore the latest innovations and download the full e‑book via QR code.

AIAnalyticsdata cleaning
0 likes · 2 min read
Unlocking the Future: AI-Driven Data Governance and Large Model Innovations
DataFunSummit
DataFunSummit
Sep 6, 2025 · Artificial Intelligence

Explore Cutting-Edge AI‑Driven Data Governance: Full Topic Catalog

This article presents a comprehensive catalog of cutting‑edge AI and large‑model topics, covering financial data governance, proactive metadata systems, data cleaning compliance, lake‑warehouse integration, intelligent operations, generative analytics, and QR‑code access to the full e‑book.

AIAnalyticsTechnology
0 likes · 2 min read
Explore Cutting-Edge AI‑Driven Data Governance: Full Topic Catalog
Baidu Geek Talk
Baidu Geek Talk
Sep 3, 2025 · Big Data

How Baidu’s TDS Platform Achieves End‑to‑End Data Governance and Smart Operations

This article details Baidu MEG’s TDS (Turing Data Studio) platform, explaining its three‑pillar governance framework—process standardization, quality controllability, and intelligent operations—along with concrete mechanisms, automation, and measurable results that dramatically improve data reliability, operational efficiency, and fault‑tolerance in large‑scale data production.

Data QualityDevOpsautomation
0 likes · 20 min read
How Baidu’s TDS Platform Achieves End‑to‑End Data Governance and Smart Operations
Smart Sea Tide
Smart Sea Tide
Sep 3, 2025 · Industry Insights

How to Govern Unstructured Data Effectively?

The article explains why unstructured data—documents, images, audio, and video—now dominates enterprise information, outlines five key management challenges such as data variety, information silos, and weak governance, and then presents a four‑step governance framework and ECM‑based solution backed by industry standards and Gartner insights.

ECMGartnerdata governance
0 likes · 15 min read
How to Govern Unstructured Data Effectively?
DataFunTalk
DataFunTalk
Sep 1, 2025 · Big Data

How JD Retail Tackles Data Governance Challenges to Boost Efficiency

JD Retail outlines the growing data management challenges it faces—including asset discovery, architecture agility, development quality, and rising IT costs—and presents a comprehensive data governance framework that leverages standards, agile architecture, development isolation, and resource optimization to improve efficiency and reduce operational expenses.

Resource Optimizationarchitecturebig data
0 likes · 7 min read
How JD Retail Tackles Data Governance Challenges to Boost Efficiency
Smart Sea Tide
Smart Sea Tide
Aug 31, 2025 · Fundamentals

How to Build an Effective Data Metric System: Classification and Naming Rules

The article explains how to construct a data metric system by first defining metric categories and naming conventions, then distinguishing atomic and derived metrics, and clarifying related concepts such as business processes, modifiers, time periods, dimensions, and business domains.

Business AnalyticsData Metricsdata governance
0 likes · 4 min read
How to Build an Effective Data Metric System: Classification and Naming Rules
DataFunTalk
DataFunTalk
Aug 28, 2025 · Big Data

How JD Retail Tackles Data Governance Challenges to Boost Efficiency

JD Retail faces growing data volume, redundant models, and resource‑intensive storage, prompting a comprehensive data‑governance strategy that defines standards, streamlines architecture, isolates development, and optimizes compute and storage costs, ultimately enabling more efficient, secure, and agile data operations across the enterprise.

Resource Optimizationbig datadata architecture
0 likes · 8 min read
How JD Retail Tackles Data Governance Challenges to Boost Efficiency
DataFunTalk
DataFunTalk
Aug 27, 2025 · Big Data

How JD Retail Overcomes Data Governance Challenges to Boost Efficiency

JD Retail confronts growing data volume, redundant models, shared account risks, and rising storage costs, and responds with a comprehensive data governance framework that standardizes data, streamlines architecture, isolates development, and optimizes resources to achieve efficient, secure, and cost‑effective data operations.

Resource Optimizationbig datadata architecture
0 likes · 8 min read
How JD Retail Overcomes Data Governance Challenges to Boost Efficiency
Big Data Tech Team
Big Data Tech Team
Aug 25, 2025 · Interview Experience

Essential Big Data Interview Questions for Data Warehouse Engineer Roles

A comprehensive list of interview topics covering self‑introduction, career moves, data‑warehouse design, team building, architecture comparisons, fact‑table classification, common dimensions, performance tuning, and data‑governance for aspiring big‑data engineers.

FlinkHiveInterview Preparation
0 likes · 4 min read
Essential Big Data Interview Questions for Data Warehouse Engineer Roles
Lakehouse Research Base
Lakehouse Research Base
Aug 15, 2025 · Big Data

Big Data & Platform Engineering Fusion: Building Scalable Data Infrastructure

This article explores the convergence of big data engineering and platform engineering, detailing how platform engineering methodologies solve big data's complexity challenges through unified resource pooling, standardized pipelines, observability, and governance, delivering faster deployment, 30-50% resource utilization gains, and reduced MTTR.

Data PipelineElastic ScalingKubernetes
0 likes · 15 min read
Big Data & Platform Engineering Fusion: Building Scalable Data Infrastructure
Data Party THU
Data Party THU
Aug 1, 2025 · Industry Insights

How Data Elements Drive Continuous Growth in Manufacturing: Challenges and Solutions

This report analyzes how treating data as a production factor reshapes manufacturing, outlines three major challenges—scenario explosion, business‑application enrichment, and intelligent‑application expansion—and shares concrete governance, platform, and AI‑model practices that enable agile, data‑driven digital transformation.

AIdata assetsdata governance
0 likes · 17 min read
How Data Elements Drive Continuous Growth in Manufacturing: Challenges and Solutions
Bilibili Tech
Bilibili Tech
Jul 25, 2025 · Big Data

How Unified Metadata Lineage Transforms Big Data Governance and Security

This article introduces the comprehensive design and evolution of a unified metadata lineage platform for big data, covering background, data processing chain, lineage models, system architecture, quality metrics, application scenarios, and future plans to enhance data governance, quality, and security.

Data Qualityarchitecturebig data
0 likes · 27 min read
How Unified Metadata Lineage Transforms Big Data Governance and Security
DataFunTalk
DataFunTalk
Jul 11, 2025 · Big Data

Lakehouse Revolution: Real‑Time Analytics and Data Architecture Insights

This article presents a curated list of case studies and insights on how Lakehouse technology powers real‑time analytics, simplifies data architecture, and drives digital transformation across industries such as e‑commerce, automotive, and social media.

LakehouseReal-time Analyticsdata governance
0 likes · 2 min read
Lakehouse Revolution: Real‑Time Analytics and Data Architecture Insights
DataFunTalk
DataFunTalk
Jul 9, 2025 · Big Data

How Lakehouse Is Transforming Real‑Time Multi‑Dimensional Analytics

This article compiles a series of expert case studies and insights on real‑time intelligent fully‑managed Lakehouse technology, illustrating how companies such as SalesEasy, Chang’an Auto, Kuaishou, Tencent, and JD.com leverage lakehouse architectures to achieve advanced multi‑dimensional analytics, cost‑performance balance, and effective data governance in the digital economy.

Case StudiesLakehousedata architecture
0 likes · 2 min read
How Lakehouse Is Transforming Real‑Time Multi‑Dimensional Analytics
DataFunTalk
DataFunTalk
Jul 8, 2025 · Big Data

Explore Cutting-Edge Lakehouse Solutions: Real-Time Analytics & Data Governance

This guide presents a curated collection of case studies and insights on cloud-native Lakehouse architectures, real‑time analytics, data‑driven user experiences, and data governance, showcasing implementations from companies like SalesEasy, Changan Auto, TikTok, Tencent, JD.com, and more.

Case StudiesLakehouseReal-time Analytics
0 likes · 2 min read
Explore Cutting-Edge Lakehouse Solutions: Real-Time Analytics & Data Governance
DataFunTalk
DataFunTalk
Jul 7, 2025 · Big Data

Unlock Real-Time Analytics with Cloud Lakehouse: A Complete Guide

This article presents a curated list of sessions covering cloud Lakehouse technology for real-time, multidimensional data analysis, including case studies from SalesEasy, Changan Auto, Tencent, and JD, as well as discussions on data lake adoption, streaming lake Paimon, and the relevance of metadata‑driven data governance in the digital economy.

IoTLakehouseReal-time Analytics
0 likes · 2 min read
Unlock Real-Time Analytics with Cloud Lakehouse: A Complete Guide
DataFunTalk
DataFunTalk
Jul 6, 2025 · Big Data

How Cloud Lakehouse Is Redefining Real-Time Multi-Dimensional Data Analytics

This article presents a curated list of case studies and insights on cloud Lakehouse technology, covering real-time intelligent analytics, data architecture simplification, IoT big‑data platforms, integrated data platforms, and the evolving role of metadata‑driven data governance in the digital economy.

Case StudiesLakehouseReal-time Analytics
0 likes · 2 min read
How Cloud Lakehouse Is Redefining Real-Time Multi-Dimensional Data Analytics
Instant Consumer Technology Team
Instant Consumer Technology Team
Jul 3, 2025 · Artificial Intelligence

Why Buying an AI Appliance Is a Strategic Pitfall for Enterprises

Enterprises rushing to purchase DeepSeek AI appliances and smart‑agent platforms often face hidden technical, data, and organizational challenges that turn promised "plug‑and‑play" solutions into costly missteps, highlighting the need for realistic strategy, robust data governance, and continuous capability building.

AI DeploymentAI capability buildingModel Quantization
0 likes · 28 min read
Why Buying an AI Appliance Is a Strategic Pitfall for Enterprises
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jun 13, 2025 · Artificial Intelligence

Designing AI-Ready Data Architecture: Key Features and Future Trends

AI-era data architecture must handle massive, multimodal datasets with real-time processing, prioritize data quality over quantity, support scalability, provenance, and native ML/AI integration, while addressing governance, security, and ethical challenges through emerging technologies like data fabric, mesh, and federated learning.

AIbig datadata architecture
0 likes · 6 min read
Designing AI-Ready Data Architecture: Key Features and Future Trends
DataFunSummit
DataFunSummit
Jun 6, 2025 · Big Data

How Unicom Digital’s Integrated Data Platform Revolutionizes Metadata Management

This article details Unicom Digital’s metadata management practice on its integrated data platform, covering the strategic background of data, key challenges, award-winning capabilities, three-pronged solutions—automation, linking+, and AI—along with practical implementations, full‑chain lineage, data responsibility, lifecycle management, and future AI‑driven enhancements.

AIautomationbig data
0 likes · 18 min read
How Unicom Digital’s Integrated Data Platform Revolutionizes Metadata Management
Continuous Delivery 2.0
Continuous Delivery 2.0
May 30, 2025 · Artificial Intelligence

Data Quality and Diversity: The Critical Battlefield Beyond AI Models

The article explains why high‑quality, diverse data—rather than just advanced models—has become the decisive factor for enterprise AI success, outlining key dimensions of data quality, strategies for building diverse datasets, and practical steps for establishing a data‑first AI strategy.

AIData Qualitydata governance
0 likes · 12 min read
Data Quality and Diversity: The Critical Battlefield Beyond AI Models
Lakehouse Research Base
Lakehouse Research Base
May 28, 2025 · Big Data

End-to-End Data Lifecycle Management: Closed-Loop Framework for Data Value

This article details a closed-loop Data Lifecycle Management (DLM) framework covering six stages—requirement confirmation, model design, development, testing, monitoring, and archiving—with governance practices, toolchains, and a bank case study showing reduced rework, storage costs, and model drift.

Data ArchivingData Lifecycle ManagementData Modeling
0 likes · 12 min read
End-to-End Data Lifecycle Management: Closed-Loop Framework for Data Value
Lakehouse Research Base
Lakehouse Research Base
May 22, 2025 · Big Data

Four Core Data Science Challenges and the DataOps Solution

The article identifies four core challenges in data science—data acquisition and management, technical engineering gaps, team collaboration barriers, and maintenance issues—and proposes a DataOps approach across technology, process, and organization to transform data assets into business value.

Data QualityData ScienceDataOps
0 likes · 9 min read
Four Core Data Science Challenges and the DataOps Solution
Lakehouse Research Base
Lakehouse Research Base
May 20, 2025 · Big Data

Why DataOps Jobs Will Explode: The Chemistry of Analytics, Lean, Agile & DevOps

This article analyzes DataOps as a deep fusion of data analytics, lean thinking, agile practices, and DevOps culture, contrasting it with DevOps, detailing its four genetic components with case studies, explaining its emergence from technical, business, and organizational drivers, examining current hiring fragmentation and talent gaps, and predicting explosive job growth driven by policy, tooling maturity, and talent supply reforms.

AgileData PipelineData Quality
0 likes · 20 min read
Why DataOps Jobs Will Explode: The Chemistry of Analytics, Lean, Agile & DevOps
Big Data Tech Team
Big Data Tech Team
May 19, 2025 · Fundamentals

Why Unified Data Modeling Matters: From Concepts to Physical Design

The article explains why establishing a unified data model is essential, differentiates data modeling from data models, outlines three modeling stages, compares normative, dimensional, and entity modeling methods, and provides practical steps and diagrams to help organizations build robust, business‑driven data architectures.

data governancedatabase designdimensional modeling
0 likes · 12 min read
Why Unified Data Modeling Matters: From Concepts to Physical Design
Big Data Technology & Architecture
Big Data Technology & Architecture
May 16, 2025 · Big Data

Apache Gravitino: An Open‑Source Metadata Lake for Unified Data and AI Asset Management

Apache Gravitino is an open‑source metadata service platform that provides a unified, high‑performance, geographically distributed metadata lake, enabling end‑to‑end data governance, multi‑engine access, and direct management of both structured and unstructured data assets across diverse systems.

Apache GravitinoData Lakedata governance
0 likes · 9 min read
Apache Gravitino: An Open‑Source Metadata Lake for Unified Data and AI Asset Management
Bilibili Tech
Bilibili Tech
May 13, 2025 · Big Data

Live Streaming Ecosystem Governance Architecture and Data Mining Engine Design

The article outlines a comprehensive live‑streaming ecosystem governance framework that combines data‑mining engines, tagging platforms, rule‑based disposal mechanisms, and multi‑stage user touchpoints to improve content quality, compliance, and platform sustainability.

Rule EngineTagging Systemcontent moderation
0 likes · 14 min read
Live Streaming Ecosystem Governance Architecture and Data Mining Engine Design
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
May 9, 2025 · Big Data

Mastering Multi‑AZ Replication in HDFS with AZ Mover

This article introduces AZ Mover, a lightweight HDFS client‑side tool that intelligently scans, schedules, and migrates block replicas across multiple availability zones, detailing its design goals, core workflow, command‑line options, concurrency controls, and future enhancements for robust big‑data disaster recovery.

AZ MoverCluster OperationsHDFS
0 likes · 9 min read
Mastering Multi‑AZ Replication in HDFS with AZ Mover
Big Data Technology & Architecture
Big Data Technology & Architecture
Apr 29, 2025 · Big Data

Big Data Interview Preparation: Data Governance, Iceberg Metadata, Lakehouse Best Practices, and Xiaohongshu HR Updates

The article reports Xiaohongshu’s cancellation of the big‑small week schedule and non‑compete clause, then provides a collection of big‑data interview questions—including data governance, Iceberg metadata management, and lakehouse production best practices—along with concise answers and resources for candidates.

LakehouseXiaohongshudata governance
0 likes · 7 min read
Big Data Interview Preparation: Data Governance, Iceberg Metadata, Lakehouse Best Practices, and Xiaohongshu HR Updates
Big Data Tech Team
Big Data Tech Team
Apr 28, 2025 · Big Data

Mastering Metadata, Master Data, and Data Governance: A Complete Guide

This article explains the core concepts of metadata, master data, data resources, data governance, and data management, outlines their roles, compares governance with management, and provides practical steps and best‑practice recommendations for building a robust enterprise data framework.

big datadata governancedata resources
0 likes · 15 min read
Mastering Metadata, Master Data, and Data Governance: A Complete Guide
DataFunSummit
DataFunSummit
Apr 7, 2025 · Artificial Intelligence

Bridging the Gap Between Large Models and Real‑World Applications with RAG and Agents

This article examines how Retrieval‑Augmented Generation (RAG) and multi‑agent technologies narrow the gap between large language models and practical deployment, highlighting their roles in operations automation, financial risk control, intelligent data governance, database localization, edge inference, and future AI‑driven solutions.

RAGdata governancefinancial risk management
0 likes · 8 min read
Bridging the Gap Between Large Models and Real‑World Applications with RAG and Agents
DataFunTalk
DataFunTalk
Apr 2, 2025 · Artificial Intelligence

Trends, Applications, and Future Directions of Large Models and Inference Acceleration

This article examines the current state and future prospects of large AI models and inference acceleration, covering technology trends, diverse application scenarios from research to industry, and the challenges and opportunities that lie ahead for intelligent data governance, multimodal agents, and AGI.

AGIAIInference Acceleration
0 likes · 11 min read
Trends, Applications, and Future Directions of Large Models and Inference Acceleration
Data Integration and Governance
Data Integration and Governance
Mar 28, 2025 · Big Data

What Does Data Governance Actually Do? A Data‑Quality Perspective

The article explains that data governance is a systematic combination of mechanisms, processes, platforms and capabilities focused on data quality, outlines an eight‑step quality workflow, defines eight quality dimensions, describes six concrete business values, and compares governance with the data middle‑platform concept.

Data LifecycleData Qualitydata governance
0 likes · 12 min read
What Does Data Governance Actually Do? A Data‑Quality Perspective