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Data Governance

687 articles · Page 2 of 7
Lao Guo's Learning Space
Lao Guo's Learning Space
Apr 24, 2026 · Artificial Intelligence

How to Build a Truly Usable AI‑Powered Natural Language Query System from Scratch

The article analyzes why natural‑language database queries often fail, outlines four technical routes, presents a five‑layer architecture with a business‑semantic middle layer, shares engineering best practices, a real‑world case study, and a product comparison to guide data companies in designing an effective intelligent query system.

AIData GovernanceNL2SQL
0 likes · 16 min read
How to Build a Truly Usable AI‑Powered Natural Language Query System from Scratch
DataFunSummit
DataFunSummit
Apr 24, 2026 · Artificial Intelligence

AI‑Driven Data Governance as a Service: Tencent Games' Paradigm Shift

This talk details how Tencent Games leverages AI to transform its data governance from rule‑based, passive processes into a semantic, service‑oriented paradigm, addressing resource waste, low collaboration efficiency, and scalability challenges while delivering measurable improvements in cost, speed, and asset quality.

AIAutomationBig Data
0 likes · 19 min read
AI‑Driven Data Governance as a Service: Tencent Games' Paradigm Shift
Big Data Tech Team
Big Data Tech Team
Apr 22, 2026 · Big Data

Inside Big Tech: Full Breakdown of AI Agents for Data Warehouse Governance

The article analyzes how leading internet companies embed AI agents across the entire data‑warehouse lifecycle to automate governance, presenting real‑world case studies from Alibaba, ByteDance, JD.com and Tencent, and quantifies benefits such as over 65% reduction in manual effort, 50% drop in metric duplication, and a 40% boost in resource utilization.

AI agentsAutomationBig Data
0 likes · 10 min read
Inside Big Tech: Full Breakdown of AI Agents for Data Warehouse Governance
Data Integration and Governance
Data Integration and Governance
Apr 21, 2026 · Big Data

Why Data Architecture Matters: A Complete Guide to Turning Data into Strategic Assets

The article explains how fragmented ERP, MES, and CRM data create silos, outlines the five-layer data architecture lifecycle, identifies three common implementation challenges, and offers practical criteria for selecting the right storage and processing solutions to turn data into reliable business assets.

Data GovernanceData LakeData Warehouse
0 likes · 13 min read
Why Data Architecture Matters: A Complete Guide to Turning Data into Strategic Assets
DataFunTalk
DataFunTalk
Apr 21, 2026 · Industry Insights

How AI Agents Are Redefining Data Governance: 5 Key Shifts and 3 Strategic Solutions

In the AI era, data consumption moves from a few technical users to all business staff, forcing a fundamental redesign of data governance across five dimensions—resource consumption, frequency, semantics, knowledge base, and modality—and proposing three actionable strategies to make data semantically rich, fully multimodal, and AI‑consumable.

AIData GovernanceMultimodal Data
0 likes · 18 min read
How AI Agents Are Redefining Data Governance: 5 Key Shifts and 3 Strategic Solutions
Big Data Tech Team
Big Data Tech Team
Apr 20, 2026 · Artificial Intelligence

How AI is Redefining Data Workflows: 4 Game‑Changing Paradigms Explained

The article outlines four AI‑driven breakthroughs reshaping data work—AI‑for‑Data automation, generative‑AI‑enhanced governance, NoETL real‑time lake ingestion, and next‑generation SQL analysis—detailing their problems, concrete case studies, implementation steps, pitfalls, and measurable efficiency gains.

AI for DataData GovernanceNoETL
0 likes · 12 min read
How AI is Redefining Data Workflows: 4 Game‑Changing Paradigms Explained
DataFunTalk
DataFunTalk
Apr 19, 2026 · Industry Insights

From ChatBI to DataAgent: Turning AI Demos into Trusted Enterprise Decision Engines

The live discussion breaks down the practical challenges of building enterprise‑grade Data Agents—from unified semantic layers and prompt engineering versus model fine‑tuning, to table discovery, multi‑turn memory, trust, cost control, and continuous improvement—showing why real‑world AI success hinges on system reliability rather than raw model power.

AIData AgentData Governance
0 likes · 17 min read
From ChatBI to DataAgent: Turning AI Demos into Trusted Enterprise Decision Engines
DataFunSummit
DataFunSummit
Apr 18, 2026 · Industry Insights

Why Palantir’s Ontology Beats Traditional Data Models – Insights from Industry Leaders

A closed‑door forum gathered experts from academia and leading Chinese tech firms to dissect Palantir’s ontology‑driven approach, comparing it with conventional data modeling, exploring AI integration, and highlighting the managerial and technical challenges that determine its success in enterprise environments.

Data GovernanceEnterprise AIIndustry Insights
0 likes · 27 min read
Why Palantir’s Ontology Beats Traditional Data Models – Insights from Industry Leaders
Smart Sea Tide
Smart Sea Tide
Apr 17, 2026 · Industry Insights

Data Governance Tools: Strategic, Management, and Operational Layers

The 2021 Data Governance Tool Map Report categorizes data governance solutions into three capability‑based layers—strategic, management, and operational—detailing the process domains each layer addresses and providing a visual panorama to guide enterprises in selecting and standardizing tools.

Data GovernanceData Managementindustry report
0 likes · 4 min read
Data Governance Tools: Strategic, Management, and Operational Layers
Data Integration and Governance
Data Integration and Governance
Apr 16, 2026 · Big Data

Why Is Metadata Management So Hard? A Practical Guide to Overcoming the Challenges

The article analyzes why metadata management often stalls in enterprises—due to scattered, inactive, and business‑misaligned metadata—and outlines a step‑by‑step approach to define core asset, relationship, and semantic information, automate collection from data flows, and build a queryable metadata network.

Data GovernanceData IntegrationMetadata
0 likes · 11 min read
Why Is Metadata Management So Hard? A Practical Guide to Overcoming the Challenges
Big Data Tech Team
Big Data Tech Team
Apr 15, 2026 · Industry Insights

How to Harness Large Language Models for Effective Data Governance: Real Scenarios, Pitfalls, and Best Practices

This article analyzes how large language models can be integrated into data governance workflows, outlines three practical use cases, identifies five common implementation traps, offers best‑practice recommendations, and presents a real hospital case that demonstrates measurable performance gains.

AIData GovernanceLarge Language Models
0 likes · 13 min read
How to Harness Large Language Models for Effective Data Governance: Real Scenarios, Pitfalls, and Best Practices
Data Integration and Governance
Data Integration and Governance
Apr 13, 2026 · Fundamentals

Data Warehouse Demystified: What It Is, Why You Need It, and How to Build One

The article explains that a data warehouse is an analysis‑oriented data management system that integrates, cleans, and stores enterprise data to provide a single, trustworthy source for reporting and decision‑making, outlines common data problems, and presents a step‑by‑step methodology—including goal definition, source integration, layering, governance, and BI connection—to successfully build and maintain one.

Business IntelligenceData GovernanceData Integration
0 likes · 14 min read
Data Warehouse Demystified: What It Is, Why You Need It, and How to Build One
Data Integration and Governance
Data Integration and Governance
Apr 10, 2026 · Fundamentals

What Are Data Elements and Why They Matter for Business Value

The article explains the concept of data elements—data that is organized, shared, and applied to create continuous business value—by outlining their definition, common challenges such as scattered, messy, and unstable data, and how integration tools like FineDataLink help turn raw data into usable assets.

Business IntelligenceData GovernanceData Integration
0 likes · 9 min read
What Are Data Elements and Why They Matter for Business Value
dbaplus Community
dbaplus Community
Apr 2, 2026 · Operations

Why Most CMDB Projects Fail and How to Build a Sustainable Data Engine

The article analyzes common pitfalls of CMDB implementations, explains why overly comprehensive models collapse, and proposes a consumption‑driven, federated, and automation‑focused approach that integrates monitoring, ITSM, and FinOps to achieve continuous data quality and business value.

AutomationCMDBData Governance
0 likes · 13 min read
Why Most CMDB Projects Fail and How to Build a Sustainable Data Engine
dbaplus Community
dbaplus Community
Mar 31, 2026 · Industry Insights

Why Most Data Governance Projects Fail and How to Build a Practical, Engineer‑Friendly Solution

Most companies see data governance fail not because of technology but because they start with the wrong direction, focusing on rules, platforms, and processes that add friction instead of improving data usability, and the article provides a step‑by‑step, low‑overhead approach with concrete SQL and Python templates to fix it.

Data GovernancePythonQuality Monitoring
0 likes · 25 min read
Why Most Data Governance Projects Fail and How to Build a Practical, Engineer‑Friendly Solution
Big Data Tech Team
Big Data Tech Team
Mar 30, 2026 · Big Data

2026 Data Warehouse Interview Guide: Essential Questions for All Three Rounds

This article compiles a comprehensive set of data‑warehouse interview questions—including self‑introduction prompts, SQL and window‑function challenges, data‑skew solutions, architecture design, file‑format trade‑offs, governance, and team‑leadership topics—to help candidates prepare for first, second, and third‑round interviews at leading tech firms.

Big DataData GovernanceInterview Preparation
0 likes · 7 min read
2026 Data Warehouse Interview Guide: Essential Questions for All Three Rounds
Data Integration and Governance
Data Integration and Governance
Mar 30, 2026 · Big Data

A Clear Explanation of Data Middle Platforms: Design, Build, Avoid Pitfalls

The article defines a data middle platform as a unified capability that continuously aggregates, governs, and serves enterprise data, outlines its six‑module architecture, details practical technology choices, governance steps, performance optimizations, and a four‑stage implementation roadmap, and warns against common pitfalls such as business‑tech misalignment and neglect of unstructured data.

Big DataData GovernanceData Integration
0 likes · 13 min read
A Clear Explanation of Data Middle Platforms: Design, Build, Avoid Pitfalls
DataFunSummit
DataFunSummit
Mar 25, 2026 · Big Data

How Apache Gravitino and OpenLineage Transform Data Governance for AI‑Driven Enterprises

In the era of AI and multi‑cloud, this article analyzes the core challenges of data governance—data silos, quality gaps, and compliance risks—and explains how Apache Gravitino’s unified metadata architecture together with OpenLineage’s standardized lineage model provide a scalable, automated solution for intelligent, real‑time data management.

Apache GravitinoBig DataData Governance
0 likes · 15 min read
How Apache Gravitino and OpenLineage Transform Data Governance for AI‑Driven Enterprises
Data Integration and Governance
Data Integration and Governance
Mar 25, 2026 · Industry Insights

Master Data Management Explained: Practical Steps to Eliminate Data Silos

This article outlines why duplicate customer entries, inconsistent supplier data, and chaotic material codes increase communication costs and risk, then details a complete MDM approach—including data standards, coding rules, modeling, quality control, lifecycle management, integration, governance, and PDCA‑driven continuous improvement—to create a single, trustworthy version of core enterprise data.

Data GovernanceData IntegrationMDM
0 likes · 12 min read
Master Data Management Explained: Practical Steps to Eliminate Data Silos
Data Integration and Governance
Data Integration and Governance
Mar 18, 2026 · Fundamentals

Finally, a Clear Guide to Managing Data Quality End‑to‑End

The article explains why data quality is critical for reliable business decisions and walks through a complete end‑to‑end management framework—including lifecycle stages, organizational responsibilities, processes, tools, culture, and six practical methods such as cleaning, deduplication, standardization, validation, monitoring, and repair.

Data GovernanceData ManagementETL
0 likes · 12 min read
Finally, a Clear Guide to Managing Data Quality End‑to‑End
TonyBai
TonyBai
Mar 17, 2026 · Industry Insights

What Will AI Engineers Really Face in 2026? A Post‑Bubble Reality Check

The article analyses the shifting AI engineering job market, exposing a crowded hiring landscape, rapid skill depreciation, over‑reliance on generative AI, and the need for data governance and fundamental engineering skills to stay relevant by 2026.

AI ToolsAI engineeringData Governance
0 likes · 9 min read
What Will AI Engineers Really Face in 2026? A Post‑Bubble Reality Check
ITPUB
ITPUB
Mar 17, 2026 · Interview Experience

Expert Links Microservices to Financial AI: Architecture and Data Governance

In this interview, senior technology specialist Chen Ke shares how he adapts internet‑scale microservice and PaaS practices to the highly regulated financial sector, discusses building enterprise knowledge‑base platforms with large language models, outlines data‑governance and compliance strategies, and predicts the evolving skill set engineers will need.

AIData Governanceengineer skills
0 likes · 15 min read
Expert Links Microservices to Financial AI: Architecture and Data Governance
Data Integration and Governance
Data Integration and Governance
Mar 13, 2026 · Fundamentals

Why a Simple Field Rename Can Break Core Reports—and How to Build a Reliable Data Lineage System

A minor field name change can cause downstream report failures, exposing the lack of a formal data lineage; this article defines data lineage, outlines its four core dimensions, compares granularity levels, and presents a step‑by‑step architecture and governance process for establishing a practical lineage system.

Data GovernanceData WarehouseETL
0 likes · 9 min read
Why a Simple Field Rename Can Break Core Reports—and How to Build a Reliable Data Lineage System
Data Integration and Governance
Data Integration and Governance
Mar 11, 2026 · Databases

Data Model vs Metric Model: Clear Differences Explained

The article clarifies the distinction between data models, which structure and store business data, and metric models, which define and manage business measurements, covering their core elements, construction logic, outputs, application stages, iteration frequency, and how they complement each other.

Data GovernanceData ModelingData Warehouse
0 likes · 10 min read
Data Model vs Metric Model: Clear Differences Explained
Past Memory Big Data
Past Memory Big Data
Mar 9, 2026 · Industry Insights

Why Growing AI Agents Make Data Platforms Indispensable for Enterprises

The article explains that as AI agents move from demos to production, enterprises discover that the real bottleneck is not model capability but the underlying data platform, which must provide reliable data ingestion, semantic organization, access control, evaluation, and real‑time capabilities for agents to operate safely and effectively.

AI agentsData GovernanceEnterprise AI
0 likes · 11 min read
Why Growing AI Agents Make Data Platforms Indispensable for Enterprises
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 GovernanceMetric 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.

Data GovernanceData Warehousecompleteness
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 GovernanceQuality Assurance
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.

Data GovernanceLarge Language ModelsMathematics Dataset
0 likes · 15 min read
Breaking the Data Ceiling: UltraData’s 2.4 TB Tiered Dataset with the Largest L3 Math Library
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 SuiteData Governance
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.

Data GovernanceProcess Automationbusiness-IT alignment
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.

Big DataData Governancearchitecture quality
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.

Data GovernanceData WarehouseDatabase Design
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 AtlasData GovernanceHBase
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 GovernanceData LakeETL
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 Governancedata quality
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.

Big DataData GovernanceData Integration
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.

Business ValueData AssetData Governance
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 GovernanceData IntegrationETL
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 testingData GovernanceTest Automation
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 GovernanceData ModelingDataOps
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 ValueData Governancecapability building
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 Governancebusiness 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.

AIData GovernanceLarge Language Models
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 GovernanceMDMdata quality
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.

Data GovernanceDatabase DesignNoSQL
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 GovernanceData Product
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 GovernanceData StorageIoT
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.

Big DataData Governancedata lineage
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 GovernanceLangChain
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 GovernanceData ModelingData Warehouse
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.

Big DataData GovernanceETL
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 AssetData GovernanceData Management
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 GovernanceMetadatadata asset management
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.

Data GovernanceEnterprise AIKnowledge Graph
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.

Data GovernanceData IntegrationData Management
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.

Big DataData EngineeringData Governance
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.

Data Governancecost optimization
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 Governancedata qualitydata standards
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 platformData GovernanceDiagnostic Analysis
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 agentsBig DataData Governance
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.

Big DataData Governancedata 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 GovernanceData ModelingMetadata
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 GovernanceEthics
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.

Data GovernanceDatabase Designconceptual modeling
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 GovernanceData MetricsE-commerce Analytics
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.

Big DataData Governancebest practices
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 Governancedata architecturedata quality
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.

Big DataData GovernanceDouyin
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 AssetData GovernanceDouyin
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 Governance
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 GroupBig DataData Governance
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 CloudCloud NativeData Governance
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.

Data GovernanceData ManagementIndicator System
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.

Data GovernanceSQL lineagedata discovery
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 GovernanceIntelligent Operations
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.

AIData GovernanceIntelligent Operations
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.

AIData GovernanceTechnology
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.

AutomationData GovernanceDevOps
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.

Data GovernanceECMGartner
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.

Big DataData GovernanceData Management
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.

Data GovernanceData Metricsbusiness analytics
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.

Big DataData GovernanceResource Optimization
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.

Big DataData GovernanceData Management
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.

Big DataData GovernanceFlink
0 likes · 4 min read
Essential Big Data Interview Questions for Data Warehouse Engineer Roles
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 Governancedata assets
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.

Big DataData Governancearchitecture
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.

Data GovernanceLakehouseReal-Time Analytics
0 likes · 2 min read
Lakehouse Revolution: Real‑Time Analytics and Data Architecture Insights