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data architecture

257 articles · Page 1 of 3
Data Integration and Governance
Data Integration and Governance
Sep 4, 2026 · Big Data

ETL vs ELT vs ETLT: Where Should Data Transformation Live?

This article explains the core differences between ETL, ELT, and ETLT data integration patterns, emphasizing that the key distinction is where transformation occurs—before or after loading—and provides five decision criteria for choosing the right approach based on data latency, raw data retention, compute costs, and business logic volatility.

Data IntegrationData PipelineELT
0 likes · 16 min read
ETL vs ELT vs ETLT: Where Should Data Transformation Live?
Smart Sea Tide
Smart Sea Tide
Sep 4, 2026 · R&D Management

Enterprise Architecture: Business Domain Design, Multi-Layer Architecture & Governance

This article outlines enterprise architecture fundamentals using a 'four horizontal, five vertical' framework, detailing business domain design principles, typical design methods for business, data, application, and technical architectures, and governance practices including principles, reviews, and asset management to align IT with business strategy.

application architecturearchitecture frameworkarchitecture governance
0 likes · 13 min read
Enterprise Architecture: Business Domain Design, Multi-Layer Architecture & Governance
Data Integration and Governance
Data Integration and Governance
Aug 31, 2026 · Big Data

Data Agent Architecture: 7 Layers to Connect Enterprise Data Beyond Text-to-SQL

This article argues that enterprise Data Agents require a seven-layer data architecture—source, preparation, object, semantic, permission, execution, and verification—rather than simply connecting databases to LLMs, detailing how each layer resolves ambiguity, ensures stability, enforces security, and enables trustworthy analytical reasoning.

AI AnalyticsBusiness IntelligenceData Agent
0 likes · 18 min read
Data Agent Architecture: 7 Layers to Connect Enterprise Data Beyond Text-to-SQL
CTO Full-Stack Academy
CTO Full-Stack Academy
Aug 24, 2026 · Fundamentals

Understanding the Boundaries and Connections Between Business, Application, Data, and Technology Architecture

The article breaks down the four layers of enterprise digital architecture—business, application, data, and technology—explaining each layer's purpose, scope, key deliverables, and how they interrelate from top‑down direction setting to bottom‑up technical support, illustrated with a shopping‑center analogy and a campus ordering system case study.

Business Architectureapplication architecturedata architecture
0 likes · 11 min read
Understanding the Boundaries and Connections Between Business, Application, Data, and Technology Architecture
Smart Sea Tide
Smart Sea Tide
Aug 24, 2026 · Big Data

Big Data Governance Platform: 5-Layer Architecture, 9 Modules & 3-Phase Implementation

This article presents a comprehensive framework for building a big data governance platform, covering a five-layer architecture, nine core governance modules, a three-phase implementation roadmap, organizational structure, success metrics, and industry-specific selection guidance to transform chaotic data into trusted, findable, and controllable assets.

Data QualityImplementation Roadmapbig data governance
0 likes · 10 min read
Big Data Governance Platform: 5-Layer Architecture, 9 Modules & 3-Phase Implementation
Digital Deification
Digital Deification
Aug 17, 2026 · Industry Insights

BA vs DA: The Semantic Gap That Derails AI Projects — Ontology as the Missing Layer

The article explains how misaligned semantics between business architecture (BA) and data architecture (DA) — previously manageable via human translation — become fatal when AI systems require machine-executable logic, arguing that ontology provides the necessary rule-based semantic layer to align business objects with machine reasoning for reliable enterprise AI.

AI readinessBusiness ArchitectureOntology
0 likes · 7 min read
BA vs DA: The Semantic Gap That Derails AI Projects — Ontology as the Missing Layer
Data Integration and Governance
Data Integration and Governance
Aug 11, 2026 · Big Data

What Is Data Architecture? Clarifying Databases, Data Warehouses, Lakes, and Middle Platforms

As enterprises add more systems, data volumes explode while accessing it becomes harder; this article defines data architecture, explains how databases, data warehouses, data lakes, and data middle platforms each solve distinct layers, and outlines the key questions and challenges for building a unified, reusable data ecosystem.

Data Lakebig datadata architecture
0 likes · 13 min read
What Is Data Architecture? Clarifying Databases, Data Warehouses, Lakes, and Middle Platforms
Data Integration and Governance
Data Integration and Governance
Jul 29, 2026 · Fundamentals

Understanding Business, Application, Data, Technical, and Code Architecture: Differences and Relationships Explained

Enterprises embarking on digital transformation must grasp five architecture layers—business, application, data, technical, and code—each solving distinct problems, their inter‑relationships, and a step‑by‑step planning approach illustrated with real‑world manufacturing and ERP/CRM examples.

Business Architectureapplication architecturecode architecture
0 likes · 15 min read
Understanding Business, Application, Data, Technical, and Code Architecture: Differences and Relationships Explained
Smart Sea Tide
Smart Sea Tide
Jul 28, 2026 · Industry Insights

4A Architecture: Aligning Business, Data, Application, and Technology

The 4A architecture provides a full‑link methodology that connects business, data, application, and technology layers, enabling enterprises to avoid siloed projects, streamline digital initiatives, and build a cohesive, scalable digital capability in the long term.

4A architectureBusiness Architectureapplication architecture
0 likes · 5 min read
4A Architecture: Aligning Business, Data, Application, and Technology
Insight Construct
Insight Construct
Jul 27, 2026 · Industry Insights

What Is Enterprise Architecture and How It Aligns Strategy with Execution

The article explains Enterprise Architecture as a systematic, organization‑wide method that aligns business capabilities, processes, data, applications, and technology with strategic goals, clarifies common misconceptions, and illustrates its practical application through a detailed e‑commerce case study.

Business Architectureapplication architecturedata architecture
0 likes · 8 min read
What Is Enterprise Architecture and How It Aligns Strategy with Execution
IT Learning Made Simple
IT Learning Made Simple
Jul 25, 2026 · Industry Insights

What’s New in the 2026 System Architecture Designer Exam Syllabus?

The article explains why the exam syllabus is the first step for candidates, outlines the 2026 changes—including added cloud‑native, DevOps, and data‑architecture topics, refined microservice details, and reduced traditional software‑engineering content—shows the new weight distribution, and offers concrete study order, time‑allocation, learning methods, impact analysis, and resource recommendations.

DevOpscloud-nativedata architecture
0 likes · 8 min read
What’s New in the 2026 System Architecture Designer Exam Syllabus?
Data Integration and Governance
Data Integration and Governance
Jul 22, 2026 · Big Data

Data Warehouse vs Data Mart vs Data Lake vs Data Middle Platform: Clear Differences

The article explains how data warehouses, data marts, data lakes, and data middle platforms each address distinct problems—unified analytics, departmental needs, raw data storage, and governed reusable capabilities—while outlining their relationships, typical use cases, implementation considerations, and guidance on choosing the right architecture for a given business stage.

Data LakeData Martbig data
0 likes · 16 min read
Data Warehouse vs Data Mart vs Data Lake vs Data Middle Platform: Clear Differences
Data Integration and Governance
Data Integration and Governance
Jul 21, 2026 · Fundamentals

Confused About Databases vs Data Warehouses? A 10‑Year Expert Clarifies

Many enterprises with ERP, CRM and other systems mistakenly treat a data warehouse as just a larger database, but the article explains that databases support transaction processing while data warehouses provide a stable, unified analytics layer, detailing their distinct goals, architectures, layer designs and the critical role of reliable data integration.

AnalyticsData IntegrationData Modeling
0 likes · 13 min read
Confused About Databases vs Data Warehouses? A 10‑Year Expert Clarifies
DataFunTalk
DataFunTalk
Jul 14, 2026 · Big Data

How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era

Xiaohongshu transformed its data platform from a simple ClickHouse‑based stack to a Lambda‑enhanced architecture and finally to a Lakehouse with incremental compute, cutting architecture complexity, resource and development costs by two‑thirds while delivering second‑level analytics on petabyte‑scale data.

ClickHouseFlinkIncremental Compute
0 likes · 22 min read
How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era
DataFunTalk
DataFunTalk
Jul 11, 2026 · Big Data

How Xiaohongshu’s Data Architecture Evolved for the Big AI Data Era

The article details Xiaohongshu’s journey from a simple ClickHouse‑based ad‑hoc analytics stack to a Lambda‑style architecture and finally to a lakehouse with generic incremental compute, cutting architecture complexity, resource cost and development effort each to roughly one‑third while achieving sub‑10‑second query latency on petabyte‑scale data.

AIClickHouseIncremental Compute
0 likes · 21 min read
How Xiaohongshu’s Data Architecture Evolved for the Big AI Data Era
Data Integration and Governance
Data Integration and Governance
Jul 9, 2026 · Big Data

Data Warehouse vs Big Data Platform vs Data Lake vs Data Middle Platform vs Lake‑Warehouse Integration: What’s the Real Difference?

The article compares five data‑architecture concepts—data warehouse, big data platform, data lake, data middle platform, and lake‑warehouse integration—explaining the specific problems each solves, their core characteristics, advantages, risks, and guidance on when to adopt each solution.

Data IntegrationData LakeLake‑Warehouse Integration
0 likes · 12 min read
Data Warehouse vs Big Data Platform vs Data Lake vs Data Middle Platform vs Lake‑Warehouse Integration: What’s the Real Difference?
DataFunTalk
DataFunTalk
Jul 6, 2026 · Big Data

How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era

Xiaohongshu transformed its data platform from a simple ClickHouse‑based ad‑hoc analysis system to a Lambda‑style architecture and finally to a lakehouse with incremental compute, cutting architecture complexity, resource and development costs by one‑third while delivering second‑level queries over petabyte‑scale data.

ClickHouseFlinkIncremental Compute
0 likes · 23 min read
How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era
Data Integration and Governance
Data Integration and Governance
Jul 3, 2026 · Fundamentals

Data Governance Explained: Standards, Quality, Security, and Metadata Management

The article breaks down data governance into four essential pillars—data standards, data quality, data security, and metadata management—illustrating why each is critical, how they interrelate, and practical steps enterprises can take to embed them into data pipelines for trustworthy, secure, and discoverable analytics.

Data Qualitydata architecturedata governance
0 likes · 14 min read
Data Governance Explained: Standards, Quality, Security, and Metadata Management
DataFunTalk
DataFunTalk
Jun 30, 2026 · Big Data

How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era

Xiaohongshu, with over 3.5 billion monthly users and daily logs in the trillions, migrated 500 PB of data to Alibaba Cloud and iterated its data platform through four architecture generations—ClickHouse‑based ad‑hoc, Lambda, Lakehouse, and a unified incremental compute model—cutting resource, development, and storage costs to one‑third while delivering sub‑10‑second query latency at petabyte scale.

ClickHouseFlinkIncremental Compute
0 likes · 22 min read
How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era
DataFunTalk
DataFunTalk
Jun 24, 2026 · Big Data

How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era

Xiaohongshu, with over 350 million monthly users and daily logs in the billions, migrated its data platform from AWS to Alibaba Cloud and iterated four times—from a ClickHouse‑based ad‑hoc layer to a Lambda architecture and finally a Lakehouse with incremental compute—cutting architecture complexity, resource cost and development effort each to about one‑third while delivering second‑level analytics on trillion‑scale data.

ClickHouseFlinkIncremental Compute
0 likes · 22 min read
How Xiaohongshu Re‑engineered Its Data Architecture for the Big AI Data Era
TechVision Expert Circle
TechVision Expert Circle
Jun 23, 2026 · Artificial Intelligence

The AI Era’s Top Strategic Mistakes CTOs Keep Making (Part 2)

This article examines the hidden but costly strategic errors CTOs make when adopting AI—treating AI as a simple module, blindly building large models, ignoring AI‑native data architecture, applying traditional R&D management to AI teams, and postponing safety and compliance—offering a concrete self‑check checklist.

AI strategyCTOMoE routing
0 likes · 12 min read
The AI Era’s Top Strategic Mistakes CTOs Keep Making (Part 2)
DataFunTalk
DataFunTalk
Jun 20, 2026 · Big Data

How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era

The article details Xiaohongshu's step‑by‑step migration from a simple ClickHouse‑based analytics stack to a Lambda‑style 2.0 architecture and finally to a Lakehouse‑based 3.0 design, highlighting concrete performance numbers, cost reductions, and the definition of a generic incremental‑compute model (SPOT) that underpins the evolution.

ClickHouseFlinkIncremental Compute
0 likes · 22 min read
How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era
IT Learning Made Simple
IT Learning Made Simple
Jun 14, 2026 · Industry Insights

Why Data Architects Are the Hottest Talent in the DT Era

The article explains why data architects have become essential in the DT era, detailing their responsibilities, core skills, big‑data technology stack, governance practices, career paths, and the tools they use to turn data into a strategic asset for enterprises.

Career PathData Modelingbig data
0 likes · 9 min read
Why Data Architects Are the Hottest Talent in the DT Era
IT Learning Made Simple
IT Learning Made Simple
Jun 4, 2026 · Fundamentals

One Diagram That Reveals the Full Software Architecture Family Tree

This article uses a single family‑tree diagram to explain the three generations of software architecture—enterprise, application, and domain‑specific architectures—detailing their layers, typical concerns, common tools, and the 4+1 view model for describing systems from multiple perspectives.

Security Architectureapplication architecturearchitecture taxonomy
0 likes · 7 min read
One Diagram That Reveals the Full Software Architecture Family Tree
DataFunTalk
DataFunTalk
May 28, 2026 · Big Data

How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era

Xiaohongshu transformed its data platform from a simple ClickHouse‑based ad‑hoc analysis to a Lambda‑style architecture and finally to a lakehouse with generic incremental compute, cutting architecture complexity, resource and development costs by one‑third while delivering second‑level queries over trillions of rows.

ClickHouseFlinkIncremental Compute
0 likes · 21 min read
How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era
DataFunTalk
DataFunTalk
May 22, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Complexity and Cost by One‑Third in the Big AI Data Era

The article details Xiaohongshu's evolution from a simple ClickHouse‑based analytics layer to a Lambda‑enabled 2.0 stack and finally a Lakehouse‑based 3.0 architecture, showing how each iteration reduced infrastructure complexity, resource consumption and development effort by roughly one‑third while supporting trillions of daily events and AI‑driven use cases.

ClickHouseFlinkIncremental Compute
0 likes · 21 min read
How Xiaohongshu Cut Data Architecture Complexity and Cost by One‑Third in the Big AI Data Era
Data Integration and Governance
Data Integration and Governance
May 18, 2026 · Big Data

Why a Data Middle Platform Is Essential: A Complete Guide to Its Architecture and Components

The article explains why a data middle platform is a prerequisite for AI initiatives, outlines its functional architecture—data asset, tool platform, and application layers—and details the technical stack from ingestion and storage to compute, governance, and service layers, providing concrete examples and best‑practice recommendations.

ETLbig datadata architecture
0 likes · 14 min read
Why a Data Middle Platform Is Essential: A Complete Guide to Its Architecture and Components
DataFunTalk
DataFunTalk
May 6, 2026 · Big Data

How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era

The article details Xiaohongshu's four‑stage data‑platform evolution—from a simple ClickHouse ad‑hoc setup to a Lambda‑based 2.0 design and finally a lakehouse‑driven 3.0 architecture—highlighting the adoption of general incremental compute, cost‑reduction to one‑third, performance gains of up to ten‑fold, and the SPOT standards that guide the new system.

ClickHouseFlinkIncremental Compute
0 likes · 21 min read
How Xiaohongshu Evolved Its Data Architecture for the Big AI Data Era
DataFunTalk
DataFunTalk
Apr 29, 2026 · Big Data

How Xiaohongshu Revamped Its Data Architecture for the Big AI Data Era

Xiaohongshu transformed its data platform from a simple ClickHouse‑based analytics stack to a unified lakehouse with generic incremental compute, cutting architecture complexity, resource cost, and development effort by roughly one‑third while supporting petabyte‑scale, sub‑second queries across its 350 million‑user app.

ClickHouseFlinkIncremental Compute
0 likes · 22 min read
How Xiaohongshu Revamped Its Data Architecture for the Big AI Data Era
Data Integration and Governance
Data Integration and Governance
Apr 28, 2026 · Big Data

Data Warehouse, Data Lake, Data Middle Platform, Lake‑Warehouse Integration: Key Differences

This article systematically explains the definitions, architectures, advantages, disadvantages, and evolution of data warehouses, big‑data platforms, data lakes, data middle platforms, and lake‑warehouse integration, helping practitioners choose the right terminology and technology for their projects.

Data LakeFineDataLinkLake‑Warehouse Integration
0 likes · 12 min read
Data Warehouse, Data Lake, Data Middle Platform, Lake‑Warehouse Integration: Key Differences
DataFunTalk
DataFunTalk
Apr 22, 2026 · Industry Insights

How Xiaohongshu Cut Data Platform Costs by Two‑Thirds with Incremental Computing

This article details Xiaohongshu's journey from a ClickHouse‑based batch analytics stack to a unified lakehouse architecture powered by generic incremental computing, showing how the company reduced architecture complexity, resource consumption and development effort each to roughly one‑third while supporting trillions of daily events with sub‑10‑second query latency.

LakehouseXiaohongshubig data
0 likes · 24 min read
How Xiaohongshu Cut Data Platform Costs by Two‑Thirds with Incremental Computing
JD Tech
JD Tech
Apr 16, 2026 · Industry Insights

How JD Revolutionized Coupon Search with a Stream‑Batch Unified Architecture

This article analyzes JD's end‑to‑end upgrade of its retail coupon search infrastructure, detailing the business drivers, data‑skew challenges, the shift from dual KV and batch pipelines to a unified stream‑batch model built on Apache Doris, and the resulting performance, resource and stability gains across multiple scenarios.

Apache DorisBatch ProcessingCoupon Search
0 likes · 12 min read
How JD Revolutionized Coupon Search with a Stream‑Batch Unified Architecture
DataFunTalk
DataFunTalk
Apr 16, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing

This article details Xiaohongshu's data platform evolution from a simple ClickHouse‑based ad‑hoc system to a Lambda‑style architecture and finally a lakehouse solution, highlighting how the adoption of a new incremental computing model reduced architectural complexity, resource consumption and development effort each to roughly one‑third while delivering sub‑second query performance on petabyte‑scale data.

LakehousePerformance OptimizationXiaohongshu
0 likes · 21 min read
How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing
DataFunTalk
DataFunTalk
Apr 10, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing

This article analyzes Xiaohongshu's data platform evolution—from a simple ClickHouse‑based analytics layer to a Lambda architecture and finally a lakehouse design—highlighting how adopting a new incremental computing model reduced architecture complexity, resource consumption, and development effort each to roughly one‑third while delivering sub‑second query performance on petabyte‑scale data.

LakehousePerformance OptimizationXiaohongshu
0 likes · 22 min read
How Xiaohongshu Cut Data Architecture Costs by Two‑Thirds with Incremental Computing
AI Info Trend
AI Info Trend
Apr 8, 2026 · Artificial Intelligence

Why Strong Data Foundations Are Crucial for Scaling Agentic AI

A McKinsey report reveals that while two‑thirds of enterprises have tried agentic AI, less than 10% achieve scalable value, and robust, modern data architectures—built on seven concrete principles and a four‑step implementation plan—are the decisive factor.

AI scalingAgentic AIEnterprise AI
0 likes · 7 min read
Why Strong Data Foundations Are Crucial for Scaling Agentic AI
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Apr 7, 2026 · Artificial Intelligence

How a Four‑Layer Pyramid Powers AI‑Driven Autonomous Ship Navigation

The article dissects the four‑layer data architecture that transforms raw maritime charts into structured knowledge, enables large models to reason about navigation scenarios, and combines algorithmic route screening with LLM‑based refinement to deliver safe, compliant, and efficient autonomous ship routing.

AIMaritimeautonomous navigation
0 likes · 12 min read
How a Four‑Layer Pyramid Powers AI‑Driven Autonomous Ship Navigation
Data Integration and Governance
Data Integration and Governance
Mar 31, 2026 · Fundamentals

Designing Data Architecture: A Complete Guide to Core Components and Principles

This article explains what data architecture really means, outlines its four essential components—data asset catalog, data standards, data model, and data distribution—and provides a step‑by‑step methodology, design principles, and practical examples for building a robust enterprise‑wide data architecture.

Enterprise Datadata architecturedata standards
0 likes · 14 min read
Designing Data Architecture: A Complete Guide to Core Components and Principles
DataFunSummit
DataFunSummit
Mar 27, 2026 · Industry Insights

Why Traditional Data Platforms Fail and How Ontology Delivers Triple‑Digit ROI

The article examines costly data platform failures—such as a $40 million payroll system collapse and a healthcare.gov outage—highlighting why traditional data middle platforms become data swamps, then explains how Palantir’s ontology approach, with its three‑layer semantic, dynamics, and decision architecture, can turn data into actionable insights and achieve triple‑digit ROI.

OntologyPalantirROI
0 likes · 4 min read
Why Traditional Data Platforms Fail and How Ontology Delivers Triple‑Digit ROI
DataFunSummit
DataFunSummit
Mar 26, 2026 · Industry Insights

Why Traditional Data Platforms Fail and How Ontology Drives Triple‑Digit ROI

The article analyzes costly data‑platform failures—such as a $40 million school‑district payroll system and a collapsed Healthcare.gov launch—identifies the root cause as ineffective data middle platforms, and explains how Palantir’s ontology‑based three‑layer architecture (semantic, dynamics, decision) transforms raw data into automated business actions, delivering measurable ROI across multiple industries.

Decision AutomationDigital TwinOntology
0 likes · 5 min read
Why Traditional Data Platforms Fail and How Ontology Drives Triple‑Digit ROI
vivo Internet Technology
vivo Internet Technology
Mar 25, 2026 · Industry Insights

How Vivo Scaled Marketing Automation with Presto, Bitmap, and StarRocks

This case study details how Vivo’s marketing automation platform evolved its data‑driven architecture—from a Presto‑based wide‑table design, through a Bitmap optimization, to a StarRocks migration—addressing performance bottlenecks, reducing resource costs, and enhancing data security.

BitmapOLAPPerformance Optimization
0 likes · 11 min read
How Vivo Scaled Marketing Automation with Presto, Bitmap, and StarRocks
DataFunSummit
DataFunSummit
Mar 19, 2026 · Industry Insights

Why Traditional Data Platforms Fail and How Ontology Delivers Triple‑Digit ROI

The article examines why costly traditional data middle platforms often become data swamps, contrasts them with Palantir's ontology‑based approach that acts like a navigation system, and outlines a three‑layer architecture that turns data into automated business actions, delivering multi‑hundred‑percent ROI.

Business IntelligenceDigital TwinOntology
0 likes · 4 min read
Why Traditional Data Platforms Fail and How Ontology Delivers Triple‑Digit ROI
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.

ETLOwnershipdata architecture
0 likes · 9 min read
Why a Simple Field Rename Can Break Core Reports—and How to Build a Reliable Data Lineage System
StarRocks
StarRocks
Mar 5, 2026 · Big Data

How Fanatics Scaled to PB‑Level Data with StarRocks & Apache Iceberg Lakehouse

Fanatics unified its fragmented data stack by building a StarRocks‑powered Lakehouse on Apache Iceberg, replacing Redshift, Snowflake, Athena, and Druid, which cut costs by up to 95%, delivered sub‑second dashboard queries on petabyte‑scale data, and enabled real‑time and historical analytics on a single platform.

Apache IcebergFanaticsLakehouse
0 likes · 10 min read
How Fanatics Scaled to PB‑Level Data with StarRocks & Apache Iceberg Lakehouse
LuTiao Programming
LuTiao Programming
Jan 27, 2026 · Big Data

Why LinkedIn Is Replacing Kafka with Its Own Next‑Gen Streaming System

LinkedIn, facing planetary‑scale data volumes, found Kafka’s architecture hitting fundamental limits and built Northguard—a decentralized, log‑striped streaming platform with Raft‑based metadata and an Xinfra migration layer—to gradually replace Kafka’s core responsibilities while maintaining compatibility.

KafkaLinkedInNorthguard
0 likes · 8 min read
Why LinkedIn Is Replacing Kafka with Its Own Next‑Gen Streaming System
StarRocks
StarRocks
Jan 22, 2026 · Big Data

How Paimon + StarRocks Accelerates Double‑11 OLAP Queries by 80% Refresh Speed

This article explains how Taotian Group unified real‑time and offline data using Paimon as lake storage and StarRocks for high‑performance OLAP, eliminating costly sync pipelines, cutting refresh time by about 80%, saving nearly ten million yuan annually, and detailing the architecture, cluster safeguards, configuration tweaks, monitoring, and future roadmap for large‑scale promotional events.

OLAPPaimonReal-time Analytics
0 likes · 24 min read
How Paimon + StarRocks Accelerates Double‑11 OLAP Queries by 80% Refresh Speed
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
Data Integration and Governance
Data Integration and Governance
Jan 8, 2026 · Big Data

How to Design Data Architecture That Keeps Up With Rapid Business Changes

When business requirements change every few days, traditional data architectures become rigid, tightly coupled, and slow, causing endless cycles of overtime; this article analyzes the root causes and presents a layered, configurable, and API‑driven approach—including moderate redundancy, data catalogs, and decoupled layers—to enable data systems to adapt quickly and reliably.

APIData Modelingconfigurable processing
0 likes · 9 min read
How to Design Data Architecture That Keeps Up With Rapid Business Changes
iQIYI Technical Product Team
iQIYI Technical Product Team
Jan 8, 2026 · Big Data

How iQIYI Cut Stream Data Costs by 70%: From Private‑Cloud Kafka to AutoMQ

This article details iQIYI's evolution from a tightly coupled private‑cloud Kafka setup to a cloud‑native AutoMQ architecture, describing the challenges of scaling, the development of the Stream platform and Stream‑SDK, the migration to hybrid and public‑cloud Kafka, and the resulting cost and elasticity improvements.

AutoMQKafkacloud migration
0 likes · 12 min read
How iQIYI Cut Stream Data Costs by 70%: From Private‑Cloud Kafka to AutoMQ
Lakehouse Research Base
Lakehouse Research Base
Jan 8, 2026 · Big Data

SME Data Architecture Selection: Lightweight Lakehouse Implementation Guide

This article provides a practical framework for SMEs to select and implement data platform architectures, comparing traditional warehouses, lakehouse, and multimodal data lakes across cost, ROI, and operational efficiency, with scenario-based recommendations and a lightweight lakehouse implementation guide using open-source stack Flink, Paimon, StarRocks, and MinIO.

Data LakeFlinkLakehouse
0 likes · 21 min read
SME Data Architecture Selection: Lightweight Lakehouse Implementation Guide
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
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Dec 16, 2025 · R&D Management

All Six Architecture Layers Explained with Real‑World E‑Commerce Examples

The article defines business, product, application, data, technical, and project architectures, outlines each layer’s purpose, key components, and provides concrete e‑commerce case studies, then illustrates how the layers interrelate and depend on one another to align strategy with implementation.

Business ArchitectureProduct Architectureapplication architecture
0 likes · 11 min read
All Six Architecture Layers Explained with Real‑World E‑Commerce Examples
Data Integration and Governance
Data Integration and Governance
Dec 9, 2025 · Fundamentals

A Clear Breakdown of the Four Core Architectures: Business, Application, Data, Technical

The article explains the distinct purposes, key concerns, and interrelationships of business, application, data, and technical architectures, showing how each layer derives from business goals, guides system design, manages data assets, and provides the stable platform needed for reliable, scalable operations.

Business Architectureapplication architecturearchitecture
0 likes · 11 min read
A Clear Breakdown of the Four Core Architectures: Business, Application, Data, Technical
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
dbaplus Community
dbaplus Community
Nov 13, 2025 · Databases

Why Modern DBAs Must Evolve into Data‑Business Architects (DBA²)

The article explores the challenges faced by traditional DBAs, redefines the DBA role as a blend of data, business, administration and architecture, presents multiple real‑world cases, and shows how AI and a DBA² mindset can dramatically improve efficiency and career prospects.

AI IntegrationCase StudiesDatabase Administration
0 likes · 19 min read
Why Modern DBAs Must Evolve into Data‑Business Architects (DBA²)
DataFunSummit
DataFunSummit
Nov 10, 2025 · Big Data

How Xiaohongshu Cut Data Architecture Costs by One‑Third with Incremental Computing

This article explains how Xiaohongshu, a lifestyle community with over 350 million monthly users, transformed its data platform from a traditional Lambda architecture to a next‑generation incremental computing model, reducing architectural complexity, resource consumption and development effort each by roughly two‑thirds while supporting massive real‑time and offline data demands.

AIXiaohongshubig data
0 likes · 6 min read
How Xiaohongshu Cut Data Architecture Costs by One‑Third with Incremental Computing
Instant Consumer Technology Team
Instant Consumer Technology Team
Oct 29, 2025 · Big Data

Revolutionizing Feature Engineering with Distributed Tech & Configurable Services

Facing PB‑scale user behavior data and millions of feature dimensions, the platform transformed its search, advertising, and recommendation pipelines by adopting a distributed, configurable‑service architecture that delivers high‑throughput streaming, elastic storage, rapid feature iteration, and robust fault‑tolerance for AI‑driven personalization.

big datadata architecturedistributed systems
0 likes · 17 min read
Revolutionizing Feature Engineering with Distributed Tech & Configurable Services
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 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
IT Architects Alliance
IT Architects Alliance
Sep 21, 2025 · Big Data

From Data Warehouses to Lakehouses: Why Data Architecture Keeps Evolving

This article traces the three‑generation evolution of data architecture—from the structured‑data era of data warehouses, through the flexible, multi‑format data lake, to the unified lakehouse model—explaining the drivers, benefits, challenges, and future trends shaping modern data platforms.

Data LakeLakehousedata architecture
0 likes · 11 min read
From Data Warehouses to Lakehouses: Why Data Architecture Keeps Evolving
Efficient Ops
Efficient Ops
Sep 18, 2025 · Artificial Intelligence

How ICBC Revolutionized Credit‑Card Risk Management with AI‑Driven Data Architecture

ICBC’s Software Development Center built an AI‑powered, multi‑layer data platform and decision engine that enables real‑time, precise risk monitoring and automated response for credit‑card operations, dramatically improving detection speed, coverage, and warning quality while supporting a full‑process intelligent risk‑control loop.

AI risk managementCredit Carddata architecture
0 likes · 11 min read
How ICBC Revolutionized Credit‑Card Risk Management with AI‑Driven Data Architecture
Big Data Tech Team
Big Data Tech Team
Sep 17, 2025 · Big Data

How to Build a Scalable Tag System for Recommendation Engines

This article explains why a robust tag system is essential for recommendation and mining strategies, outlines the hierarchy of entity, concept, and theme tags, and provides practical principles, architecture, and step‑by‑step methods for constructing and managing tags in large‑scale data platforms.

big datadata architecturedata labeling
0 likes · 14 min read
How to Build a Scalable Tag System for Recommendation Engines
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
StarRocks
StarRocks
Aug 19, 2025 · Big Data

How Joydata Scaled to 150 Billion Daily Events with StarRocks: A Data Architecture Journey

Facing daily data growth from millions to 150 billion records, Joydata‑U transformed its analytics platform through three architectural stages—Hadoop, Hadoop + Trino, and finally StarRocks—introducing resource isolation, Flat JSON acceleration, and Bitmap indexing to cut query latency by up to seven times and achieve sub‑2‑minute data freshness across BI, ad‑tech, game analytics, and CRM workloads.

Bitmap IndexFlat JSONFlink
0 likes · 12 min read
How Joydata Scaled to 150 Billion Daily Events with StarRocks: A Data Architecture Journey
DataFunSummit
DataFunSummit
Jul 20, 2025 · Big Data

How Beike Scaled to 600 PB: The Evolution of a Data‑Fusion Architecture

This article details Beike's data‑fusion architecture evolution, covering industry trends, multi‑stage Hadoop upgrades, storage cost optimization with erasure coding, remote shuffle integration, GPU‑centric training stability, and future hybrid‑cloud strategies, while also sharing organizational and operational lessons learned.

AICloud ComputingHadoop
0 likes · 16 min read
How Beike Scaled to 600 PB: The Evolution of a Data‑Fusion Architecture
DataFunTalk
DataFunTalk
Jul 13, 2025 · Big Data

Unlock Real-Time Multidimensional Insights with Cloud Lakehouse Technology

This guide presents a series of expert case studies and insights on how Cloud Lakehouse solutions enable real‑time, fully managed multidimensional data analysis, improve user data experiences, balance performance and cost, and power large‑scale IoT and big‑data platforms across industries.

IoTLakehouseReal-time Analytics
0 likes · 2 min read
Unlock Real-Time Multidimensional Insights with Cloud Lakehouse Technology
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
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
Data Thinking Notes
Data Thinking Notes
Dec 29, 2024 · Information Security

A Complete Blueprint for Enterprise Digital Transformation Architecture

This article presents a comprehensive visual guide to enterprise digital transformation, covering overall digital planning, application system architecture, data architecture, information security architecture, and digital organization and governance, illustrating each layer with detailed diagrams to aid strategic implementation.

data architecturedigital transformationenterprise architecture
0 likes · 5 min read
A Complete Blueprint for Enterprise Digital Transformation Architecture
DataFunSummit
DataFunSummit
Dec 29, 2024 · Big Data

Ant Group Data Architecture Practice and Upgrade Strategy

This article shares Ant Group's practical experience and evolution of data architecture, covering theoretical foundations, analysis of current challenges, proposed upgrade solutions based on domain‑driven design, and future outlook through complex network theory to improve scalability, governance, and resilience of large‑scale data systems.

Ant GroupDomain-Driven Designdata architecture
0 likes · 19 min read
Ant Group Data Architecture Practice and Upgrade Strategy
DataFunSummit
DataFunSummit
Dec 21, 2024 · Big Data

Big Data Implementation Practices and Architecture in a Foreign Bank

This article shares the foreign bank's big data implementation journey, covering background and goals, overall planning and architecture, practical insights, phased rollout, data governance, security, and Q&A, illustrating how a unified data platform, storage‑compute separation, and AI‑driven tools drive business innovation.

AIbankingdata architecture
0 likes · 19 min read
Big Data Implementation Practices and Architecture in a Foreign Bank
58 Tech
58 Tech
Dec 19, 2024 · Big Data

Architecture Evolution and Implementation of the Intelligent Acceleration Engine in the 58 Big Data Platform

The article details the background, architectural analysis, multi‑tenant redesign, engine selection enhancements, compatibility adaptations, stability fixes, containerized deployment, performance optimizations, and measurable business outcomes of the Intelligent Acceleration Engine upgrade using Apache Kyuubi and StarRocks within the 58 big data platform.

Apache KyuubiContainerizationSQL optimization
0 likes · 12 min read
Architecture Evolution and Implementation of the Intelligent Acceleration Engine in the 58 Big Data Platform
AntData
AntData
Nov 18, 2024 · Databases

Modern Data Paradigms: From Relational Databases to Vector Retrieval and AI

This article surveys the evolution of modern data technologies—from the 4V characteristics of big data and the limitations of traditional relational databases, through the rise of NoSQL and polyglot persistence, to embedding‑driven vector search, hybrid retrieval and RAG, illustrating how each paradigm frees applications from data constraints.

Artificial IntelligenceNoSQLbig data
0 likes · 30 min read
Modern Data Paradigms: From Relational Databases to Vector Retrieval and AI
Bilibili Tech
Bilibili Tech
Oct 25, 2024 · Big Data

DataFunSummit2024: Next-Generation Data Architecture Technology Summit

DataFunSummit2024, co-hosted by Bilibili, convenes industry experts, scholars, and enterprise leaders across six forums to discuss next‑generation data architecture, showcasing Bilibili’s Iceberg‑based stream‑batch innovations, AI‑BI analytics, NoETL practices, and emerging alternatives to Lambda architecture.

AI+BILambda ArchitectureNoETL
0 likes · 3 min read
DataFunSummit2024: Next-Generation Data Architecture Technology Summit
Big Data Technology & Architecture
Big Data Technology & Architecture
Oct 22, 2024 · Big Data

Key Frameworks and Characteristics of Lakehouse Architecture: A Ground‑Level Perspective

This article reviews the emerging lakehouse architecture, outlines its core frameworks such as Hudi, Iceberg, Paimon, Flink, and Doris, discusses their storage‑compute separation, read‑write optimizations, and highlights how companies of different sizes adopt these technologies based on cost, efficiency, and specific business scenarios.

DorisFlinkLakehouse
0 likes · 6 min read
Key Frameworks and Characteristics of Lakehouse Architecture: A Ground‑Level Perspective
DataFunTalk
DataFunTalk
Oct 3, 2024 · Big Data

Data Lake Technology Maturity Curve: Architecture, Design Principles, Core Functions, and Open‑Source Solutions

Amid growing data demands, this article explains the data lake technology maturity curve, detailing lake‑warehouse architectural patterns, design principles, core functionalities, and the four leading open‑source solutions (Hudi, Iceberg, Delta Lake, Paimon) to guide enterprises in building flexible, scalable, and governed data platforms.

Data LakeDelta LakeHudi
0 likes · 10 min read
Data Lake Technology Maturity Curve: Architecture, Design Principles, Core Functions, and Open‑Source Solutions
JD Tech
JD Tech
Sep 28, 2024 · Big Data

From Early Coding to Big Data Architecture: A Personal Journey Through Data Platforms, Cloud Migration, and System Design

The article chronicles the author’s 30‑year programming career, detailing early experiences, the evolution from JavaScript projects to large‑scale big‑data architectures, cloud migration, business‑agnostic framework design, interactive analytics, and reflections on becoming an independent software architect.

Cloud ComputingSoftware Engineeringbig data
0 likes · 24 min read
From Early Coding to Big Data Architecture: A Personal Journey Through Data Platforms, Cloud Migration, and System Design
DataFunSummit
DataFunSummit
Sep 7, 2024 · Big Data

Observations on the Third Evolution of Data Infrastructure and the Next‑Generation Data Platform Architecture

This article reviews the current state of data platforms, analyzes the third wave of data infrastructure evolution driven by databases, big data and generative AI, proposes next‑generation lakehouse and cloud‑native architectural directions, and outlines future trends and unresolved challenges for AI‑centric data platforms.

cloud-nativedata architecture
0 likes · 21 min read
Observations on the Third Evolution of Data Infrastructure and the Next‑Generation Data Platform Architecture
Data Thinking Notes
Data Thinking Notes
Jul 29, 2024 · Big Data

What Is a Data Middle Platform and How Does It Transform Enterprise Data Management?

This article explains the concept, design principles, and core components of a data middle platform, detailing its overall, functional, layered, logical, and data architectures, as well as the specific platforms for data collection, processing, organization, governance, quality, sharing, and visualization, illustrated with diagrams.

Data Integrationbig datadata architecture
0 likes · 27 min read
What Is a Data Middle Platform and How Does It Transform Enterprise Data Management?
Data Thinking Notes
Data Thinking Notes
Jul 22, 2024 · Fundamentals

Why Data Architecture Governance Is the Key to Successful Digital Transformation

Data architecture governance, encompassing standards, security, modeling, quality, and lifecycle management, is essential for digital transformation in fast‑growing industries like express delivery, and this article outlines current challenges, traditional approaches, and a practical, phased methodology with platform support to implement effective governance.

Data Modelingdata architecturedata governance
0 likes · 12 min read
Why Data Architecture Governance Is the Key to Successful Digital Transformation
DataFunTalk
DataFunTalk
Jul 17, 2024 · Databases

From DIKW to Distributed Data Warebase: Letting Data Emerge as Intelligence

This article explores the DIKW hierarchy, explains how data evolves into information, knowledge, and wisdom, examines traditional data models and products, critiques existing multi‑system architectures, and proposes a new distributed Data Warebase that unifies structured, semi‑structured, and vectorized knowledge to enable intelligent data-driven applications.

DIKWData SystemsDistributed Data Warehouse
0 likes · 24 min read
From DIKW to Distributed Data Warebase: Letting Data Emerge as Intelligence
DataFunSummit
DataFunSummit
Jul 2, 2024 · Cloud Computing

Global Perspective on Multi-Cloud Data Architecture

The forum presents a series of technical talks on multi‑cloud data architecture, covering Xiaomi’s lake‑warehouse practice, cross‑border e‑commerce data platforms, Alluxio‑based machine‑learning acceleration, Qichacha’s cost‑effective data solutions, and Kuaishou’s Flink on Kubernetes migration, highlighting strategies, implementations, and audience benefits.

Cloud ComputingMulti-Cloudbig data
0 likes · 8 min read
Global Perspective on Multi-Cloud Data Architecture
DevOps
DevOps
Jun 20, 2024 · Fundamentals

Understanding the 4A Enterprise Architecture: Business, Technology, Application, and Data Architecture

This article explains the TOGAF framework and its 4A architecture model—Business, Technology, Application, and Data Architecture—detailing each domain's definition, purpose, value, and step‑by‑step guidance for creating enterprise architecture diagrams to align strategy, processes, and technology.

Business ArchitectureTOGAFapplication architecture
0 likes · 8 min read
Understanding the 4A Enterprise Architecture: Business, Technology, Application, and Data Architecture
Code Ape Tech Column
Code Ape Tech Column
May 28, 2024 · Databases

Query Separation: A Practical Approach to Optimizing Large Table Reads

This article explains the concept of query separation, outlines its suitable scenarios, compares implementation methods such as synchronous, asynchronous, and binlog approaches, discusses storage system choices like MongoDB, HBase, and Elasticsearch, and addresses consistency and operational challenges when decoupling read workloads from write workloads.

ElasticsearchMQdata architecture
0 likes · 8 min read
Query Separation: A Practical Approach to Optimizing Large Table Reads
DataFunTalk
DataFunTalk
May 1, 2024 · Artificial Intelligence

A Comprehensive Guide to Vector Database Architecture and Application Scenarios

This article provides a detailed overview of vector database structures, their evolution, enterprise challenges, functional features, future trends, and key use cases, illustrating how they serve as the memory engine for large AI models and support multimodal data processing in modern data architectures.

AIdata architectureenterprise
0 likes · 11 min read
A Comprehensive Guide to Vector Database Architecture and Application Scenarios