Industry Solutions Overview

Singdata Lakehouse consolidates business scenarios that traditionally required multiple independent systems (stream processing clusters + AI inference services + data warehouses + BI + vector databases) into a single platform implemented with pure SQL, through core capabilities including Dynamic Table · AI Functions · Volume · PIPE · MERGE INTO · Window Functions · Full-text/Vector Search.

This page summarizes all currently published industry solutions to help you quickly locate the solution documentation that best matches your scenario.

Solution Landscape

AI & Intelligent Analytics

Solution	Industry	Core Need	Key Technologies
Manufacturing Part Defect AI Detection	Manufacturing	Dual-channel defect detection via image + text, tiered AI inference triggers	`AI_CLASSIFY` · `AI_EXTRACT` · `AI_COMPLETE` · Dynamic Table · Volume
Equipment Predictive Maintenance	Discrete / Process Manufacturing	IoT sensor rolling-mean anomaly detection + AI maintenance recommendation generation	`AI_COMPLETE` · Dynamic Table · BloomFilter Index · API Connection
Smart Mining Safety Early Warning	Mining / Heavy Industry	Cross-system correlated alerts across six subsystems + AI response suggestions + RAG retrieval over historical knowledge	`AI_CLASSIFY` · `AI_COMPLETE` · `AI_EMBEDDING` · Dynamic Table · Full-text/Vector/Hybrid Search
Customer Complaint Intelligent Labeling	E-commerce / Retail / Local Services	Automated ticket classification replacing manual labeling, latency ≤5 min	`AI_COMPLETE` · Dynamic Table · API Connection
Email Customer Support Auto-Triage	E-commerce / Consumer Electronics / Cross-border	Single AI call for intent classification + entity extraction + reply draft, latency ≤10 min	`AI_COMPLETE` · Dynamic Table · `REGEXP_EXTRACT` · `GET_JSON_OBJECT`
Product Review Sentiment Analysis	E-commerce Platform	Kafka review stream real-time sentiment classification + structured summary extraction	`AI_SENTIMENT` · `AI_COMPLETE` · `CREATE PIPE` · Dynamic Table
Content Platform Recommendation System Data Warehouse	Content Platform / Gaming	User interaction behavior + content metadata for recommendation feature engineering, supporting vector recall	Vector Index · Inverted Index · External Function · Dynamic Table · ZettaPark
Financial Fraud Ring Detection	Finance	Account-device-IP entity relationship graph for identifying fraud rings and black-market gangs	`MERGE INTO` · Dynamic Table · SQL UDF · BloomFilter Index · Inverted Index · ZettaPark

Retail & E-commerce

Solution	Industry	Core Need	Key Technologies
User Behavior Funnel Analysis	E-commerce / Local Services / Cross-border	Multi-channel funnel conversion rate auto-aggregation, latency ≤1 hour, pinpointing largest drop-off	Dynamic Table · `MERGE INTO` · `COUNT DISTINCT` · Window Functions
Supply Chain Inventory Optimization	Manufacturing / Retail / E-commerce	Dynamic replenishment decisions + real-time supplier lead time integration, replacing ERP static models	Window Functions · Dynamic Table · `MERGE INTO` · `AI_EXTRACT`
Retail Chain Store Operations Data Warehouse	Retail Chain	Nationwide POS multi-shard aggregation, partition-based incremental store rollup, month-end reconciliation with Time Travel	MySQL CDC · Dynamic Table · `PARTITIONED BY` · BloomFilter Index · External Schema · Time Travel
Retail Customer 360 Churn Prediction	Retail / E-commerce	Online + offline data unification, RFM segmentation + churn scoring, precision retention interventions	`MERGE INTO` · SQL UDF · Dynamic Table · Semantic View · BloomFilter Index
SKU-Level Demand Forecasting Data Warehouse	Retail / E-commerce	Parallel Prophet time-series model training across thousands of SKU × store combinations, driving auto-replenishment	MySQL CDC · Dynamic Table · ZettaPark Parallel Prophet · External Function
Weather × Retail Cross-Analysis	Retail	Weather data + store sales correlation, analyzing weather-driven demand amplification/suppression, supporting dynamic replenishment	External Function · Dynamic Table · Window Function Rolling Average · OSS PIPE
Supply Chain and Logistics Tracking Data Warehouse	Supply Chain / Logistics	OMS/WMS/TMS three-path heterogeneous data integration, unified SKU inventory turnover and shipment on-time rate monitoring	Dynamic Table · Kafka PIPE · OSS PIPE · BloomFilter Index · `MERGE INTO`

Marketing & User Growth

Solution	Industry	Core Need	Key Technologies
Digital Marketing CDP with Unified User ID	Marketing / Retail / E-commerce	Multi-channel OneID unification, RFM tag auto-refresh, BITMAP billion-scale audience segmentation	`MERGE INTO` · External Function · Dynamic Table · BITMAP · MySQL CDC
Multi-Channel Ad Attribution Data Warehouse	Marketing / E-commerce	Last Touch / Linear / Position-Based three-model comparison, ad ROI auto-calculation	Dynamic Table · Inverted Index · Table Stream · OSS PIPE · Kafka PIPE
Marketing Attribution and Uplift Modeling	Marketing / E-commerce	Distinguishing organic purchases from intervention increments, precision budget allocation, causal inference	Dynamic Table · BITMAP · ZettaPark Python Task · Kafka PIPE
Product Analytics Data Warehouse (Funnel + A/B Testing)	Internet / SaaS	Event stream multi-layer data warehouse, end-to-end funnel + A/B experiment conversion rate measurement	Window Functions · BITMAP · Table Stream · `MERGE INTO` · Dynamic Table

Finance & Risk Control

Solution	Industry	Core Need	Key Technologies
Real-Time Financial Risk Control Data Warehouse	Banking / Payments	Kafka transaction stream real-time ingestion, sliding window features + SQL UDF scoring, millisecond risk output	Kafka PIPE · Dynamic Table Sliding Window · SQL UDF · Column Masking
Insurance Core Business Compliance Reporting	Insurance	Policy / claims / customer data integration, meeting CBIRC compliance report requirements	Dynamic Table · Time Travel · Column Masking · RBAC · Oracle/PostgreSQL Batch Sync
Regulatory Reporting Data Warehouse (BCBS 239 / IFRS 9)	Banking / Securities	Reproducible snapshot at any point in time, IFRS 9 three-stage ECL classification, multi-role permission isolation	Time Travel · Dynamic Table · Column Masking · RBAC

Industrial & Manufacturing

Solution	Industry	Core Need	Key Technologies
Industrial IoT Device Health Monitoring	Industrial / Manufacturing	Real-time sensor ingestion, Bronze→Silver→Gold multi-layer data warehouse, device health scoring and predictive maintenance alerts	Kafka PIPE · Dynamic Table · BloomFilter Index · Column Masking · SQL UDF
Manufacturing SPC Quality Control Data Warehouse	Manufacturing	MES real-time inspection data + manual sampling, SPC control charts + Cpk process capability analysis + defect Pareto	Kafka PIPE · Dynamic Table · BloomFilter Index · SQL UDF · Sliding Window

Internet & SaaS

Solution	Industry	Core Need	Key Technologies
SaaS Multi-Tenant Operations Data Warehouse	SaaS	Kafka usage events + MySQL CDC integration, tenant health scoring + churn alerting, RBAC multi-role isolation	Kafka PIPE · MySQL CDC · Dynamic Table · SQL UDF · Column Masking · Semantic View
Gaming Operations Data Warehouse	Gaming	Player behavior event LTV segmentation, payment conversion funnel, N-day retention matrix	Kafka PIPE · OSS PIPE · Dynamic Table · BITMAP · LAG/LEAD Window Functions · BloomFilter Index
Online Education Learning Behavior Data Warehouse	Online Education	Learning behavior log multi-layer data warehouse, learning effectiveness scoring + high-risk student early warning	Kafka PIPE · Dynamic Table · Inverted Index · BITMAP · SQL UDF

Healthcare & Life Sciences

Solution	Industry	Core Need	Key Technologies
Healthcare Operations Data Warehouse	Healthcare	HIS/EMR/laboratory system integration, department KPI dashboards, patient privacy compliance	MySQL Batch Sync · Dynamic Table · Column Masking · RBAC · Time Travel
Healthcare FHIR Clinical Data Analysis	Healthcare	HL7 FHIR JSON ingestion, clinical quality indicator calculation, PHI field masking + historical snapshot auditing	JSON Nested Extraction · Dynamic Table · Column Masking · Time Travel

Government & Public Services

Solution	Industry	Core Need	Key Technologies
Smart City Data Platform	Government	Multi-department open data aggregation, cross-department joint analysis, PII masking + department data isolation	COPY INTO · Dynamic Table · External Schema · RBAC · Table Stream · Column Masking

Transportation & Mobility

Solution	Industry	Core Need	Key Technologies
Ride-Hailing Supply-Demand Analysis Data Warehouse	Mobility / Ride-hailing	Passenger orders + driver GPS real-time ingestion, city-level supply-demand analysis, dynamic pricing and incentive strategies	Kafka PIPE · Dynamic Table Partition Incremental · Table Stream · SQL UDF · Studio Task
Autonomous Driving Full-Loop Data Platform	Autonomous Driving	Road test data collection → labeling → training set → model iteration full loop	Dynamic Table · Volume · `AI_COMPLETE` · Table Stream

Energy & Time-Series

Solution	Industry	Core Need	Key Technologies
Energy Time-Series Data Warehouse	Energy / Power	Hourly load data peak-valley pricing strategy, load curve analysis, Z-score anomaly detection	Kafka PIPE · Dynamic Table · LAG/LEAD · ROWS BETWEEN Window Functions

Security & Compliance

Solution	Industry	Core Need	Key Technologies
SOC Log Analysis Data Warehouse	Cybersecurity / Enterprise IT	Firewall + IAM + application log centralized analysis, replacing/augmenting SIEM, threat detection + forensics	OSS PIPE · Dynamic Table · BloomFilter Index · Inverted Index · SQL UDF · Time Travel

HR & Human Resources

Solution	Industry	Core Need	Key Technologies
HR Employee Lifecycle Data Warehouse	Enterprise / HR	Full-lifecycle analysis from onboarding to departure, attrition risk prediction, pay equity analysis, organizational effectiveness diagnostics	Dynamic Table · Column Masking · LAG/LEAD Window Functions

Media & Content

Solution	Industry	Core Need	Key Technologies
Media Copyright Monitoring and Royalty Settlement	Media / Copyright	Content assets + licensing contracts + multi-platform playback transaction integration, royalty auto-attribution, month-end snapshot lock	OSS PIPE · CDC · Dynamic Table · Table Stream · `MERGE INTO` · Time Travel

Data Platform Architecture

Solution	Industry	Core Need	Key Technologies
Multi-Engine Iceberg Data Lake Federation	Data Platform	Iceberg tables written by Spark/Flink queried directly via federation without copying, Dynamic Table incremental processing	External Catalog (Iceberg REST) · Dynamic Table · OSS/S3/COS
Enterprise Data Mesh Productization	Data Platform	Each business domain manages its own Schema and data contracts independently, cross-domain federation queries, fine-grained consumption permissions	Domain Schema · Semantic View · RBAC · Cross-Domain Analytics
DataOps Pipeline Quality Gates	Data Platform	Automatic assertion checks after each layer refresh, non-conforming data isolated to Quarantine, failure alerting	Dynamic Table · Studio Task DAG · `information_schema.job_history`

Select by Technology Capability

Start from "I want to use a specific Lakehouse feature" and find corresponding reference solutions:

Technology Capability	Reference Solutions
`AI_CLASSIFY` (classification function)	Defect AI Detection · Smart Mining
`AI_EXTRACT` (structured extraction)	Defect AI Detection · Supply Chain Inventory Optimization
`AI_COMPLETE` (LLM inference)	Predictive Maintenance · Smart Mining · Complaint Labeling · Email Support · Product Reviews · Defect Detection · Autonomous Driving
`AI_SENTIMENT` (sentiment classification)	Product Review Sentiment Analysis
`AI_EMBEDDING` (text vectorization)	Smart Mining (historical incident semantic retrieval + RAG)
Dynamic Table (incremental computation)	Used in all solutions
`MERGE INTO` (idempotent archiving / UPSERT)	Supply Chain Inventory · User Behavior Funnel · Retail Customer 360 · Marketing CDP · Ad Attribution · Fraud Detection · Copyright Settlement
Window Functions (multi-time-window / rolling average)	Supply Chain Inventory · Smart Mining · User Behavior Funnel · Energy Time-Series · Gaming Operations · Ride-Hailing Operations · Product Analytics · HR Data Warehouse · Manufacturing SPC
`CREATE PIPE` (Kafka / OSS ingestion)	Product Reviews · IoT Device Health · Gaming Operations · Real-Time Risk Control · SaaS Operations · Ride-Hailing · Ad Attribution
Volume / `GET_PRESIGNED_URL` (image ingestion)	Defect AI Detection · Autonomous Driving
BloomFilter Index (high-cardinality column acceleration)	Predictive Maintenance · Smart Mining · IoT Device Health · Gaming Operations · Retail POS · Fraud Detection · Manufacturing SPC · SOC Logs
Inverted Index (full-text search)	Smart Mining · Ad Attribution · Content Recommendation · Online Education · Fraud Detection · SOC Logs
Vector Index + `AI_EMBEDDING` (semantic similarity / RAG)	Smart Mining · Content Recommendation
BITMAP (large-scale user set operations)	Gaming Operations · Marketing CDP · Online Education · Uplift Modeling · Product Analytics
Table Stream (change data capture)	Autonomous Driving · Ad Attribution · Copyright Settlement · Ride-Hailing · Product Analytics · Smart City
Time Travel (historical snapshot / reconciliation)	Retail POS · Insurance Compliance · Regulatory Reporting · Healthcare Operations · FHIR Clinical · Copyright Settlement · SOC Logs
Column Masking + RBAC (data masking / permission isolation)	IoT Device Health · SaaS Operations · Real-Time Risk Control · Healthcare Operations · FHIR Clinical · HR Data Warehouse · Insurance Compliance · Regulatory Reporting · Smart City
SQL UDF (reusable business logic encapsulation)	IoT Device Health · SaaS Operations · Real-Time Risk Control · Fraud Detection · Online Education · Manufacturing SPC · Retail Customer 360 · Ride-Hailing · SOC Logs
External Function (external service integration)	Marketing CDP · Content Recommendation · Weather × Retail · SKU Forecasting
External Schema / Iceberg REST (data lake federation)	Retail POS · Smart City · Iceberg Federation
Semantic View (natural language queries)	SaaS Operations · Retail Customer 360 · Data Mesh
ZettaPark Python Task (Python task orchestration)	Content Recommendation · Fraud Detection · SKU Forecasting · Uplift Modeling
Studio Task DAG (task dependency orchestration)	DataOps Quality Gates · Ride-Hailing
API Connection (AI model credential management)	Predictive Maintenance · Smart Mining · Complaint Labeling · Email Support

Select by Business Need

I want to use AI to analyze unstructured data

Images / Video: See Defect AI Detection to learn how to connect images to AI functions via Volume + GET_PRESIGNED_URL.

Text classification (single-label): See Intelligent Complaint Labeling for the simplest LLM classification pipeline — from source table to labeled results in just three Dynamic Table layers.

Multi-task text (classification + extraction + draft generation): See Email Customer Support Auto-Triage, which shows how a single AI_COMPLETE call with a structured JSON prompt completes five tasks at once, plus the REGEXP_EXTRACT + GET_JSON_OBJECT pattern for reliably parsing LLM output.

Text sentiment + structured summary extraction: See Product Review Sentiment Analysis, which shows the dual-function split between AI_SENTIMENT and AI_COMPLETE, and the tiered trigger cost-control pattern that skips AI for neutral reviews.

Extracting fields from unstructured notifications: See the supplier lead time parsing in Supply Chain Inventory Optimization — AI_EXTRACT converts email/notification text into structured fields that directly drive business logic.

Historical document knowledge base + RAG augmentation: See Smart Mining, which shows how to use AI_EMBEDDING + vector indexes to build a searchable knowledge base from historical incident reports and inject retrieval results into AI_COMPLETE prompts, without needing a separate vector database (Milvus/Pinecone).

I want to build a near-real-time data pipeline

All solutions use Dynamic Table for incremental refresh, with no external scheduler needed. Complexity from low to high:

Simplest (AI row-by-row inference): Complaint Labeling · Email Support — three Dynamic Table layers, AI classification completes within ≤10 min of new data arriving
Medium (aggregation + threshold filtering): Predictive Maintenance · User Behavior Funnel · IoT Device Health — aggregation first to reduce noise/count UV, then filter/MERGE into summary tables
Multi-level multi-frequency (industrial safety): Smart Mining — real-time link (1-min Studio Cron) + aggregation-layer DT (5 min) + cross-system correlation DT (5 min) + trend prediction DT (5 min), four refresh intervals complementing each other
Complex (stream ingestion + multi-layer AI): Product Review Sentiment Analysis · Real-Time Financial Risk Control — Kafka PIPE ingestion + multi-layer Dynamic Table + sliding window aggregation + AI or scoring functions

I want to do e-commerce operations analytics

Funnel conversion rates: User Behavior Funnel Analysis — multi-channel UV statistics, three-segment drop-off breakdown, MERGE INTO idempotent summary writes, latency ≤1 hour
Negative review alerting: Product Review Sentiment Analysis — real-time negative review tagging, SKU-level positive rate aggregation, driving quality control and proactive outreach
Customer service ticket efficiency: Intelligent Complaint Labeling + Email Customer Support Auto-Triage — ticket auto-classification routing, high-priority alerting, AI reply drafts in one system
Store POS operations analytics: Retail Chain Store Operations Data Warehouse — multi-shard aggregation, partition-based store rollup, Time Travel month-end reconciliation
Customer churn prediction: Retail Customer 360 Churn Prediction — online/offline data unification, RFM segmentation + churn scoring driving precision retention

I want to do marketing analytics and user growth

Multi-channel ID unification: Digital Marketing CDP — OneID system construction, MERGE INTO incremental merging, BITMAP billion-scale audience segmentation
Ad attribution analysis: Multi-Channel Ad Attribution — three attribution model comparison (Last Touch / Linear / Position-Based), Table Stream captures conversions
Causal inference and uplift modeling: Marketing Uplift Modeling — distinguishing organic purchases from intervention increments, precision budget allocation
Product A/B experiments: Product Analytics Data Warehouse — event stream multi-layer data warehouse, end-to-end funnel + A/B experiment conversion rate measurement

I want to replace static decision models in MES/ERP

See Supply Chain Inventory Optimization. The solution demonstrates how to implement dynamic replenishment calculations with Dynamic Table, use COALESCE to automatically switch between real-time supplier lead times and ERP static values, and MERGE INTO for idempotent archiving — all without modifying existing systems. For more complex replenishment scenarios, see SKU-Level Demand Forecasting, which uses ZettaPark to run thousands of Prophet models in parallel for precision forecasting.

I want to deploy AI in industrial scenarios

Quality inspection: Defect AI Detection — image + text dual-channel, AI_CLASSIFY for full-volume classification followed by tiered AI_COMPLETE, cost-controlled
Equipment O&M: Predictive Maintenance · Industrial IoT Device Health Monitoring — after sensor data lands in the lake, Dynamic Table automatically completes the three-stage pipeline of aggregation, threshold filtering, and scoring
Quality control: Manufacturing SPC Quality Control — real-time inspection data SPC control charts + Cpk process capability analysis, sliding windows auto-calculate control limits
Safety production: Smart Mining — cross-system JOIN correlation alerts across six subsystems, AI_CLASSIFY + AI_COMPLETE CTE chaining, RAG injecting historical incident experience

I want to manage sensitive data / meet compliance requirements

Financial regulation: Regulatory Reporting (BCBS 239 / IFRS 9) — Time Travel for reproducible snapshots at any point, Column Masking for multi-role permission isolation
Insurance compliance: Insurance Core Business Compliance Reporting — CBIRC reports, Oracle/PostgreSQL batch sync, Time Travel for historical reconciliation
Healthcare privacy: Healthcare Operations Data Warehouse · FHIR Clinical Data Analysis — Column Masking to desensitize PHI/PII fields, RBAC fine-grained access control
Cybersecurity forensics: SOC Log Analysis — Time Travel to trace state at any point, Inverted Index for rapid log keyword search
Government data isolation: Smart City Data Platform — multi-department RBAC isolation + Column Masking for citizen information masking

See Autonomous Driving Full-Loop. This solution covers unified management of structured time-series data, semi-structured JSON events, and large files (Parquet annotation packages), plus the complete closed-loop architecture from data collection to model iteration. It serves as a reference blueprint for other data-intensive industries (precision agriculture, medical imaging, satellite remote sensing).

I want to build an enterprise-grade data governance system

Data productization (Data Mesh): Enterprise Data Mesh Productization — each business domain manages its own Schema, Semantic View exposes the semantic layer, cross-domain federation queries
Data quality automation: DataOps Pipeline Quality Gates — assertion checks after each layer refresh, non-conforming data auto-quarantined, Studio Task DAG drives the entire quality chain
Multi-engine lakehouse integration: Multi-Engine Iceberg Data Lake Federation — Iceberg tables written by Spark/Flink queried via federation without copying, Dynamic Table incremental processing