Real-Time Unified Data Layers: A New Era for Scalable Analytics, Search, and AI v 1.1Table of Contents Introduction 1. The Interconnection of Analytics, Search, and AI 2. What is a Real-Time Unified Data intelligence. For example: FMCG & Manufacturing need real-time production dashboards and historical analytics shared across plants & lines to improve Overall Equipment Effectiveness (OEE). Energy companies platforms require real-time monitoring and analytics to personalize experiences and ensure performance. 32. The Interconnection of Analytics, Search, and AI Analytics, search, and AI are deeply interconnected

гибкая система 8 Web analytics Mobile app analytics Ads analytics Realtime bidding E-commerce analytics Retail Games analytics Video streaming analytics Media & news analytics Social recommendations DDoS protection Application performance monitoring Logs & metrics Security events and logs. SIEM Analytics of corporate networks Telemetry Industrial monitoring Sensor data IoT Self-driving cars Agriculture Scientific datasets Genomics Particle physics Astronomy & astrophysics Econometrics ML feature analytics and research Trading & financial data Fintech Insurance Investment banking Blockchain Gambling

гибкая система 8 Web analytics Mobile app analytics Ads analytics Realtime bidding E-commerce analytics Retail Games analytics Video streaming analytics Media & news analytics Social recommendations DDoS protection Application performance monitoring Logs & metrics Security events and logs. SIEM Analytics of corporate networks Telemetry Industrial monitoring Sensor data IoT Self-driving cars Agriculture Scientific datasets Genomics Particle physics Astronomy & astrophysics Econometrics ML feature analytics and research Trading & financial data Fintech Insurance Investment banking Blockchain Gambling

gn-primer 8 / 97 ClickHouse in Production: Yandex.Metrika › Third web analytics service in the world › Most popular analytics service in Russia › 800’000 RPS › ≈80 billion events per day › 98% processed Zone Analytics Load Balancer API User User CDN Data Centers Kafka Cluster Browser 19 / 97 ClickHouse in Production: Cloudflare HTTP Requests Data Kafka Consumers Zone Analytics Load Consumers Zone Analytics Load Balancer API User User Data Centers Kafka Cluster Browser 21 / 97 ClickHouse in Production: Cloudflare HTTP Requests Data Kafka Consumers Zone Analytics Load Balancer

solutions that bring the best of our clients. Be it data mining, data gathering, databases, or data analytics, our services aim to enhance, transform, and revolutionize our clients operations through the client’s need these could eliminate the need for expensive ETL tools. As well as its real-time data analytics system do give it a notable advantage over competitors in the same product category. (Large Databases databases that require processing securely at very high speeds queries. MySQL Compatible Real-Time Analytics High Level of Guarantees on data reads and writes An ecosystem of tools Support Those with Large

high volumes of data to and from a variety and sources and targets for real-time reporting and analytics using Log based CDC and Data Replication. What is HVR? 4 Key Benefits of Using HVR for your your Business 提升业务洞察力 关键业务连续性 提高效率 降低风险 5 Geographical Distribution Real-Time Analytics Data Lake Data Warehouse Cloud HVR 连续数据集成技术 Migrations Disaster Recovery 6 扩展性—高性能架构 7 • 创建并装载目标表 greenplum or RDS Kafka or Kinesis streamed analytics users HVR Simultaneous ingestion into streaming, relational and storage ETL users streamed analytics EMR ODS Kafka S3 users users HVR Strengths

Embedded Analytics Augmented Analytics Data Workspace ML Tooling Custom Applications Micro Services/Service Mesh ERP/SCM CRM Applications Operational Databases A16Z Analytics Serving OLAP Processing OLTP NoSQL/Multi Model Lindorm HTAP PolarDB PolarDB TSDB Search Elasticsearch Analytics Infinity https://github.com/infiniflow/infinity 感谢交流

Integrated Analytics 392 Overview of Greenplum Database Integrated Analytics 0 The Greenplum Database Integrated Analytics Ecosystem 392 Machine Learning and Deep Learning 392 Geospatial Analytics 393 Text Text Analytics 393 Programming Language Extensions 393 Why Greenplum Database in Integrated Analytics 393 Machine Learning and Deep Learning using MADlib 394 Machine Learning and Deep Learning using Rules 400 Naive Bayes Classification 402 References 406 Graph Analytics 406 Graph Analytics 0 What is a Graph? 406 Graph Analytics on Greenplum 407 Using Graph 407 Graph Modules 409 All Pairs Shortest

Integrated Analytics 383 Overview of Greenplum Database Integrated Analytics 0 The Greenplum Database Integrated Analytics Ecosystem 383 Machine Learning and Deep Learning 383 Geospatial Analytics 384 Text Text Analytics 384 Programming Language Extensions 384 Why Greenplum Database in Integrated Analytics 384 Machine Learning and Deep Learning using MADlib 385 Machine Learning and Deep Learning using Rules 391 Naive Bayes Classification 393 References 397 Graph Analytics 397 Graph Analytics 0 What is a Graph? 397 Graph Analytics on Greenplum 398 Using Graph 398 Graph Modules 400 All Pairs Shortest

Integrated Analytics 318 Overview of Greenplum Database Integrated Analytics 0 The Greenplum Database Integrated Analytics Ecosystem 318 Machine Learning and Deep Learning 318 Geospatial Analytics 319 Text Text Analytics 319 Programming Language Extensions 319 Why Greenplum Database in Integrated Analytics 319 VMware Greenplum v6.17 Documentation VMware, Inc. 14 Machine Learning and Deep Learning using Rules 326 Naive Bayes Classification 328 References 332 Graph Analytics 332 Graph Analytics 0 What is a Graph? 332 Graph Analytics on Greenplum 333 Using Graph 333 Graph Modules 335 All Pairs Shortest