Which data should you move to Hadoop?
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This document discusses trends driving enterprises to move cold data to Hadoop and optimize their data warehouses. It outlines two trends: 1) collecting more customer data enables competitive advantages, and 2) big data is overwhelming traditional systems. It also discusses two realities: 1) Hadoop can relieve pressure on enterprise systems by handling data staging, archiving, and analytics, and 2) architecture matters for production success with requirements like performance, security, and integration. The document promotes MapR and Attunity solutions for data warehouse optimization on Hadoop through real-time data movement, workload analysis, and incremental implementation.
Which data should you move to Hadoop?
- 1. 1 Moving Cold Data to Hadoop
- 2. 2 2 Trends Forcing a revolution in enterprise architecture
- 3. 3 Industry Leaders Compete and Win with Data1TREND More Data Beats Better Algorithms Collecting interaction data from ecommerce, social media, offline, and call centers enables a “customer 360 view” and consumer intimacy Competitive Advantage is Decided by 0.5% Consumer financial services: 1% improvement in fraud detection means hundreds of millions of dollars Advertising and retail: 0.5% improvement in lift means millions of dollars increase in profitability
- 4. 4 Big Data is Overwhelming Traditional Systems • Mission-critical reliability • Transaction guarantees • Deep security • Real-time performance • Backup and recovery • Interactive SQL • Rich analytics • Workload management • Data governance • Backup and recovery Enterprise Data Architecture 2TREND ENTERPRISE USERS OPERATIONAL SYSTEMS ANALYTICAL SYSTEMS PRODUCTION REQUIREMENTS PRODUCTION REQUIREMENTS OUTSIDE SOURCES
- 6. 6 OPERATIONAL SYSTEMS ANALYTICAL SYSTEMS ENTERPRISE USERS 1REALITY • Data staging • Archive • Data transformation • Data exploration • Streaming, interactions Hadoop Relieves the Pressure from Enterprise Systems 2 Interoperability 1 Reliability and DR 4 Supports operations and analytics 3 High performance Keys for Production Success
- 7. 7 FOUNDATION Architecture Matters for Success2REALITY Data protection & security High performance Multi-tenancy Real-time operational & analytical apps Open standards for integration NEW APPLICATIONS SLAs TRUSTEDINFORMATION LOWERTCO
- 9. 9 TDWI: Evolving Data Warehouse Architectures 2 1 Data Staging & Archive 3 Big Data Analytics 2 ETL Hadoop Uses in Data Warehouse Environment Source: TDWI April 2014
- 10. 10 The MapR Advantage • Scale Reliability Across the Enterprise – Advanced multi-tenancy – Business continuity – HA, DR • Speed – 2-7x faster than other Hadoop distro’s – Ultra-fast data ingest (100M data points per sec) – NFS & R/W file system • Real-time & Self-Service Data Exploration – On-the-fly SQL without up-front schema – Fast lookups and queries Best Hadoop Platform for Data Warehouse Optimization & Analytics Security Streaming NoSQL & Search Provisioning & coordination ML, Graph W orkflow & Data Governance Batch SQL INTEGRATED COMMERCIAL ENGINES TOOLSCOMPUTE ENGINES Batch Interactive Real-time Online Others Management Operations Governance Audits Security MapR-FS MapR-DB MapR Data Platform
- 11. 11 Attunity Solutions Right Data. Right Place. Right Time.
- 12. 12 Attunity – Growing, Modular Portfolio Delivering Big Data for Analytics
- 13. 13 Data Warehouse Optimization with Hadoop 1 2 3 Assess and identify data and workloads to rebalance on Hadoop Develop a roadmap to move data and workloads Implement the roadmap incrementally and iteratively
- 14. 14 Completely analyze workloads and data usage Reduce costs | Optimize performance | Justify investments The Data Dashboard User Activity Data Usage Workload Performance Attunity Visibility – The Data Dashboard
- 15. 15 Attunity Replicate • Real-time data movement • Change Data Capture (CDC) • Broadest platform support • Files - MF - RDBMS - Hadoop • Non-intrusive architecture • Automation of standard maintenance tasks • “Click-to-Load” design
- 17. 17 MapR and Attunity Are a Great Partnership • Complimentary set of enterprise-grade features – Focus on Data • Movement • Identification • Usage • High availability • Scale • Data Warehouse Optimization – Experience across broad set of use cases/workloads • Customer 360 view • Telco • Internet of Things (IoT)
- 18. 18 Additional Resources • Go to: www.Attunity.com/mapr • Find us on Twitter: – @mapR – @attunity • Watch our video • View the Moving Cold Data to Hadoop webinar