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Big Data Overview
- 2. Agenda
• Introduction
• Types of Big Data
• Data Realm for Information Architecture
• Big Data Characteristics
• Importance of Big Data
• Big Data Platform
• Big Data Best Practices
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- 3. Big Data Introduction
• Collection of large and complex data sets
• Integration of structured, semi-structured &
unstructured data
• Difficult to process using on-hand DBMS tools
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- 4. Types of Big Data
• Traditional enterprise data (CRM, ERP,
Transactional data)
• Machine-generated /sensor data (meters,
sensors, recorders)
• Social data (Facebook, Twitter)
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- 5. Data Realm for Information
Architecture
• Master Data (Customer, product, supplier)
• Transaction Data (Purchase records, inquiries,
payments)
• Refrence Data (Geo, market data)
• Metadata (data definitions)
• Analytical Data (dimensions & facts)
• Document & Content (forms, files, images)
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- 6. Characteristics of Big Data
• Volume (very high volumes)
• Velocity (very high frequency)
• Variety (non-traditional data formats)
• Value (different economic value)
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- 7. Importance of Big Data
• Thorough/insightful understanding of
business
• Enhanced productivity
• Stronger competitive position
• Greater innovation
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- 8. Big Data Platform
• Acquire (DBMS, Files, NoSQL, HDFS)
• Organize (ETL/ELT/MapReduce)
• Analyze (ODS/DWH/OLAP)
• Decide (Reports/BI/Analytics)
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- 9. Solution by Oracle
• Oracle Big Data Appliance (Stream & Acquire)
• Oracle Big Data Connectors (Organize)
• Oracle Exadata (Analyze)
• Oracle Exalytics (Visualize)
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- 10. Big Data Best Practices
• Align Big Data with Specific Business Goals
• Ease Skills Shortage with Standards and Governance
• Optimize Knowledge Transfer with a Center of
Excellence
• Top Payoff is Aligning Unstructured with Structured
Data
• Plan Your Sandbox For Performance
• Align with the Cloud Operating Model
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