Big Data for Smart City
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This document discusses how big data can be used for smart cities. It provides three use cases: 1) social media and sentiment analysis to analyze opinions on topics, 2) retail analytics and recommendation engines to predict customer product preferences, and 3) security and risk management using machine learning to detect fraud patterns. It also discusses optimizing data warehouses to improve data services while reducing costs. Big data systems like Hadoop and Spark are introduced for large-scale storage and processing.
Big Data for Smart City
- 1. Big Data for Smart City Furqonuddin Ramdhani www.icion-leadership.com
- 2. 22 Smart City Definition, objectives, Big Data Use Cases for Smart City Big Data Definition, Landscape, Ecosystem, Hadoop, Life Cycle Big Data Use Case RecommendationEngine, Risk Management, Data Warehouse Optimization Outline
- 3. 3 Smart City
- 4. Smart City 44 In Smart Cities, digital technologies translate into better public services for citizens, better use of resources and less impact on the environment.
- 5. 5 Big Data Use Cases for Smart City • Social Media Analysis / Sentiment Analysis, aims to analyze and study of people’s opinions, attitudes and emotions toward an entity in text of specific subjects. • Retail Analytics, recommendation engine to predict next best offers of products to customers.
- 6. 6 Introduction to Big Data
- 7. 7 What is Big Data ?
- 8. 8 Big data enabled by five ‘Digital Economy’ drivers
- 10. 10 Hadoop • “Scalable”, “Fault Tolerant” platform for large amount data storage & processing, distributed across machines. • Based on Google File System (GFS) & MapReduce
- 11. 11
- 13. 13 Hadoop
- 14. 1414 Big Data Life Cycle
- 15. 15 Copy Files in HDFS
- 17. 17 Stream data into Hadoop using Flume
- 19. 19 Process Data
- 20. 20 Data Processing • Transform the data • Enrich the data • Examples : • Store data in multiple formats • Aggregate data • Build recommendations • …
- 21. 21 MapReduce Processing Model • Define mappers • Shuffling is automatic • Define reducers
- 22. 22 Apache Spark : Fast Big Data • Fast to Run • General execution graphs • In-memory storage • Rich APIs in Java, Scala, Python
- 23. 23 Apache Drill
- 24. 24 Use Case 1 Financial Services : RecommendationEngine & Realtime Targeting
- 25. 25 Financial Services : RecommendationEngine & Realtime Targeting Making personalized real-time offers to credit card customers
- 26. 26 Making personalized real-time offers to credit card customers Financial Services : RecommendationEngine & Realtime Targeting
- 27. 27 Use Case 2 Security & Risk Management
- 28. 28 Security & Risk Management High Performance machine-learning to detect fraud patterns
- 29. 29 Security & Risk Management
- 30. 30 Use Case 3 Data Warehouse Optimization
- 31. 31 TDWI : Evolving Data Warehouse Architectures
- 32. 32 Data Warehouse Optimization Improve data services to customers while reducing enterprise architecture costs
- 34. Thank you Support our CISSP CLASS FROM 25 TO 29 APRIL 2016 Contact to shindy@advancedtechpac.com www.advancedtechpac.com • www.icion-leadership.com • LOOK FORWARD TO YOUR SUPPORT IN 2017 • CISSP COMMUNITY EVENT FEB IN PONDOK INDAH • https://www.youtube.com/watch?v=fqUjXIlCcfM