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Big Data and Advanced Spatial Analytics Eve Kleiman Director, APAC Technology Product Releases & Management Programs Oracle
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Disappearing line between Geospatial Technologies and Information Technologies
Mapping Digital data file Spatial Information
Technology
SOA
Geographic Information Systems
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Java, Databases, BI, Applications, Cloud
Location Infused Technology
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Internet of Things
The New Infrastructure
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Internet of Things| Open a World of Possibilities Total economic value add estimated at
$1.9 Trillion, Source:Gartner
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Need for an Enterprise Platform
Standardization
Streamline how IoT applications are developed,
secured & deployed
1
Real-Time Analytics
Manage IoT data from collection,
storage, processing and
analysis
2
Integration
Connect intelligent devices
to existing enterprise
applications
3 Security
Manage security and identity of data, devices,
enterprise applications
4
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Definition: What is Big Data Anyway? The 4 ‘V’s of Big Data
Volume – It’s about 100s Terabytes and Petabytes... BUT could be smaller volumes – size is in the eye of beholder
Value – At volume low value data can highlight high value patterns, trends and insights of significant commercial value
Variety – Highlights the new types of data from the ‘internet of things’ that can be stored and analysed
Velocity – Relates to streams of high frequency data arriving e.g. From a sensor, network, Imagery, UAV, or high volume event
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• Mobile Sensing & Geocoding – Mobile tracking – Automated Data Capture / Geocoding – Filtering / Geocoding
• 3D data into mainstream – Apple, Google, Microsoft – 3D city models, terrains, imagery
• Enhancing Web and Enterprise apps – Business intelligence & operations
Spatial Data From Scarcity to Abundance
8
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Conquering Big Data
If you could have all the data you wanted, what would you do differently?
The Business Opportunity 100 million daily 1 billion visitors / yr Web Transactions eCommerce
1 million daily Image uploads Claims analysis Insurance
10 billion daily Device syncs Consumer
10 million meters Hourly uploads Utility
20 million daily Monitoring Healthcare
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MEDIA/ ENTERTAINMENT Viewers / advertising effectiveness Cross Sell
COMMUNICATIONS Location-based advertising
EDUCATION & RESEARCH Experiment sensor analysis
Retail / CPG Sentiment analysis Hot products Optimized Marketing
HEALTH CARE Patient sensors, monitoring, EHRs Quality of care
LIFE SCIENCES Clinical trials Genomics
HIGH TECHNOLOGY / INDUSTRIAL MFG. Mfg quality Warranty analysis
OIL & GAS Drilling exploration sensor analysis
FINANCIAL SERVICES Risk & portfolio analysis New products
AUTOMOTIVE Auto sensors reporting location, problems
Games Adjust to player behavior In-Game Ads
LAW ENFORCEMENT & DEFENSE Threat analysis - social media monitoring, photo analysis
TRAVEL & TRANSPORTATION Sensor analysis for optimal traffic flows Customer sentiment
UTILITIES Smart Meter analysis for network capacity,
Sample of Big Data Use Cases Today
ON-LINE SERVICES / SOCIAL MEDIA People & career matching Web-site optimization
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What Does a Big Data World Look Like? Truck / Motor Manufacturer
What they collect •Monitors the complete car •Kilometers Per Litre, Driving techniques •Location information
How they use it •Better tailored servicing plans •Better targeted marketing •Offer better finance deals or related options •More data for R&D •Sell on to partners
Big Data means… •The ability to predict when components might fail •Create better service plans based on actual usage •Drivers can post their data to manufacturers website •Black box data can help with accidents
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• Verizon Telematics provides a full service end-to-end solution
• Supports over 50 Telematics features (vehicle, driver, social, etc.)
• Verizon Telematics provides a modular platform
• Verizon Telematics supports a curated ecosystem
Examples
• The global first implementation of a city wide “smart” parking management system and technology to manage parking supply and demand more intelligently.
• Sensors at 8,200 of the city’s 27,000 metered parking spaces, to get information from the gate arms at the city’s 14 garages, which among them have about 13,000 spaces
Smart City: Parking Management
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• Provide a composite identity for customers and cars
• Need for a reliable 24/7 IAM infrastructure
• Leverage Mobility/Web technologies to provide advanced Infotainment and Safety Services
Telematics
Examples (cont.) Subsidiary of GM that provides
subscription-based communications, in-vehicle security, hands free calling, turn-by-turn navigation, and remote diagnostics systems
OnStar relies on Oracle to deliver service to 5.5 million car owners
• Location Intelligence Company • GIS, Mobile, LBS products • Spatial Content & Platform Provider • InfoMobil vehicle tracking and
dispatching system • 800 Customers, 2 Operation Centers,
50,000+ Mobile Devices, 2000+ Users
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What Does a Big Data World Look Like? Retailer / White Goods
What they collect •Food monitoring by RFID tags –Fridge monitors food usage and sell-by dates •Video Surveillance •Feedback / comments
How they use it •Automated food ordering •Better targeted marketing due to better data about how/when customer uses products
•More detailed information about customers •Better store based demand planning
Big Data means…
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New ways sit along side existing ways to generate data Oil & Gas Industry
Business Users Data Warehouse
Data Marts
Enterprise Data Warehouse
Source Systems
EXTRACTS
REAL-TIME DATA EXTRACTS
PROCESS MANUFACTURING
PROJECTS CONTRACTS
ENTERPRISE PROJECT PORTFOLIO MANAGEMENT TELESERVICE
ENTERPRISE ASSET MANAGEMENT
FIINANCIALS
FEEDS
3C/4C Seismic Sensors
Micro-seismic monitoring
Time-lapse Seismic data
Monitoring Infrastructure
Borehole Data Acquisition
Environmental Monitoring
Asset Management
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Telco Industry Big Data Use Cases
Location based marketing Real-time analytics combined with complex event processing to create analysis across the GPS data that a service provider can collect to understand the customers current location or look for patterns or relationships.
Network optimization Big Data is used to deliver real-time analytics to detect when a network is down, overloaded or reaching capacity.
Sentiment analysis Use of social media (Twitter, Facebook, etc.) - this is not just comms specific but a good example applicable across industry. Collect/stream data from social media sites into CRM and customer service applications to determine importance/”clout” of customer and to get a better overall picture of each customer’s behavior, likes and dislikes.
Weblog or clickstream analysis Applicable across industries; allowing service providers to better understand how their web site or online store is navigated.
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Incoming Data
• Track outcomes • Track treatments, notes • Track social media, payments • Correlate Omics w/EMR data • Correlate biometrics data across
devices
• Model protocols • Model outcomes • Model normal behavior
• Visualize data • Discover unknowns • Highlight outliers • Determine risk • Populate metrics • Report
• Prevent • Predict • Diagnose • Treat • Measure
Pharmaceutical
Activity / Claims Cost
Clinical
Lifestyle/History
Metabolic
Biometrics
Healthcare Industry Complete secure solution from data collection to analysis to decision
EMR
Social
Stream Acquire Organize /Discover
Analyze, Visualize Decide
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• Fuelband monitors active lifestyle of 8 million users on a daily basis
• Current data grid volume is approximately 150,000 request per minute with about 40 million objects at any given time on the grid
Healthcare
Nike
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FSI - Bank Real-time Location Based Offers
Objectives
Customer profile enrichment with Big Data Capture credit card POS and merchant data with
event processor Determine geo location of POS and nearby bank
wholesale customers Leverage real-time decision engine to generate
offer to mobile device
Solution
Increase revenue through real-time, location based offers
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The Challenge
• “Finding Useful Data” – Modeling, Statistics
– Econometrics
– Decision Science
– Psychology
Recognizing a Pattern – Predicting Behavior
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Make Better Decisions Using Big Data
Big Data in Action
ANALYZE
DECIDE ACQUIRE
ORGANIZE
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Acquire all available data
Big Data In Action
ANALYZE
DECIDE
ORGANIZE
ACQUIRE
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Hadoop Architecture
Management/Monitoring
Hadoop Distributed File System (HDFS)
MapReduce
Distributed file system Map/Reduce programming paradigm Highly scalable data processing
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NoSQL Databases
• A Distributed Key-Value Database
Nodes East
Nodes West
Nodes Central
NoSQL Driver
Application
NoSQL Driver
Application R
ead
Del
ete
Rea
d
Upd
ate
Simple data model
Scalability
High Availability
Transparent Load Balancing
Simple Administration
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SMS Message
Immediate Automatic Responses
Real-Time Streaming Data
Workflow Initiation
Real-time Dashboards
Console Alerts
Aggregate, Correlate, Filter
Virtual Data Repository
Pattern Detection
Event capture
Enrichment
Real-time Data Streams
Complex Event Processing
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Choose the RIGHT tool for the job Hadoop Distributed File System
(HDFS) NoSQL Databases Relational Databases
File System Key Value Store Relational Database
No inherent structure Simple data structure Complex data structures, rich SQL
High volume writes High volume random reads and writes High volume OLTP with 2-PC
Limited functionality, roll-your-own applications
Simple get/put high speed storage, flex configuration
Security, Backup/Restore, Data life cycle mgmt, XML, etc.
Batch Oriented Real-Time, web-scale specialized applications
General purpose SQL platform, multiple applications, ODBC, JDBC
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Organize and distill big data using massive parallelism
Big Data in Action
ANALYZE
DECIDE ACQUIRE
ORGANIZE
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Big Data Challenge – Aligning Data Types
• Semantic Graphs
Big Data: Decisions based on all your data
Machine-Generated Data Social Data
Documents
Video
Geospatial – Where is it Happening? In What Context?
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RDF for Enterprise Integration
Index
Content Mgmt BI Server Data Warehouse
Machine Generated Data
RDF metadata layer (integrated graph metadata)
Transaction Systems
Big Data Appliance
Subscription Services Human Sourced
Information Social Media
Event Server
Data Servers
Data Sources / Types
Access & Presentation Layer
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Graph Analysis
Recommendation
Purchase Record
customer items
• Create recommendations for a specific customer from its neighbors in a purchase graph
• Identify nodes that are critical to connectivity of an information flow graph
Influencer Identification
Communication Stream (e.g. tweets)
Pattern Matching
• Find sub-graphs that match a specified pattern
P1 P2 “ex”
P3 P4 friend friend friend
• Represent your data as a graph, analyze it and discover useful information • By considering relationships between data entities
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Analyze all your data, at once
Big Data in Action
ANALYZE
DECIDE ACQUIRE
ORGANIZE ANALYZE
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Navigation and Visualization of RDF graphs
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Web Mapping with GeoSPARQL
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Big Data Tools for Exploring & Analyzing
R Statistical Programming Language Open source language and environment Used for statistical computing and graphics Strength in easily producing publication-quality plots Highly extensible with open source community R packages
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Big Data Tools for Exploring & Analyzing Data Mining Tools for Guided Pattern Discovery & Statistical Analysis Problem
Classification Sample Problem
Classification Given demographic data about a set of customers, predict customer response to an affinity card program
Regression Given demographic and purchasing data about a set of customers, predict customers' age
Attribute Importance Given customer response to an affinity card program, find the most significant predictors
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Big Data Tools for Exploring & Analyzing
Automated Discovery & Predictive Analysis Problem Classification Sample Problem
Anomaly Detection
Given demographic data about a set of customers, identify customer purchasing behavior that is significantly different from the norm
Association Rules
Find the items that tend to be purchased together and specify their relationship – market basket analysis
Clustering Segment demographic data into clusters and rank the probability that an individual will belong to a given cluster
Feature Extraction
Given demographic data about a set of customers, group the attributes into general characteristics of the customers
F1 F2 F3 F4
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Text Analytics
2 miles
Spatial Analytics
Query and Reporting Data Mining
Statistics
Graph Analytics
Big Data Extends the Depth of Analytics
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Decide based on real-time big data
Big Data in Action
ANALYZE
ACQUIRE
ORGANIZE
DECIDE
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Summary
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Q&A MORE INFORMATION
HTTP://WWW.ORACLE.COM/US/TECHNOLOGIES/BIG-DATA/INDEX.HTML
HTTP://WWW.ORACLE.COM/TECHNETWORK/TOPICS/BIGDATA/WHATSNEW/INDEX.HTML [email protected]