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Oracle Stream Analytics - Industry Examples
- 1. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 1
Turn Data into Action in Real-time !
Oracle Stream nalytics
- 2. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Oracle Stream Analytics
Golden Gate CDC or
Txn Logs
Sensor Data
Social Media
Click Stream
Geo Location
Filter
Aggregate
Transform
Correlate/Enrich
Geo-fence
Time Windows
Data Patterns
Spatial Analytics
Anomalies
Classification
Clustering
Statistical Inference
Regression Models
Business Rules
Policies
Conditional Logic
Notify/Publish
Invoke/Execute
Visualize
Persist
Data Ingestion Pre-processing Analysis &
Prediction Decisions Actions
Data Processing Stages in an OSA Pipeline
- 3. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Oracle Stream Analytics - Functional Components
OSA
Positioned as a Leader by Forrester and Bloor
Runs 100% on Spark
Complex Event
Processing
Operational
Intelligence
Real-time OLAP for
Event & Time-series
Data
Prediction &
Forecasting
- 4. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
The New OSA Stack
Oracle Confidential 4
Stream Explorer Web UI
Spark SQL MLLIB GraphX
RETE Rule
Processor
Continuous
Query
Processor
Spatial
Cartridge
Spark Streaming
Spark Core
Oracle Stream Analytics Engine
- 5. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Kafka Kafka
Data Ingestion & Target Systems
Oracle Stream Analytics
Downstream Apps
ICS Flows
BPM Processes
Databases
REST
- 6. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Kafka Kafka
Real-time Analytics on Transaction Data using Golden Gate
Oracle Stream Analytics
Downstream Apps
ICS Flows
BPM Processes
Databases
REST
Transaction
Logs
Insert/Update/Delete
Inflight analytics using transaction
context
- 7. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Why Oracle Stream Analytics ?
1. Build Complex Event Processing applications
– Filters and aggregates on streaming data
– Sliding Windows (Time Windows, Row Windows, Value Windows)
– Shifting Windows (This Day, This Hour, This Minute, etc…)
– Pattern Matching and Recognition
– Geo-spatial Analytics
– Business Rules
– ML, Event Scoring, and Prediction
2. Visualize streams and build operational dashboards
3. Run ad hoc queries on CEP results (real-time and historical)
– Sub second response to all ad hoc queries
4. Predict or forecast future values based on historical data and PMML models
- 8. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Oracle Stream Analytics Industry Examples
- 9. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Retail
Some examples from Gartner Research
1. Supplier Analysis
– Compute transaction losses, margins, etc. in real-time to renegotiate with suppliers
2. Markdown optimization
– Continuously track demand/inventory-levels and gradually lower prices for better margins instead or
randomly marking down at end of season
3. Dynamic pricing and forecasting
– Readjust prices based on demand, inventory levels, sentiments and user feedback in social media
4. Personalized offers
– Make real-time offers based on customer presence, store vicinity, customer profile, and spend patterns
5. Real-time shelf-space management in stores
– Based on customer traffic and point-of-sale data
6. Purchase and consumption trends from social media
– Empower marketing and sales by identifying top selling products and services in real-time
- 10. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Retail…contd
Some examples from Gartner Research
1. Shopping cart defections
– Identify lull in shopping cart activity and improve conversion rates
2. Recommendations using fuzzy match
– Based on what other customers are browsing/purchasing in similar categories and at the same time
3. Improved mall experience
– Upsell/cross-sell based on customer profile and current location in the mall
– Make special offers for checking in at more than 10 stores or making purchases worth 100$ or more
4. Monetize retail data
– Stream quantity sold, buying patterns, etc. to partners and suppliers in real-time
5. Fraud detection and prevention
– Prevent fraudulent return of merchandize
- 11. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Financial and Banking Services
1. Fraud detection
– Flag and block transactions from stolen and misused credit cards
2. Money laundering
– Many small transactions from same source but to different destination accounts in a small window
3. Upsell products and services
– Based on customer’s financial profile, seize the tiny window of opportunity when customer is online
4. Real-time risk management
– Evaluate portfolio risk from real-time equity and commodity prices
5. Tick analytics & social media feeds
– Blend tick data with social media to identify securities/commodities likely to be affected in next few
minutes or hours
6. ATM Service Optimization
– Identify optimal period and amount to be stocked based on bill-sizes and withdrawal patterns
– Obtain real-time alerts on malfunction for preventive maintenance Some examples from Gartner Research
- 12. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Transportation & Logistics
1. Asset utilization and tracking
– Average time spent on dock loading/unloading merchandise
2. Asset handling and staff monitoring
– Number of driving violations with trailer on road
3. Asset maintenance
– Check deviation of operating parameters and proactively schedule maintenance
4. Turnaround planning
– Prepare dock, staff, etc. and optimize workflows based on estimated time of arrival
5. Real-time route optimization
– Calculate optimal delivery sequence based on items being shipped, traffic, weather, customer
profile, etc..
Some examples from Gartner Research
- 13. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Telecommunications
1. Wifi offloading
– Free cellular bandwidth by automatically switching users with data plan to hotspots
2. Lower support costs
– Monitor network outages and proactively inform affected customers via automated text and VMs
3. Reduce customer churn and improve loyalty
– Address dropped calls and proactively inform customers of data usage when roaming before they
further breach the thresholds
4. Fraud detection on prepaid cards
– Detect and block stolen/misused cards
5. Distributed denial of service attacks
– Prevent attacks on network by continuously monitoring source and destination IP addresses
6. Improve end-user application security
– Prevent session hijacking by monitoring IP and associated cookies
Some examples from Gartner Research
- 14. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Utilities
1. Optimize energy distribution with demand pricing
– Move homes to different price slabs based on their current energy consumption
• E.g. Current energy consumption of home X is 30% higher than the global median so move to different slab
2. Energy theft
– Continuously monitor unusual usage patterns and variations in meter signatures
3. Peak-demand analytics
– Anticipate and plan for real-time energy demand by monitoring weather and neighborhood events
(e.g. Superbowl), etc.
4. Monetize energy consumption data
– Sell energy consumption data to producers, distributors, and appliance manufacturers in real-time
Some examples from Gartner Research
- 15. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Public Sector
1. Education
– student performance improvement
• Correlate student performance with learning data (use of library, lab, classroom, etc.) for better scores in weak areas
2. Public Safety
– Listen to social media chatter and identify areas likely to be affected by crime or terrorism
3. Traffic and infrastructure optimization
– Analyze real-time traffic flow and infrastructure usage
4. Law enforcement efficiency
– Use real-time traffic for better dispatch policies
Some examples from Gartner Research
- 16. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Insurance
1. Usage-based premiums
– Price premium on driver behavior and data from telematics
2. Damage prevention alerts
– Proactively alert subscribers in vulnerable areas on inclement weather
– Proactively alert subscribers to avoid areas of social unrest, epidemics, etc. using social media feeds
3. Reduce customer churn
– Track behaviors that reveal an impending cancelation
4. Fraud detection
– Detect parameter fiddling to reduce premium
• E.g. Continuous changes to work distance parameter when seeking quotes
Some examples from Gartner Research
- 17. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Manufacturing
1. Reduce costs using real-time parts flow monitoring
– Plan and schedule production resources based on current location of parts
2. Preventive maintenance of manufacturing equipment
– Continuously monitor operating parameters for deviation and likely breakdown
3. Preventive maintenance of manufactured products
– Continuously monitor usage and proactively inform consumers of upcoming maintenance or
expected malfunction
4. Improve staff safety using data from sensors
– Crucial in hazardous environments, poor air quality, employee fatigue, etc.
Some examples from Gartner Research
- 18. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Life Sciences and Health Care
1. Supplies, facilities, equipment, and staff
– Continuously monitor life-saving equipment and prevent breakdowns
– Continuously monitor life saving supplies and eliminate costs of overstock and understock
– Continuously monitor drugs for expiration dates
2. Adaptive treatment
– Continuously monitor the effects of medication through sensors and adapt dosage
3. Healthcare fraud detection
– Large invoices with no matching purchase orders or vendors
– Identify excessive billing by a single physician
– Alert on illegal staff overtime charges
Some examples from Gartner Research
- 19. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Media and Entertainment
1. Right content at right location and right time
– Change ad on bus based on its location, time-of-day, and other contextual data
2. Personalized offers for online gaming
– Track customers on losing streak and offer coupons from local stores
3. Targeted ads based on viewing preferences and location
– Target ads based on user location and content being viewed
• E.g. Place local restaurant ads when customer is viewing Food Network
• E.g. Place ads from local nursery when customer is viewing Home and Garden
4. Monetization of content analytics
– Collect and stream viewing stats by category to content providers in real time
Some examples from Gartner Research
Editor's Notes
- New age banking
Single instant insight view of a customer
Mobility marketing using new Banking Apps
Next generation international fraud
DDOS