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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
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