Genera&ng Value from Big Data in the Internet of Things

Transcription

1

2 Genera&ng Value from Big Data in the Internet of Things THT10421 Cheng Kian Khor Global Industry Solu&on Leader - IoT/M2M for CSPs Communica&ons & Media Industry Solu&ons Group September 30, 2014

3 Safe Harbor Statement The following is intended to outline our general product direc&on. It is intended for informa&on purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or func&onality, and should not be relied upon in making purchasing decisions. The development, release, and &ming of any features or func&onality described for Oracle s products remains at the sole discre&on of Oracle.

4 The Internet of Things

5 Moving from M2M to the Internet of Things Transform Industries Innovative Services Differentiated Value Large scale ver&cal applica&ons Reduced Time and Cost to Market with Common PlaWorm Rich Process Interac&on, Informa&on Aggrega&on Deep, transforma&ve industry func&onality and ecosystem IoT Ecosystem Enablers Process Enablers & Information Mashup Enablers Focus on Connectivity Device Cloud & Horizontal Enablers

6 IoT Analy&cs Genera&ng Value from Big Data UTILITIES Reduced break- fix &me from 90 to 30 days 75% fewer truck rolls to fix the same number of broken meters USD 6M Recovered in losses in one year Proac&ve iden&fica&on of problema&c meters 50% Reduc&on in field crew cost HEALTHCARE Reduced healthcare / insurance costs Improved adherence/compliance to treatment and monitoring e.g. CPAP for OSA Analy&cs for pa&ents/healthcare providers / popula&on healthcare managers AUTOMOTIVE Predict wear and tear replacement intervals Remote, pro- ac&ve and guided diagnos&cs Traffic / Driving Behaviour analy&cs Usage Based Insurance (UBI) MANUFACTURING Remote asset fix rate greater than 50% Reduced field service dispatch Reduced down- &me through pro- ac&ve detec&on of equipment failures, saving hundreds of thousands

7 Oracle Approach - Conceptual View Internet of Things (IoT) Ac&onable Events Ac&onable Data Sets Ac&onable Informa&on Input Events Streaming Engine Data Reservoir Enterprise Data & Repor&ng Structured Enterprise Data Execu&on Innova&on Data Discovery Lab Discovery Output

8 Real- Time Analy&cs - Event Processing with Spa&al / Loca&on / Geofencing

9 Copyright 2014, Oracle and/or its affiliates. All rights reserved.

10 Moving Analytics Closer to the Edge

11 Analyze, Visualize and Mone&ze Automo&ve Big Data Example Automo&ve Dataset from Telema&cs Data: Number of trips recorded Number of kilometers logged Travel by Loca&on Petrol consump&on by model Diagnos&c Trouble Codes by model Driver Aggression Profile (e.g. RPM Profile) Distance by model / holiday travel Traffic Palern Visualiza&on Warranty Claim Visualiza&on Copyright 2014, Oracle and/or its affiliates. All rights reserved. Oracle Confiden&al Internal/Restricted/Highly Restricted 11

12 Smart Metering Analy&cs - Collect, Analyze and Act to Increase Efficiency / Reduce Cost Monthly register reads don t easily reveal slowing consump&on Daily data reveals there is a trend, but is it unusual, or weather driven? (Yellow = temperature) Comparison to rate class behaviour (Red rate class aggregate) reveals that the palern is specific to the meter Inclusion of meter flag / event data seals the deal: meter is highly likely to be failing 12

13 style program. Bring on an experienced team to build the technical infrastructure and integrate it with existing systems. Make sure your technology implementation team is involved in the first stages of the project management life cycle, beginning with contracting and procurement, long before it comes time to purchase servers. Have that team work with your existing IT team to ensure that technology choices fit in with your implementation plan. Expect to spend more time in requirements discovery, business process reengineering, and off-plan work than expected. None of the vendors has ever done this type of project before, so workarounds and detours are commonplace. The technological maturity of vendor products is much less than was anticipated. Most vendors do not have mature software organization s existing IT standards and direction. development, testing, and change control procedures. Smart City - Parking Data: Collect, Analyze, Act and Expose as a Mobile applications Service Business intelligence tool automated report example 94 / Ch. 5: Parking technology Screen shots of iphone app SFpark provides on- and off-street parking availability and rate information via an iphone app and soon an Android app. SFpark: Putting Theory Into Practice / 93

14 Oracle Big Data Management Architecture ORACLE BIG DATA SQL DATA RESERVOIR DATA WAREHOUSE Cloudera Hadoop Oracle NoSQL Oracle R Advanced Analy@cs for Hadoop Oracle R Distribu@on Oracle Big Data Connectors Oracle Data Integrator Oracle Oracle Database Database In- Memory, Oracle Industry Mul@- tenant Models Oracle Industry Models Oracle Advanced Oracle Analy@cs Advanced Analy@cs Oracle Spa@al & Graph Oracle Spa@al & Graph Oracle Event Processing Big Data Appliance Apache Flume Oracle GoldenGate Oracle Data Integrator Exadata Oracle Oracle Event GoldenGate Processing SOURCES Copyright 2014 Oracle and/or its affiliates. All rights reserved.

15 Oracle Approach Enterprise IoT Analy&cs Internet of Things (IoT) ENTERPRISE IOT ANALYTICS Ac&onable Events Ac&onable Data Sets Ac&onable Informa&on Input Events Streaming Engine Data Reservoir Enterprise Data & Repor&ng Structured Enterprise Data Execu&on Innova&on Data Discovery Lab Discovery Output

16 IoT Analy&cs As A Service An Emerging Opportunity Internet of Things (IoT) IOT DATA STORAGE AND ANALYTICS AS A SERVICE (PROVIDED BY CSP or OTT PROVIDER) Ac&onable Events Ac&onable Data Sets ENTERPRISE IOT ANALYTICS Ac&onable Informa&on Input Events Execu&on Streaming Engine Data Reservoir Enterprise Data & Repor&ng Structured Enterprise Data Innova&on Data Discovery Lab Discovery Output

17 Genera&ng Value from Big Data in IoT Big Data Analytics Platform BI & DW Data Driven Decision Making for Competitive Advantage Information as a Service Monetize your Data Analytics as a Service Competitive Advantage for your Customers Up the M2M and IoT Value Chain

18