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IOT TOP BUSINESS MODELS AND USE
CASES FOR 2016
© 2016 VoltDB
OUR SPEAKERS
Cheryl Wiebe, Partner,
Analytics of Things,
Teradata
Dennis Duckworth,
Dir. Product Marketing,
...
3
Internet of Things now
worth 14.4 trillion dollar up
from 35 billion dollar.
Is amazing Compound
Hype Cycle Growth Rate
...
4
•  Smart Meters
•  Digital Oil
Field
•  Delivery
•  Refinement
•  Wind/Solar
Management
•  Lights Out
Production
•  Smar...
5
Two Major Subsystems
Operations of Things Analytics of Things
Things
Gateway
The Edge
Networks
Analytics
Data Center
Loc...
6
IoT data introduces new complexities
Data management and Analytics must adapt
Key Issues:
•  The velocity and volume of ...
7
Two Types of IoT users
Asset Maker / Seller Owner/ operators
Focus
External…the customers
using their products
Internal…...
8
Use cases for the Asset Maker / Seller of Heavy Equipment:
Condition Based Monitoring & Maintenance
Improving field serv...
9
•  Data Collaboration
–  Engines
–  Aircraft
–  Operator
•  Improved Maintenance
–  Condition-Based
–  Predictive
Produc...
10
GOAL: Deploy scalable
fault probability calculations
–  Define remaining useful life of all trucks
–  Eliminate downtim...
11
Semi Conductor
Owner/Operator of the Manufacturing Site or Campus
Operations Performance Optimization
Helping high tech...
12
Need to analyze a
constantly changing
set up >20,000
attributes to identify
yield loss factors
required flexible
schema...
13
Parse machine logs, to
identify significant
machine events.
Pattern matching helps
predicts machine failure
Affinity an...
© 2016 VoltDB
VOLTDB OVERVIEW
Mike Stonebraker
FAST
World Record Cloud Benchmark:
YCSB 2.4 millon tps
Other Stonebraker Co...
© 2016 VoltDB
VOLTDB: WE DON’T MAKE THE APPS, WE MAKE THE APPS…
15
• Real-time intelligence and context for richer interac...
© 2016 VoltDB
Low  Complexity  
  
Rich,  Smart  
   Value of Individual Data Item Aggregate Data Value
DataValue
Data
War...
© 2016 VoltDB
Streaming
Analytics
-  Filtering
-  Windowing
-  Aggregation
-  Enrichment
-  Correlations
Deep
Analytics
- ...
© 2016 VoltDB
VOLTDB FAST DATA USE CASES AND INDUSTRIES
Use Cases
Personalization
Precision resource counting, billing
Rea...
© 2016 VoltDB
IOT DEPLOYMENTS WITH VOLTDB*: SMART METERS
* More than 60 million meters under management
Leader in the Gart...
© 2016 VoltDB
IOT IS A DEEP STACK: OUR FOCUS IS DATA
Device
Security & Policy
Communication
Edge Compute
More Networks
Cen...
© 2016 VoltDB
IoT WILL REQUIRE FAST DATA OPERATIONAL SYSTEMS
4. Optimized Opera&onal  
3. Automated Opera&onal  
2. Intera...
© 2016 VoltDB
VOLTDB CUSTOMERS ARE DOING IT TODAY
Platforms IoT Applications
Huawei
Openet
Nokia
Hewlett Packard Enterpris...
© 2016 VoltDB 23
FAST
DATA
BIG
DATA
Devices
Security/Authorization
Device Management
…
Application1
Application2
Applicati...
© 2016 VoltDB
Ingest sensor readings from
millions of smart meters
Energy Validation process.
Determine id billing thresho...
page© 2016 VoltDB
THANK YOU
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IoT Top Business Models and Use Cases for 2016

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In this webinar, experts from VoltDB and Teradata discussed top-of-mind topics to help you gain immediate traction in your IoT architectures. Cheryl Wiebe, Partner, Analytics of Things, Think Big, A Teradata Company and Dennis Duckworth, Dir. Product Marketing, VoltDB will discuss the most impactful IoT use cases and business models, and key technology considerations to ensure effective analytics against IoT data. Finally they will outline real world IoT customer case studies showcasing break-through value. To view the entire webinar, click here: http://learn.voltdb.com/WRTeradataIoT.html

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IoT Top Business Models and Use Cases for 2016

  1. 1. page IOT TOP BUSINESS MODELS AND USE CASES FOR 2016
  2. 2. © 2016 VoltDB OUR SPEAKERS Cheryl Wiebe, Partner, Analytics of Things, Teradata Dennis Duckworth, Dir. Product Marketing, VoltDB
  3. 3. 3 Internet of Things now worth 14.4 trillion dollar up from 35 billion dollar. Is amazing Compound Hype Cycle Growth Rate (CHCGR) of 41143% Big Data Borat ‫‏‬@BigDataBorat 18 Mar
  4. 4. 4 •  Smart Meters •  Digital Oil Field •  Delivery •  Refinement •  Wind/Solar Management •  Lights Out Production •  Smart Warehouses •  Smart Cities •  Waste Management •  City Works •  Sowing and Harvesting •  Yield Prediction •  Plant Disease Diagnostics •  Delivery Efficiency •  Driver Safety •  Truck Maintenance •  Insurance Based on Driving •  Market Predictions Based on These Other Markets •  Smart Hospitals •  Smart Home + Healthcare Possibilities for IoT in Your Industry Gartner: Internet of Things: The Foundation of the Digital Business, Jan 6, 2016“Analytics are essential to the success of IoT systems. They are arguably the main point of the IoT as they support the decision-making process in operations that are created in business transformation and digital business programs.” Roy Schulte and Rita Sallam, Three Best Practices for Internet of Things Analytics, October 23, 2015
  5. 5. 5 Two Major Subsystems Operations of Things Analytics of Things Things Gateway The Edge Networks Analytics Data Center Local | Cloud | Hybrid
  6. 6. 6 IoT data introduces new complexities Data management and Analytics must adapt Key Issues: •  The velocity and volume of the data may be huge •  In some cases, most of the data is unimportant, or redundant •  In some cases there will be a need to increase/decrease collection •  Some data is clearly erroneous •  May need intelligent processing at the edge
  7. 7. 7 Two Types of IoT users Asset Maker / Seller Owner/ operators Focus External…the customers using their products Internal…their own operation Examples Large Equipment, Auto, Aerospace Utilities, Hospitals, Plants, Oil Exploration / Refining, Cities Goal R&D, warranty, Product as Service Improve own operations, product Analytics at Edge Data Compression; Anomaly detection Fleet coordination; policy enforcement
  8. 8. 8 Use cases for the Asset Maker / Seller of Heavy Equipment: Condition Based Monitoring & Maintenance Improving field services for some of the most complex, transportation and heavy asset companies out there
  9. 9. 9 •  Data Collaboration –  Engines –  Aircraft –  Operator •  Improved Maintenance –  Condition-Based –  Predictive Product as a Service •  Power by the Hour –  Pay for usage –  Known cost projection •  Pay when it works, not breaks –  Supplier/Operator incentives aligned •  IoT enables model in lower cost businesses Commercial Airline Services
  10. 10. 10 GOAL: Deploy scalable fault probability calculations –  Define remaining useful life of all trucks –  Eliminate downtime and opportunity costs –  Extend new analytics to the edge Anything less than high performance = high cost and low customer satisfaction Post-operation manual analysis was slow and unsatisfactory •  Engine sensor data •  Vehicle master & engineering data Single system failure detection required time-intensive computation for cross-fleet prediction © 2016 Teradata
  11. 11. 11 Semi Conductor Owner/Operator of the Manufacturing Site or Campus Operations Performance Optimization Helping high tech, discrete and process manufacturers reduce equipment downtime, plant throughput, and available-to-promise Paper / Cellulose Processed Food Consumer Elec. Contract Mfg
  12. 12. 12 Need to analyze a constantly changing set up >20,000 attributes to identify yield loss factors required flexible schema AND large matrix math Data prep •  Ingest raw data using JSON •  UnPivot Sensor Data •  From Semi- conductor Probes (>20,000 variables) •  Principal components analysis •  Linear Regression •  Embedded Visualization
  13. 13. 13 Parse machine logs, to identify significant machine events. Pattern matching helps predicts machine failure Affinity analysis predicts likely replacement parts •  Npath Pattern detection •  Affinity analysis •  Visualize Process Automation Equipment •  Line equipment; Sensor logs
  14. 14. © 2016 VoltDB VOLTDB OVERVIEW Mike Stonebraker FAST World Record Cloud Benchmark: YCSB 2.4 millon tps Other Stonebraker Companies Customers Technology •  In-Memory RDBMS with durability •  Scale-Out shared-nothing architecture •  Reliability and fault tolerance •  Super fast ingest and export •  SQL + Java with full ACID transactions •  Hadoop and data warehouse integration •  Open source and commercially licensed (24x7) •  Cloud Ready Co-Founded by winner of the 2014 ACM Turing Award Forrester Wave for In-Memory DB
  15. 15. © 2016 VoltDB VOLTDB: WE DON’T MAKE THE APPS, WE MAKE THE APPS… 15 • Real-time intelligence and context for richer interactions • Make different decisions on each individual event or person • Analyze and act on streaming data • More efficient use of hardware • 100X faster than traditional databases • World record performance in the cloud (YCSB) • Millisecond response time • High-speed data ingestion • Simpler apps, easier to test and maintain • Easier to program with SQL + Java • Seamless ecosystem integration • Data is always consistent and correct, never lost Smarter Faster Simpler 1/10 of the Resources Needed 100X Traditional DB 100% Consistent, Correct
  16. 16. © 2016 VoltDB Low  Complexity     Rich,  Smart     Value of Individual Data Item Aggregate Data Value DataValue Data Warehouse Hadoop, etc.NoSQL Interactive Real-time Analytics Record Lookup Historical Analytics Exploratory Analytics Data in Motion Data at Rest Fast Data Big Data Feeds, Collectors CEP CEP + DB VoltDB DataInteraction THE FAST DATA + BIG DATA UNIVERSE: VOLTDB OWNS A UNIQUE MARKET SEGMENT Teradata
  17. 17. © 2016 VoltDB Streaming Analytics -  Filtering -  Windowing -  Aggregation -  Enrichment -  Correlations Deep Analytics -  Statistical correlations -  Multi-dimensional analysis -  Predictive/ Prescriptive analytics Operational Interactions / Transactions -  Context-aware -  Personal -  Real-time + Big Data FAST DATA APPLICATION REQUIREMENTS Fast Data
  18. 18. © 2016 VoltDB VOLTDB FAST DATA USE CASES AND INDUSTRIES Use Cases Personalization Precision resource counting, billing Real-time policy enforcement Operations and manufacturing IoT sensor data processing Industries Mobile/Telco IoT Media & Entertainment Financial Services Retail
  19. 19. © 2016 VoltDB IOT DEPLOYMENTS WITH VOLTDB*: SMART METERS * More than 60 million meters under management Leader in the Gartner Magic Quadrant Announced Utility Customers •  UK Smart Meter •  ShikoKu Electric Power •  Hokkaido Electric Power
  20. 20. © 2016 VoltDB IOT IS A DEEP STACK: OUR FOCUS IS DATA Device Security & Policy Communication Edge Compute More Networks Centralized Compute Data Services Cloud Applications Fast (in motion) Streaming Analytics: real time summary aggregation, modeling Transaction Processing: per-event decisions using context + history Big (at rest) Exploration: data science, investigation of large data sets Reporting: recommendation matrixes, search indexes, trend and BI
  21. 21. © 2016 VoltDB IoT WILL REQUIRE FAST DATA OPERATIONAL SYSTEMS 4. Optimized Opera&onal   3. Automated Opera&onal   2. Interactions Opera&onal   1. Monitoring Streaming  analy&cs   IoTApplication Evolution
  22. 22. © 2016 VoltDB VOLTDB CUSTOMERS ARE DOING IT TODAY Platforms IoT Applications Huawei Openet Nokia Hewlett Packard Enterprise + Smart Energy GB Mitsubishi’s Smart Metering Wearables Home Security / Automation
  23. 23. © 2016 VoltDB 23 FAST DATA BIG DATA Devices Security/Authorization Device Management … Application1 Application2 Application3 Models/ Historical Insights Horizontal Capabilities Specific Applications DATA IN IoT PLATFORMS …
  24. 24. © 2016 VoltDB Ingest sensor readings from millions of smart meters Energy Validation process. Determine id billing threshold has been exceeded. Initiate message to user of dynamic rate change. Categorize and filter by meter type and rate table prior to export to billing application and other apps connected through Teradata Update Operational models and processes Events VoltDB Triggered Alerting Teradata 1 3 2 1 2 3 4 4 Rule Engine SAMPLE SMART METER SYSTEM ARCHITECTURE 5 5
  25. 25. page© 2016 VoltDB THANK YOU

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