Grab some coffee and enjoy the pre-show banter

before the top of the

hour! !

The Briefing Room

A Bigger Magnifying Glass: Analyzing the Internet of Things

u Reveal the essential characteristics of enterprise

software, good and bad

u Provide a forum for detailed analysis of today’s innovative

technologies

u Give vendors a chance to explain their product to savvy

analysts

u Allow audience members to pose serious questions... and

get answers!

Mission

Teradata and the Analytics of Things Presenter Name, Date A Bigger Magnifying Glass Analyzing the Internet of Things

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Today’s Speakers

Dan Graham Teradata

Richard Hackathorn Bolder Technology

Eric Kavanagh CEO, The Bloor Group

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Potential of IoT as The Bigger Magnifying Glass

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•  Magnifying Glasses into Your Business –  Basic transactional systems, with reporting –  Integrating data warehouses –  Interactive dimensional analyses –  Active DW to support core biz processes –  Big data from web and social media –  IoT throughout the biz ecosystem

Where we are going…

•  Looking at 8 companies using IoT

•  IoT apps exploding but unclear goals

•  Why should executives care about IoT

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People and process

Operational and edge computing

Doing

Analytics of Things Thinking

Internet of Things

R Its simple: the #AnalyticsofThings is part of the #InternetofThings #IoT

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Public Clouds

Data Center

Analytics Networks

Information Technology

Things Gateway

Operational Technology

The Edge

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“On a three-hour journey, only one out of over two

thousand journeys are delayed by more than five

minutes.”

Gerhard Kress Siemens spokesman

SIEMENS High-speed train between Madrid and Barcelona

R @Siemens makes trains on time in Madrid with @Teradata #IoT

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•  Situation –  32,000 miles of track | 3350 trains per day

•  Problem –  Prevent derailments from overheated wheels

•  Solution –  Sensors every 20 miles | outliers detection

•  Results –  20M daily sensor readings | 1500 issues/day |

new maintenance schedules | cut bearing-related derailments by 75%

Preventing Derailments

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•  Situation –  Per capita electricity consumption

•  Problem –  Peak periods utilization surges –  Electricity based heating

•  Solution –  Alternative pricing programs –  Incentives for natural gas heating

Utilities

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•  Situation –  10-20K sensors per machine

•  Problem –  Unplanned shutdowns –  Consumables cost—felts and belts, parts

•  Solution –  CBM and benchmarking consumables –  Analyze pulp, chemicals, heat, suppliers

•  Results –  $35M selling ‘our’ consumables

Grinding Pulp and Sensor Data

@Teradata Aster delivers $35M in revenue from #IoT

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•  Situation –  Semiconductor manufacturing yields

•  Problem –  Hard to analyze fragmented data –  30K files daily from around the globe

•  Solution –  Consolidating data in data lake

•  Results –  Prepare data for IDW –  Find root causes: quality up, costs down

Increased Product Quality

@ThinkBigA builds data lakes for #IoT

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•  Situation –  Oil shifts around as it is pumped out –  Find the oil, again, and again

•  Problem –  Geolocation accuracy | legacy sensors

•  Solution –  Teradata consultants –  Deep math and analytics

•  Results –  High quality surveys | less downtime

Deep Sea Oil Reservoirs

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•  Situation –  Predicting machine repairs

•  Problem –  No business access to sensor data

•  Solution –  Connect QueryGrid to data lake

•  Results –  Improved maintenance -  Labor, parts, schedules in sync

–  Bridge between cultures

Heavy Assets

https://commons.wikimedia.org/wiki/File:Titan,_once_the_largest_mining_truck_in_the_world.jpg

13 DTG

•  The vision – Smart City 2050 –  Resources (energy, mobility, buildings) –  Quality of life (social, health, environment) –  Innovation (education, economy, research)

•  Solution –  New 42 acre suburb –  Multi-vendor multi-year deployments

•  Results and next steps –  Low voltage grid optimizer –  Balancing to weather is next

Smart Cities

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Data Warehouse

Project benchmarks

Operational grid planning

Grid load forecasts

Strategic grid planning

Low voltage grid optimizer

Grid management

Grid alerts

Smart meters

Energy monitoring and control

Building flexibility

Predictive maintenance

Consumption optimization

Citizen interaction

Smart City: Where OT Meets IT

DTG

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•  IoT will incrementally expand

•  May be limited by tech assimilation

•  Numerous strategic impacts

•  Drives revenue & business strategy

•  Value depends on analytics

Why Should Executives Care About the Internet of Things?

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Why Executives Should Care

•  Value expansion from initial use cases –  Ask questions & imagine opportunities –  Incremental not ‘big-bang’ projects –  Need to evolve people & culture

•  Technology assimilation –  Lead cultural change -- ask tough questions –  Bust thru traditional tech boundaries

R @hackathorn says #IoT projects breed like rabbits and that’s good. Cute bunnies photo

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Why Executives Should Care

Strategic

Tactical

Operational

Policy

Procedure

Actions

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Why Executives Should Care

–  Holistic view of the business

–  Cross-functional business impacts

IoTSensors

IoTNetworks

IoTDataCura2on

DataWarehouse

Analy2cs

IoTBusinessValue

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Questions and Answers

For More Information Hyperlink

Business Value from the Analytics-of-Things

http://www.teradata.com/Resources/White-Papers/Business-Value-from-the-Analytics-of-Things

Obsession with Quality at Western Digital Corporation

http://www.teradata.com/Resources/Case-Studies/Western-Digital-Obsession-with-Quality-at-Western-Digital-Corporation

How the Internet of Things Changes Big Data Analytics

http://data-informed.com/how-the-internet-of-things-changes-big-data-analytics/

Richard Hackathorn http://bolder.com/

Teradata and the Internet of Things http://www.teradata.com/solutions-and-industries/IoT

THANK YOU for your

ATTENTION!

Some images provided courtesy of Wikimedia Commons