From Big Data to Big Results

16 May 2012

Leonard Hayes

Agenda

Big Data – really?

Big Data – a bigger definition

Pioneers of Big Data

Connectedness

Essential Industries impact

An Asset perspective

Big Data survey

16 May 2012 From Big Data to Big Results 2

A wake-up slide

Result: Most mornings 4 companies know I’m awake before I do

16 May 2012 3 From Big Data to Big Results

7:30am

Result: 27 companies know I’m online before I get out of bed

Big Data – a bigger definition

VVV: Volume, Velocity, Variety

SSS: Size, Speed, Structure

16 May 2012 4 From Big Data to Big Results

Connected

Kilobyte (KB)103

Megabyte (MB)106

Gigabyte (GB)109

Terabyte (TB)1012

Petabyte (PB)1015

Exabyte (EB)1018

Zettabyte (ZB)1021

Yottabyte (YB)1024

Data tsunami or tidal wave ???

Big Data experts

16 May 2012 From Big Data to Big Results 5

Why consider the Big Data experts?

Technology – leading the industry

Insight – understanding use case

Regulation – increasing scrutiny

Art of the possible – join Facebook

Expectation – kids of today, customers of tomorrow

Data management – suck every bit of knowledge

Consider what consumerism did for Mobile

16 May 2012 From Big Data to Big Results 6

Google/IDC quotes

“Every two days we create as much information as we

did from the dawn of civilization up until 2003”

“I spend most of my time assuming the world is not

ready for the technology revolution that will be

happening to them soon”

16 May 2012 From Big Data to Big Results 7

Source: IDC's Digital Universe Study, sponsored by EMC, June 2011

Over the next decade, the number of “files” or containers that encapsulate the information in the digital universe will grow by 75x (while the pool of IT staff available to manage them will grow only by 1.5x)

Eric Schmidt, Executive Chairman of Google

Alternative quote

16 May 2012 From Big Data to Big Results 8

“My car starts itself, parks itself, and auto-tunes” Royce Da 5’9”, Rapper

The Internet of Things (IoT)

Started as labelling: RFID, QR

Now it’s connected

16 May 2012 From Big Data to Big Results 9

Smart meters, security systems, PoS, tracking devices

Autonomic systems

Self-configuring

Self-healing

Self-optimising

Self-protecting

Non-intrusive load monitoring, smart-plugs, IHD, HAN etc

Big growth

“The Number Of Mobile Devices Will

Exceed World’s Population By 2012”

Source: Cisco® Visual Networking Index (VNI) Global Mobile Data

Traffic Forecast Update

“Anything but Routine, SAMSUNG Launches a Laundry Experience Game-Changer” Source: Samsung

Connected

16 May 2012 11 From Big Data to Big Results

16 May 2012 From Big Data to Big Results 12

So What?

Exponential growth in edata generation, by:

Devices

Business

People

16 May 2012 From Big Data to Big Results 13

But we already know Big Data

Fast data: SCADA

Big data: Millions of assets

Complex data: Customer

Connected data: EAM/GIS/SCADA/OMS

16 May 2012 From Big Data to Big Results 14

Big Data in the Essential Industries

Industry consolidation IT/OT

SCADA integration

Industry creep (Google)

Disruptive technologies

Consumer expectation

Consumer driven software engineering £££

IoT data sources – more data, faster data

Smart Meters/Intelligent devices

Photographs/Video augmenting or replacing Asset data?

Managing our (connected) assets better

16 May 2012 15 From Big Data to Big Results

Asset registration – Big Data?

Large number of assets, designed, bought, maintained, disposed and occasionally lost

Registration occurs when? – commissioning, live & operational

Structured plant number V’s Functional position/Physical item reference

Location awareness

Decommissioning, refurbishment, recommissioning

What happens when the smart asset “reports for duty” and it’s not yet registered?

Health & Safety – not counting assets

Reporting – rateable asset value

Planning – deeper understanding of asset estate

Commissioning – self-reporting devices

Data Governance – Who’s the master now?

Automation of asset registrations?

Self-discovery networks?

16 May 2012 From Big Data to Big Results 16

www.amt-sybex.com/bigdata

Asset performance data

Operational data from assets – how important?

Asset maintenance strategies – Change for smarter assets?

What data matters? Facebook loves your email address, what do our engineers love?

What is the value of the data to your organisation?

Assets going into the ground now that will last 40 years – what data will we need?

What is the new system of record of asset data, EAM, GIS, EAI, The Asset?

Who do you trust more – asset data from your mobile EAM or live “ping” from the

device?

Joining up/connecting the data is key to this transition to a smarter world

Linking outage data to weather data?

16 May 2012 From Big Data to Big Results 17

www.amt-sybex.com/bigdata

Smart Metering

Approx 53,000,000 meters/supporting infrastructure

Customer behaviour changes? Expectation of Facebook generation

Data – active power, reactive power, meter events, power quality

How to validate the data, estimate, enrich, react to data?

Possibility of seeing and controlling the entire value chain

- from generation/source to consumption?

Decisions around network reinforcement, security of supply?

Combining data from network topology, asset database, smart network to create

actionable items to address issue or take advantage of situations?

So where’s the value?

16 May 2012 From Big Data to Big Results 18

www.amt-sybex.com/bigdata

Big Results – Next steps

Platform/Infrastructure that can support business aspirations

Recognising the growth that is taking place in Big Data

3rd party data (weather, census, topology)

Understand the value of your data

Better data governance

Analytics/Forecasting

Better number crunching, reporting etc

Process/Operational automation

Not just read-only data, early-stage autonomics

Complex event management

An Intelligent set of rules

16 May 2012 19 From Big Data to Big Results

Client survey

Commissioned in parallel with this event today

APCO Worldwide, April 2012

Key findings:

Expecting exponential growth

Big Data is recognised as being strategic issue

Becoming a larger management issue

Operational performance key driver

Linking to business benefit

Key challenge is connecting data

16 May 2012 From Big Data to Big Results 20

Survey findings – Key drivers

16 May 2012 From Big Data to Big Results 21

7.9

8.2

7.8

6.3

7.5

6.7

6.6

Regulatory pressure

Operational performance improvement

Improved customer service

Correction of operational issues

Safety

Statutory accounting etc

Cost management

www.amt-sybex.com/bigdata

6

6

8.1

6.4

7.1

5.6

6.2

Understanding what data you have

Using data proactively

Joining up data across your organisation

Having flexibility within your data management

Sharing data with other organisations

Managing the volume and frequency

Having the enterprise systems to cope

Survey findings – Key challenges

www.amt-sybex.com/bigdata 16 May 2012 22 From Big Data to Big Results

Thank You

16 May 2012 From Big Data to Big Results 23