Post on 26-May-2020
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 ???
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
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