The North of Scotland is in the midst of a full-scale transformation. Building on a well-established reputation as a global energy hub, the North is fast becoming a key destination for emerging innovation across an increasing range of sectors.
The DIGIT North Summit is designed to bring IT and Digital leaders together and drive practical innovation through shared learning. The event will facilitate cross pollination between key industries, from traditional sectors like Oil & Gas and Agriculture to high-growth fields like: Life Sciences, Biotech, Gaming, Fintech and Space.
The programme will contextualise the key emerging technologies and industry disruptors, and consider the vital role that IT and Digital leaders will play in ensuring organisations can thrive amid a backdrop of market change and economic volatility.
3. James McLean CIO – SSEN Transmission
A Five Year Transformation….
4. Overview
➢ Who are SSEN Transmission?
➢ What we started with, where we are, and where we are going
➢ Organisation and Operating model - Moving to Value Stream delivery
models
➢ Hiring and outsourcing
➢ Culture alignment and executive support for the strategy
5. • Transmission takes energy from Generators and hands it off to Distribution companies – WE ARE THE MOTORWAYS.
• It is a price control business funded by Ofgem currently in RIIO-T2 which ends April 2026
• Fastest growing Transmission company driven by ScotWind & NOA network expansion
• To meet Network energy targets we will need to capital invest significantly, every year until to 2030
Network Option Assessment (NOA) on Vimeo
10Gw 24Gw
ScotWind Leasing Plans
6. What we started with, where we are, and where we are going
Build and Fly at the same time
What we started with 2019/20:
• Low core system digitisation; many spreadsheets; huge green field
• Digital transformation plan submission to Ofgem and circa £45m awarded
• Team of 12
• Cloud first strategy – price control is a timebox
• Ramp up and establish pace of programmes and organisation build out
Where we are:
• Team of 30 established – Project delivery, Service Delivery, Analytics, Data
Governance, Operations Technology, Architecture
• Core systems re-platformed to cloud, separated from legacy support
• Value streams established, culture of digitisation underway
• Service Delivery function and Technical support teams growing
• Improving and developing departmental controls, standards, procedures, policy
adherence
Where are we going 24/25:
• Estimated team of 45 – fully staffed to current org design
• Substantial progress of digital programme – agile exploitation on core platforms
• Further strategic plans necessary to support business growth
• Submittal of RIIO-T3 Digital business case
• April 2026 new price control begins
7. Change
Resources
Change
Resources
Change
Resources
Change
Resources
Change
Resources
VS1: Stakeholders &
Customers
VS2: Capital Projects
VS3: Planning &
Commercial
VS4: Operations
IT VS5: Functions,
Integration, Exploitation
Product Owner
3rd Party
Vendors
Solution
Architect
Security
Architect
Security
Assurance
Delivery Lead
Business
Analyst
Change
Resources
Data &
Analytics
Product Owner Delivery Lead
Business
Analyst
Change
Resources
Data &
Analytics
Product Owner Delivery Lead
Business
Analyst
Change
Resources
Data &
Analytics
Product Owner Delivery Lead
Business
Analyst
Change
Resources
Data &
Analytics
Product Owner Delivery Lead
Business
Analyst
Change
Resources
Data &
Analytics
Solution
Architect
Cyber Program CIO
Head of Cyber
Resilience OT CROT Project (Waterfall)
Solution
Architect
Security
Assurance
3rd Party
Vendors
Digital Program Manager Head of IT Operations
Head of Data
& Analytics
Lead
Solution
Architect
Transmission Operating Model
Internal provider of services – with flex to use external suppliers e.g. fixed capacity resources
Hybrid Waterfall with Agile, shifting to primarily Agile as culture evolves
Lead
Security
Assurance
Directorates
8. Hiring and Outsourcing
Clear use cases and differentiation
Staffing Strategy:
• Differentiating service roles
• Roles where deep business understanding creates value
• Challenging market conditions
Outsource Strategy:
• Leverage Group provision
• SaaS, PaaS Cloud provision for key systems
• SSE Cloud for Integrated Data Platform
Vendor Strategy:
• Accelerate insight and delivery from expertise
• Long term partnerships with framework suppliers
• Leverage Agile experience and establish MVP’s
9. Culture Alignment to achieve Digital Transformation
To be successful and realise the value and business outcomes set out in the Digital Vision, the following
needs to be in-place
The Executive Committee must believe in the Digital Vision and Strategy.
Leadership commitment
To deliver at pace we will have the right governance but that the programme requires fiscal flexibility to adapt to circumstance as we
evolve our capability.
Target setting and
governance
Our digital journey is heavily depend on developing the skills and capabilities required to ensure that the organisation can absorb and
embrace the digital change.
Organisational readiness
and communication
Ensure the right people come together from business and IT to deliver each initiative, dedicating the right amount of time to deliver
the outcomes
Implement, accelerate &
scale - “Start small, think
big, act fast”
Digital should become embedded in our ways of working and business as usual to ensure that we are flexible to change at all levels.
Sustain
We need to encourage the awareness of the intrinsic value of data as an asset to the business and stewardship of that data.
Fostering a digital & data
culture
Recognition that the digital investment benefits will be realised not only during T2 but into T3 and beyond; this is a long game.
Business value focused
10. Value of Digital within SSEN Transmission
Digital Transformation is key to the delivery of SSEN Transmission’s commitments in the RIIO-T2 5 year
plan, as well as meeting the broader digital ambitions of SSE Group
Ofgem: “The fastest route to Net Zero is via Data and Digitalisation”
Optimise Operations
Reduced manual
processing, multiple data
entry and information
retrieval.
Enhanced Customer Experience
Deliver the great stakeholder and
customer experience needed to meet
increased expectations, and in-line with
our peers
Attract & retain talent
Support the growing workforce with the
digital and data skills they need in the
modern world, and providing the
capabilities they need to deliver our
strategic objectives and meet their
personal goals
Increase safety
Through better visibility of our
operations and our people
Readiness for T3
Be better prepared with the
right platforms and processes
to react to the challenges &
opportunities that T3 will bring
Simplify & Standardise
Deliver the capabilities that the business
desire, consolidate existing tools where
needed and developing the platforms to
collaborate effectively with Suppliers to
maximise the value they deliver to SSENT
Improve decision making
(more informed and quicker)
Better, faster, fact-based decision
making at all levels through self-
service reporting & analytics.
Reduce Network Risk
Better data and information to
inform NARM and asset
performance to inform and
optimize investment decisions
14. Digital (R)evolution:
Developing an Open Business Platform for Multi-Agency Working
Chief Officer
of Digital &
Technology
Steve Roud
People
Development
Manager
Sandie
Scott
▪ Setting the vision
▪ From vision to reality
▪ Blending evolution
and revolution to
achieve pace and
stability
▪ Adoption and change
management
15. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
What are the new and evolving needs
of the city and citizens?
How does this change the work we
do?
Where will our employees
interact with customers?
Where and how can our
employees do their best
work?
What skills and behaviours
will our people need to
thrive?
How might our culture
need to shift?
Aberdeen City Transformation
17. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
Multi-Agency Transformation &
LOIP Improvement
ACC Transformation Programme
Whole
System
Change
Service Design
(Annual Critical Path)
Aberdeen City Council Business Platform
18. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
Multi-Agency Transformation &
LOIP Improvement
ACC Transformation Programme
Whole
System
Change
Service Design
(Annual Critical Path)
Underlying Platform Components (Customer)
19. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
Multi-Agency Transformation &
LOIP Improvement
ACC Transformation Programme
Whole
System
Change
Service Design
(Annual Critical Path)
Underlying Platform Components (Data)
20. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
Multi-Agency Transformation &
LOIP Improvement
ACC Transformation Programme
Whole
System
Change
Service Design
(Annual Critical Path)
Underlying Platform Components (ACC apps)
21. The Nature of
Work
The
Workforce
of the
Future
The
Workplace
of the
Future
Multi-Agency Transformation &
LOIP Improvement
ACC Transformation Programme
Whole
System
Change
Service Design
(Annual Critical Path)
Aberdeen City Council Transformation
22. Internal Drivers and Enablers
Digital Principles
Main
Drivers
for
change
Customer/
Data/ Digital
Strategy
Technology
change opp
End of life/
burning
platforms
Business
change
opps
Regulatory
change
Commercial
challenges
Cost Trajectory
• Reduce costs
• Visibility and control of cost base
• Simplification and standardisation
• Rationalise licencing
Technology Trajectory
• Removal of components/ systems
• Simplify support
• Drive controlled self service
Target
Architecture
23. Driving Innovation
Convergence
App migration
App modernisation
Foundational Strategic Value and Capabilities
Application
Dev
Data
Estate
Smart Apps
(Infused with
pre-built AI)
Intelligent Apps
(Cloud Native)
Data migration
Data modernisation
Advanced Analytics
Data Intelligence
(AI/ML)
27. How it’s going….
Successfully migrated
data to the cloud
Teams sites
established for every
single Cluster and
Service in the Council
An army of Digital
Champions leading
the way
An elite crack squad
of Super Champs
training their peers
Programme for Senior
Managers
Teams, SharePoint,
Yammer and Stream
fully established.
28. Moving towards a Multi-Agency approach
Invited partners to
join our Super
Champion
community
Duplicated
successful
structure over to
ACHSCP
Open approach to
resource and
knowledge sharing
Presenting to the
Digital Office
Request-a-Guest
29. HOW WE DID IT
Training Voice Co-creation
Communications
Empowering
Managers
Executive
Sponsorship
Self-managing
People feel
knowledgeable,
capable and confident
to transition to the
future state
People share their
views and ideas
through established
reliable channels, digital
and face-to-face.
People are collectively
designing solutions to
organization wide
issues or challenges set
by leadership
Communicate the
business reasons of the
change and how the
change will impact
employees
Engage managers and
supervisors toguide
employees through
changes, reinforce and
role model behaviours
at a locallevel.
Create active and
visible executive
engagement
People make change
happen. Spontaneous
self-led groups with
minimal intervention
corporately.
Measurement
Measuring if our
changes are having the
desired impact towards
solving problems and
achieving our business
objectives
32. Top things that made a
difference
1. Clear direction and tasks
2. Recruitment
3. Sponsorship and support
4. Reward and recognition
5. Visibility and clarity
33. Digital (R)evolution:
Developing an Open Business Platform for Multi-Agency Working
Chief Officer of
Digital &
Technology
Steve Roud
People
Development
Manager
Sandie
Scott
36. NSTA’s role
Creating value through strategic approach and focused action
Strategic Vision
Digital Strategies
Early Action
Open data, NDR, website &
access to data
Early Outcomes
Improved compliance,
benchmarking & data quality
Powers
Energy Act 2016
Petroleum Act 1998
37. Insights
Benchmarking and open data to
encourage positive action
Digital Energy Platform
• Public access
• Downloadable data
• Cloud based
• Integrated with
other data sources
• Authoritative
Geographic Information
Systems (GIS)
Energy transition & integration
Power of data and digital
Digital excellence unlocking numerous insights and opportunities
Exploration
Hydrocarbons & CCS
Transparency
Energy Pathfinder Inclusion
38. Why did we do it?
Background
• Original purpose of data
• Original process for collection
Potential uses
• Decommissioning, repurposing
• Different attributes required
• Data quality paramount
Using technology
• Spatial formats
• Attribute and spatial-based quality
checks
40. Practical implementation of data quality improvement
• Numerous improvements including requiring spatial formats to be reported
• Enforcing data quality by automated checks sending out automated emails
• Working with companies to help them report data correctly
• Positive feedback
Infrastructure reporting
Scope
110
Companies
responding
40+
companies
reporting
data
36 basic
automated
checks
45 Types of
infrastructure
2 workshops 40+
resubmissions
41. Future plans
More attributes Driving further quality
improvements
Industry involvement
Tighter definitions
More checks Submissions more automated
58. Copyright RAB-Microfluidics 2022
Version 1.0.
Confidentiality Statement: This document is the property of RAB-Microfluidics R&D Company Limited and is considered to be strictly confidential. It contains information intended only for the person to whom
it is transmitted.
Improving Machine Reliability
with Data-Driven Insight
enabled by Automation
Delivered By
Dr Rotimi Alabi
62. Copyright RAB-Microfluidics 2022
Industry Challenge and Market Opportunity
£2.1 Bn spent
on breakdown
and downtime
losses.
2.06bn spent
on breakdown
and Downtime
loses
£2.83 Bn spent
to diagnose
failure.
Market Growth CAGR – 8.7%
Analysis automation will add
£400 Mn to testing and analysis
market by 2025 – Markets and Markets
2020
62
Total Market Value - £5.2 Bn
1044 lubrication related engine failures in the
maritime industry in 2020.
72. Copyright RAB-Microfluidics 2022
create
Microfluidic Lab-on-a-chip Technology
Online Analysis/Big Data Generation
Digital Analogue/Twin
Predictive Analytics/Maintenance
Value
• Enhanced production efficiency.
• Better understanding of machinery performance.
• Automation and digitisation of oil analysis.
• Machinery availability.
• Cost savings.
• Predictive analytics and maintenance.
Value Proposition
72
73. Copyright RAB-Microfluidics 2022
73
Summary
• Platform technology that permits the
real-time analysis of lubricating oil.
• Address unmet need for rapid point-of-
use multi-parameter testing of lubricant
samples.
• Transform lubricating oil analysis by:
o automating conventional processes.
o information for predictive analytics
models and internet of things (IoT)
modules.
74. Copyright RAB-Microfluidics 2022
Contact Us.
Monday – Friday 08:00 – 17:00
Business Hours
rotimi.alabi@rab-microfluidics.co.uk
E-mail Address
Unit 5
Aberdeen Science & Technology Park
Bridge of Don
Aberdeen AB1 2AB
Building Address
07429 315557
01224 010400
Telephone Number
105. Sustainability – nice to have, or business
critical?
In 2020, 95 Fortune 500
companies have a Chief
Sustainability Officer
Over 600 sustainability
standards to report on
113. Click to edit Master title text
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What is a brand?
www.tltechsmart.com
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Our Story
www.tltechsmart.com
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Voice Trends - Control
Ref. Statista
Alexa
Compatible
Devices
2020+
~4000
>100,000
2017 www.tltechsmart.com
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Voice Trends - Search
www.tltechsmart.com
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Voice Trends - Commerce
www.tltechsmart.com
Ref. PWC Global Consumer Insights Pulse Survey
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Voice Trends - Commerce
www.tltechsmart.com
Ref. PWC Global Consumer Insights Pulse Survey
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Characteristics of a Voice Interface
www.tltechsmart.com
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Benefits of a Voice-First Strategy
www.tltechsmart.com
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Designing for Alexa
Tutorials:
▪ Alexa Skills Kit
▪ Alexa Developers on YouTube
▪ Dabble Lab
▪ Codecademy
Further community support:
▪ Github Alexa
▪ Alexa Presentation Language for creating display
graphics – APL Ninja
▪ Alexa community Slack group
TL Tech Voice strategy blog piece www.tltechsmart.com
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Thank You
For further information:
www.tltechsmart.com
caroline@tltechsmart.com
https://www.linkedin.com/in/caroline-laurenson/
https://www.createyourkindspace.com/
123. #digitnorth
Mark Stephen
Journalist & Broadcaster,
BBC Scotland
Deryck Mitchelson
Chief Information Security Officer,
Check Point
Mark Mitchell
Technical Evangelist
for the Office of the CTO,
Check Point
143. PICTURES
Enabling large-scale medical
image data research
19th May 2022
DIGIT North Innovation Summit
Susan Krueger, PICTURES Project Manager skrueger001@dundee.ac.uk
Project website: https://www.imageonamission.ac.uk/
144. Overview
PICTURES
InterdisciPlInary Collaboration for efficienT and effective Use of clinical images in big health care
RESearch (PICTURES)
About
Overcoming the challenges of providing access to population scale, routinely collected health
and imaging data for AI development whilst protecting patient confidentiality
Scope
▪ the Project
▪ the Problem
▪ the Solution
146. PICTURES | the Project
Context
▪ InterdisciPlInary Collaboration for efficienT and effective Use of clinical images in big health
care RESearch (PICTURES)
▪ Medical Research Council (MRC) funded, 5-year programme of work
▪ Collaboration between the University of Dundee (UoD), University of Edinburgh (UoE),
Abertay University, Public Health Scotland (PHS) and industry partner Aidence B.V.
▪ Effective start/end dates are 1st August 2019 to 31st July 2024
147. PICTURES | the Project
Motivation
▪ Linked, de-identified population level data
▪ Opportunity for very large-scale studies
▪ Wide range of disease areas
▪ Improved diagnostic accuracy
▪ New detection methods
148. A TRE is a Trusted Research Environment. Also known as ‘Data Safe Havens’, TREs
are highly secure computing environments that provide remote access to health data
for approved researchers to use in research that can save and improve lives.
What is a TRE?
TREs help make research
efficient, collaborative and
cost effective, providing rich
data that enables deep insights
which will go on to improve
healthcare and save lives.
TREs provide approved
researchers with a single
location to access valuable
datasets. The data and analytical
tools are all in one place, a bit
like a secure reference library.
How is my data safeguarded?
TREs make research safer.
Making data available through
a TRE means that people can be
confident that their personal
health data is accessed securely
and their privacy protected.
Learn more about TREs and discover examples of how TREs
are being used to enable life-saving health research.
Health data should always be kept safe and secure, and used responsibly
to ensure privacy. Heath Data Research UK ensures these high standards
are met by promoting the use of the ‘Five Safes’ model across all TREs.
Learn more about TREs
Why are they important?
Safe People
Only trained and specifically accredited
researchers can access the data
Safe Projects
Data is only used for ethical, approved research
with the potential for clear public benefit
Safe Data
Researchers only use data that have been
de-identifed to protect privacy
Safe Outputs
All research outputs are checked to ensure
they cannot be used to identify subjects
Safe Settings
Access to data is only possible using secure
technology systems – the data never leaves the TRE
149. PICTURES | the Project
Core Programme
▪ increasing the capabilities of Safe Havens to support emerging technologies and new
data types (images)
▪ building on existing measures, in place to maintain the trust of the public that their
personal health data is used for the benefit of patients and / or the population as a
whole
▪ 9 work packages:
▪ metadata for complex cohort building
▪ scalability and automation
▪ environments and tools for researchers
▪ speeding it all up
150. PICTURES | the Project
Exemplar 1
Developing a multivariable lung nodule malignancy risk prediction model
for incidental lung nodules using both imaging markers and clinical data.
Exemplar 2
Developing an algorithm to predict individual risk of dementia using MRI
brain scans, genetic data and other longitudinal health records.
Both exemplars will determine new information from routinely collected
data that would otherwise have been ignored. Predicting and therefore
treating diseases at an early stage improves patient outcomes and reduces
the cost to the NHS.
CT chest scans
MRI brain scans
151. PICTURES | the Project
Data Science and Engineering Research Questions
How to build
research relevant
Cohorts: Messy,
unstructured,
identifiable data!
How to handle Big
Data: scaling
How can we
protect patient
data?
Natural
Language
Processing
Machine
Learning and
classification
methods
Hardware and
Software
optimisation
methods: Next
Generation Safe
Haven
Cybersecurity
research
152. PICTURES | the Problem
Info model taken from https://dcm4che.atlassian.net/wiki/spaces/d2/pages/1835038/A+Very+Basic+DICOM+Introduction
DICOM
▪ Digital Imaging and Communications in Medicine standard
Radiologists communicate their
findings to the referring clinician
through text-based Radiology
Reports (aka Structured Reports).
153. PICTURES | the Problem
PACS
▪ Picture Archiving and Communication System (PACS)
▪ Central archive
▪ Regional Health Boards
▪ Single PACS for Radiology
▪ Relatively stable population
▪ Unique healthcare identifier
North Region
East Region
West Region
154. PICTURES | the Problem
Research Copy 2010-2018
Modality Total count of images Live
CT 1,551,835,095
MR 475,172,769
PT 34,731,015
SR 27,539,556
CR 21,131,886
XA 7,746,882
RF 7,292,660
DX 6,274,075
MG 2,348,114
NM 1,222,818
PX 225,726
IO 100,608
155. PICTURES | the Problem
Pixel Data
Images can contained burned in Personally Identifiable Information (PII)
156. PICTURES | the Problem
Table taken from https://towardsdatascience.com/understanding-dicom-bce665e62b72
DICOM Metadata
Data elements or ‘tags’ in the Header contain values like name, ID, etc., and the image pixel data.
157. PICTURES | the Problem
Radiology reports are designed to be both
machine and human readable, with
information organised and hierarchical.
Image taken from https://www.dicomstandard.org/docs/librariesprovider2/dicomdocuments/wp-cotent/uploads/2018/10/day2_s7_dicom_structured_reports_d-clunie.pdf?sfvrsn=d4e2b344_4
Structured Reports
158. PICTURES | the Problem
Handling Data at Scale
https://www.researchgate.net/publication/239743213_Digital_imaging_in_radiology_practice_An_introduction_to_few_fundamental_concepts
159. PICTURES | the Solution
DE-IDENTIFY and PSEUDONYMISE
PACS
Researcher VM with
tools to view and
manipulate images
Study-specific
Image Metadata
and Pixel Data
(Project Ids)
BUILD COHORT
Research co-ordinators
Cohort builders
Researchers
Disclosure
Control
Preamble
Header
Pixel Data
DICOM DE-IDENTIFY and TRANSFORM
IDENTIFIABLE ZONE DE-IDENTIFIED ZONE ANALYTIC ZONE
System Administrators
De-identification Analysts
Scottish Medical Imaging (SMI)
A microservices architecture
For information on SmiServices go to https://github.com/SMI/SmiServices
160. PICTURES | the Solution
Complex Cohort Building
Three methods of feature extraction
1. DICOM Tags 2. Natural Language Processing 3. Autoencoder
Image taken from http://www.dclunie.com/pixelmed/DICOMSR.book.pdf
Simple example of a DICOM Structured Report
161. PICTURES | the Solution
Complex Cohort Building
Three methods of feature extraction
1. DICOM Tags 2. Natural Language Processing 3. Autoencoder
Research Data Management Platform (RDMP)
https://github.com/HicServices/RDMP/
Semantic Search System for Electronic Health Records
(SemEHR) https://pubmed.ncbi.nlm.nih.gov/29361077/
162. PICTURES | the Solution
Protecting Patient Confidentiality
Disclosure control – it’s all about the layers!
• Legal
• Procedural
• Technical
• Human
GRAIMatter, a HDR UK funded sprint:
• Aim: a range of tools and methods to support TREs to
assess output from AI methods for potentially identifiable
information, investigate the legal and ethical implications
and controls, and produce a set of guidelines and
recommendations to support all TREs with export
controls of AI algorithms.
GRAIMatter – a DARE UK Sprint project https://dareuk.org.uk/sprint-exemplar-project-graimatter/
163. PICTURES Programme
Scottish Medical Imaging (SMI) Service
▪ a national resource for the provision of images and associated report data to researchers
▪ may be linked to other available pseudonymised datasets
▪ launched in April 2022
▪ small number of high impact research studies already underway
▪ aims to continually develop and grow in the coming years
▪ https://www.isdscotland.org/Products-and-Services/eDRIS/Scottish-Medical-Imaging-Service/
164. Acknowledgments
Acknowledgments
▪ Farr Institute of Health Informatics Research and Dundee University Medical School.
▪ Medical Research Council (MRC) grant No. MR/M501633/1 (PI: Andrew Morris) and the Wellcome Trust grant No. WT086113 through the Scottish Health
Informatics Programme (SHIP) (PI: Andrew Morris).
▪ MRC and EPSRC (grant No. MR/S010351/1) and the Chief Scientist Office of the Scottish Government Health and Social Care Directorates via a leverage grant
made to Farr Scotland, and the Scottish Government through the “Imaging AI” grant award.
▪ This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-5012) funded by the UK MRC, Engineering and
Physical Sciences Research Council, Economic & Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish
Government Health and Social Care Directorates, Health and Social Care Research & Development Division (Welsh Government), Public Health Agency
(Northern Ireland), British Heart Foundation (BHF), & the Wellcome Trust.
Further reading
An extensible big data software architecture managing a research resource of real-world clinical radiology data linked to other health data
from the whole Scottish population Nind T, Sutherland J, McAllister G, Hardy D, Hume A, MacLeod R, Caldwell J, Krueger S, Tramma L,
Teviotdale R, Abdelatif M, Gillen K, Ward J, Scobbie D, Baillie I, Brooks A, Prodan B, Kerr W, Sloan-Murphy D, Herrera JFR, McManus D, Morris
C, Sinclair C, Baxter R, Parsons M, Morris A, Jefferson E. Gigascience. 2020 Sep;9(10) . doi:10.1093/gigascience/giaa095. PMID: 32990744;
PMCID: PMC7523405.
165. Health Informatics Service
University of Dundee
Mail Box 15
Ninewells Hospital and Medical School
Dundee
DD1 9SY
01382 383102
dundee.ac.uk/hic
hicservices-admin@dundee.ac.uk
Thanks for
Listening!
170. Ransomware
$265B estimated cost of
ransomware by 2031
Unplanned/Planned
Disruptions
62.9% organizations have
suffered a disruption
Cloud Complexity
By 2025, 100 zettabytes of
cloud data
Need 24x7: no downtime and no data loss
TOP CUSTOMER CHALLENGES
171. BEYOND THE COST OF RECOVERY
21 days
average disruption period of an attack
66%
of victims suffered significant revenue loss
25%
of victims suffered a period of business closure
$1.85 million
average cost of ransomware
recovery
173. 2
4 6
3
Continuous
user/admin
education
Never think your
organization is
impenetrable
Test recovery plans
to prove RTOs and
RPOs
Keep systems
patched and
antivirus updated
1
5
Harden data
protection
solutions
Take advantage
of 3rd party
expertise
BEST PRACTICES FOR PREVENTION AND PREPARATION
174. Guide for Cybersecurity Event Recovery
Data Protection
Where Does Data Protection Come In?
Identify Protect
Detect Cyber
Event
Respond to
Cyber Event
Remediate
Root Cause
Tactical
Recovery
Phase
Strategic
Recovery
Phase
Figure 3-1: NIST SP 800-184 Guide for Cybersecurity Event Recovery Relationship with the NIST CSF
175. Continuous Data Protection
Resume in minutes to
seconds before an attack
Ransomware
Recovery
Foolproof recovery with
fastest RTO and RPO
Disaster
Recovery
Freedom to innovate
across clouds
Multi-Cloud
Mobility
CONTINUOUS PROTECTION
Any App, Any Cloud, Any Threat
177. ▸ No production impact
▸ No scheduling, snapshots, or agents
▸ Hardware, Storage & Cloud Agnostic
▸ Always-on, always protected
NEAR-SYNCHRONOUS
REPLICATION
Storage
of your choice
Software-only,
simple deployment
Protect on-premises, to the cloud,
or both simultaneously
▶︎ SIMPLICITY AT SCALE
▶︎ HYBRID AND MULTI-CLOUD
▶︎ CONTINUOUS DATA PROTECTION
178. GRANULAR
POINT-IN-TIME
RECOVERY WITH THE
ZERTO JOURNAL
Legacy vs. Journal-based Recovery
10:00:00 backup
Up to 24 hrs data loss
6:00:00 snapshot
Up to 4 hrs data loss
9:59:55
Rewind within
seconds
10:00:00
Disaster hits
▶︎ SIMPLICITY AT SCALE
▶︎ HYBRID AND MULTI-CLOUD
▶︎ CONTINUOUS DATA PROTECTION
▸ Recover in minutes to seconds
before an attack or disruption
▸ Fastest RPOs and RTOs
▸ Neutralize ransomware threats
179. Applications recovered as a single entity
DB
Server
App.
Server
Web
Server
File
Server
2:48:00 AM 2:48:05 AM 2:48:10 AM 2:48:15 AM 2:48:20 AM
DB
Server
App.
Server
Web
Server
File
Server
DB
Server
App.
Server
Web
Server
File
Server
DB
Server
App.
Server
Web
Server
File
Server
DB
Server
App.
Server
Web
Server
File
Server
▸ Write order fidelity across entire
multi-VM application stack
▸ No staggered backup windows
▸ All copies kept in app-centric
groups
APP-CENTRIC
RECOVERY
▶︎ SIMPLICITY AT SCALE
▶︎ HYBRID AND MULTI-CLOUD
▶︎ CONTINUOUS DATA PROTECTION
181. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
V M
V M
V M
V M
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
P H Y S I C A L
S T O R A G E
182. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
P H Y S I C A L
S T O R A G E
V M V M V M V M
183. Scenario #1
Recovery
• Utilizes Live Failover
• Fully automated and orchestrated
• RPO of Seconds
• RTO of Minutes
• Only 3 clicks to failover
• Simple reverse replication and failback
185. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
V M
V M
V M
V M
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
V R A
V R A
I A A S
P U B L I C C L O U D D R S I T E
Z C A
S T O R A G E
C L O U D
S T O R A G E
A P I
186. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
V R A
V R A
I A A S
P U B L I C C L O U D D R S I T E
Z C A
S T O R A G E
C L O U D
S T O R A G E
A P I
V M V M
V M V M
V M
187. Scenario #2
Recovery
• Utilizes Live Failover
• Fully automated and orchestrated
• Converts into public cloud IaaS on the fly
• RPO of Seconds
• RTO of Minutes
• Only 3 clicks to failover
• Simple reverse replication and failback
189. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
V M
V M
V M
V M
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
V R A
V R A
I A A S
P U B L I C C L O U D D R S I T E
Z C A
S T O R A G E
C L O U D
S T O R A G E
A P I
190. P R O D U C T I O N
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
V R A
V M
V M
D A T A S T O R E S
Replica Compressed journal
<=30 days retention
H O S T
V R A
V M
V M
P H Y S I C A L
S T O R A G E
I M M U T A B L E C O P Y
D R S I T E
V C E N T E R Z V M
V R A
V R A
I A A S
P U B L I C C L O U D D R S I T E
Z C A
S T O R A G E
C L O U D
S T O R A G E
A P I
191. I M M U T A B L E C O P Y
R E C O V E R Y
S I T E
V C E N T E R Z V M
P H Y S I C A L
S T O R A G E
H O S T
D A T A S T O R E S
H O S T
V R A V R A
P H Y S I C A L
S T O R A G E
V M V M
V M V M
192. Scenario #3
Recovery
• Utilizes immutable copy restores
• Repository is portable so can be
attached to any Zerto infrastructure
• Restores are still app-centric
• Available on prem and in cloud storage
• RPO and RTO longer that CDP restores
but no longer than traditional backup
194. BJSS Limited
May 2022
Helping to transform Elexon's central infrastructure and internal
systems to facilitate MHHS within Great Britain’s electricity market
DATA AND DECARBONISATION
196. THE LEADING
TECHNOLOGY &
ENGINEERING
CONSULTANCY
Trusted by our 100 active clients, we
collaborate to deliver complex,
innovative technology, engineering
and industry solutions that millions of
people use every day.
Talented people working together
on complex projects.
Nine tightly-integrated
services, all underpinned
by Digital Transformation:
Locations across the UK, USA,
Europe and Australia.
Active engagements within
large enterprises.
Technology
& Engineering
Cloud
& Platform
Managed
Service
Data & AI
Strategy Design
Energy, Commodities
& Utilities
Financial
Services
Health &
Social Care
Retail &
Consumer Markets
Public Sector
Betting &
Gaming
Transport
LowCode Sustainability
Cyber Security
Delivery by:
197. OUR LOCATIONS
> Copenhagen
> Dublin
> Lisbon
> Porto
Europe
> Melbourne
Australia
> Aberdeen
> Birmingham
> Bristol
> Cardiff
> Edinburgh
> Exeter
> Glasgow
> Leeds
> Lincoln
> Liverpool
> London
> Manchester
> Milton Keynes
UK
> Newcastle
> Nottingham
> Reading
> Sheffield
> Swansea
> York
> Houston
> New York
USA
198. WHO ARE ELEXON?
Elexon is responsible electricity settlement which is essential to the smooth
running of the electricity system in GB
> Elexon manages the Balancing and Settlement Code (BSC) for Great Britain’s electricity market
> In simple terms, they compare the amount of electricity that generators say they will produce, and how much
electricity suppliers say will be consumed.
> They then work out the prices for these differences, and transfer funds between the relevant parties.
Key Stats:
> Elexon handles more than 1.5m meter readings each day
> Elexon settles around 46 TWh of electricity annually
> Elexon handles billions of pounds of electricity companies’ money each year.
199. SO WHAT IS MHHS?
The Market-wide Half Hourly Settlement (MHHS) Programme is an industry first, in that Ofgem
has placed responsibility on the industry to deliver the Programme and made Elexon the Senior
Responsible Owner (SRO) of the Programme.
> The outcome of MHHS will be a faster, more accurate settlement process for all market participants
> MHHS will see the introduction of site-specific reconciliation using half-hourly meter readings
> MHHS is a key enabler to a smarter, more flexible energy system and will be vital in supporting flexible solutions to
enable the nation’s transition to Net Zero
> MHHS is expected to save consumers up to £4.5B over the next 20 years
> The first step in defining the ‘blueprint’ for future large change programmes within the energy industry.
200. WHAT IS BJSS’ ROLE?
BJSS are proud to support Elexon’s Helix programme, a multi-year programme which is
the largest transformation of Elexon’s central systems and infrastructure for more than twenty
years.
> Helix is delivering the changes to Elexon’s internal systems and processes in support of MHHS
> BJSS are responsible for delivering WP1 – the Data Hub, as well as supporting overall programme leadership to support
the enterprise agile delivery
> Multi-supplier programme, working alongside CGI and Cognizant
> Working closely with Microsoft throughout the delivery, leveraging our Microsoft Gold Partner status to ensure best
practice and maximise the value of Azure cloud technologies to support the programme
> The data hub is crucial to the success of Helix as it underpins the other components of the programme, managing the
data that other aspects of the service require, in order to accurately calculate balancing costs and provide settlement
process back to suppliers.
202. > 30 million updates
(1.5 billion rows) per day
> 10 TB working set
CHALLENGES
Large scale IOT-
style data
Long ramp-up
period
Complex and
evolving
interfaces
Security
> Scalable cost model
over next 5-10 years
> MHHS program in-flight
> Legacy data flows
> Large volume of PII
203. > Maybe in the future?
PROBLEMS WE DON’T HAVE
Exploratory
data science
Un-predictable
scale
Data sprawl Poor data quality
> We’re bound by the
number of houses in the
UK
> We have a small, well
understood set of data
types
> Most of the data we
receive has been
pre-validated by
upstream systems
205. A WORD ON “BIG DATA” PROCESSING
Proprietary runtimes for open tools
Spark
(processing)
Parquet /
Delta / Avro
(storage)
206. AZURE DATA PROCESSING
> Many, many products available!
> Lots of different ways to solve the same problem
> Assuming your data is big and parallelisable
> Storage: ADLS, Parquet, Avro, Delta
> Ingest: DataFactory (Integration), EventHubs (Streaming)
> Processing: Spark
> DataBricks or Synapse or Stream Analytics or DF Spark or…
> POC a few, pick one. You can change later if you need to…
208. WHERE NEXT?
Helix
> Complete development work
> Wait for the rest of MHHS to catch up
> Industry testing (12 months)
> Other data-intensive applications within Elexon
> Data Governance requirements
Re-use the data platform capability
209. THANKS FOR YOUR TIME
Visit our
stand for a
chat
Connect
with us
212. • Problem definition
• Workload Locations and Types
• Distributed workload support challenges
• Problem Workloads
• Use cases 1-3:
• Problem - analysis - solutions
Agenda
215. On-Prem/DC
SELF HOSTED APPS
New POS SaaS
API
New Other SaaS
API
Data Warehouse
Public or Private
Cloud
Normal Stuff
Databases
Sysadmin
Patches
Updates
Networks
Break Fix
New Stuff
Database appliances
Hyperscaler Admin
Hyperscaler workload costs
APIs
Complex ETL
Multiple End Points
Containers
DevOps
BI Work Loads
Public Cloud
Hybrid Clouds
216. Key challenge then is:
• Transform to modern workloads
• Maintain stability
Most organisations will need help with this.
217. • Legacy OS
• Legacy Application Stack
• Complicated Architecture
• Licensing issues
• Cross platform Workflows and ETL
What
about the
problem
workloads?
218. The ideal support partner provides:
• Connected infrastructure options
across public, private, on-prem
and SaaS
• Can provide a Full Stack service
across those platforms
• Has a single point of contact for
resolution across all platforms for:
• Security, network, application
and database level
For modern workloads and legacy
applications.
219. • Strategic move to Azure tenancy
frustrated by core application vendor
• API issues with Core Apps to SaaS
providers
• Oracle licence issues
Use Case 1.
(Small Bank)
Solution:
Oracle friendly HA cloud, with cross
platform monitoring and support
220. • Ancient stack and Infrastructure - end
of life
• Needed custom patching to bring
stack up to current support levels
• Move from traditional metal
infrastructure to streamlined HA
Database Optimised Cloud
Use Case 2.
(Large Website)
Solution:
Custom patching regime to new OS/Stack
versions
HA Database friendly cloud with full-resolving
support.
221. Business disruption caused change in
business needs - move to multi-franchise
model
Multiple POS systems introduced
Move from IBM/Oracle to Legacy Cloud
environment
Flexible compute - near SaaS support and
cross platform monitoring and workflow
management
Use Case 3.
(High Street Restauranteur)
Solution:
Oracle friendly HA cloud, with cross
platform monitoring and support