Ronan Fitzpatrick, Director of Digital at PWC shares insights from PWC research on AI and Robotic Process Automation. Ronan explains that insight and trust in your data is pivotal to the successful use of Artificial Intelligence and Robotics.
Key to your company's success is being able to integrate and use the data you have. Linked Data holds the promise to deliver on this with semantic data hubs that don't strip context and enable you to use your data across your organization.
Dcaf transformation & kg adoption 2022 -alan morrisonAlan Morrison
A keynote presentation on knowledge graph adoption trends and how to do digital transformation differently.
Delivered at the Enterprise Data Transformation & Knowledge Graph Adoption
A Semantic Arts DCAF Event
February 28, 2022
Data-centric design and the knowledge graphAlan Morrison
The #knowledgegraph--smart data that can describe your business and its domains--is now eating software. We won't be able to scale AI or other emerging tech without knowledge graphs, because those techs all require a transformed data foundation, large-scale integration, and shared data infrastructure.
Key to knowledge graphs are #semantics, #graphdatabase technology and a Tinker Toy-style approach to adding the missing verbs (which provide connections and context) back into your data. A knowledge graph foundation provides a means of contextualizing business domains, your content and other data, for #AI at scale.
This is from a talk I gave at the Data Centric Design for SMART DATA & CONTENT Enthusiasts meetup on July 31, 2019 at PwC Chicago. Thanks to Mary Yurkovic and Matt Turner for a very fun event!.
Scaling the mirrorworld with knowledge graphsAlan Morrison
After registration at https://www.brighttalk.com/webcast/9273/364148, you can view the full recording, which begins with Scott Abel's intro for a few minutes, then my talk for 20 minutes, and then Sebastian Gabler's. First presented on October 23 at an SWC webinar.
Conclusions:
(1) The mirrorworld (a world of digital twins, which will be 25 years in the making, according to Kevin Kelly) will require semantic knowledge graphs for interaction and interoperability.
(2) This fact implies massive future demand for knowledge graph technology and other new data infrastructure innovations, comparable to the scale of oil & gas industry infrastructure development over 150 years.
(3) Conceivably, knowledge graphs could be used to address a $205 billion market demand by 2021 for graph databases, information management, digital twins, conversational AI, virtual assistants and as knowledge bases/accelerated training for deep learning, etc. but the problem is that awareness of the tech is low, and the semantics community that understands the tech is still quite small.
(4) Over the next decades, knowledge graphs promise both scalability and substantial efficiencies in enterprises. But lack of awareness of its potential and how to harness it will continue to be stumbling blocks to adoption.
At Neo4j we believe that ‘Graphs Are Everywhere’. In this session, we’ll be looking specifically at graphs within the Financial Services industry. We’ll review the types of data that are typically available within a bank, illustrate the graphs can be formed from that data, and discuss the use cases that those graphs can enable and support.
The use cases presented will include Anti-Money Laundering and Fraud Detection and Prevention (including integration with AI and Machine Learning technologies), Regulatory Compliance (such as BCBS 239 and GDPR), Customer 360 View, Master Data Management, and Identity and Access Management.
Many players in the Financial Services industry already rely on Neo4j's graph database: such as Lending Club, the world's largest microservices credit marketplace, for Network and IT, the big German insurance company die Bayerische for graph-based search, Cerved for Master Data Management, Wobi for price comparison and real-time recommendation, or UBS for Identity and Access Management.
Key to your company's success is being able to integrate and use the data you have. Linked Data holds the promise to deliver on this with semantic data hubs that don't strip context and enable you to use your data across your organization.
Dcaf transformation & kg adoption 2022 -alan morrisonAlan Morrison
A keynote presentation on knowledge graph adoption trends and how to do digital transformation differently.
Delivered at the Enterprise Data Transformation & Knowledge Graph Adoption
A Semantic Arts DCAF Event
February 28, 2022
Data-centric design and the knowledge graphAlan Morrison
The #knowledgegraph--smart data that can describe your business and its domains--is now eating software. We won't be able to scale AI or other emerging tech without knowledge graphs, because those techs all require a transformed data foundation, large-scale integration, and shared data infrastructure.
Key to knowledge graphs are #semantics, #graphdatabase technology and a Tinker Toy-style approach to adding the missing verbs (which provide connections and context) back into your data. A knowledge graph foundation provides a means of contextualizing business domains, your content and other data, for #AI at scale.
This is from a talk I gave at the Data Centric Design for SMART DATA & CONTENT Enthusiasts meetup on July 31, 2019 at PwC Chicago. Thanks to Mary Yurkovic and Matt Turner for a very fun event!.
Scaling the mirrorworld with knowledge graphsAlan Morrison
After registration at https://www.brighttalk.com/webcast/9273/364148, you can view the full recording, which begins with Scott Abel's intro for a few minutes, then my talk for 20 minutes, and then Sebastian Gabler's. First presented on October 23 at an SWC webinar.
Conclusions:
(1) The mirrorworld (a world of digital twins, which will be 25 years in the making, according to Kevin Kelly) will require semantic knowledge graphs for interaction and interoperability.
(2) This fact implies massive future demand for knowledge graph technology and other new data infrastructure innovations, comparable to the scale of oil & gas industry infrastructure development over 150 years.
(3) Conceivably, knowledge graphs could be used to address a $205 billion market demand by 2021 for graph databases, information management, digital twins, conversational AI, virtual assistants and as knowledge bases/accelerated training for deep learning, etc. but the problem is that awareness of the tech is low, and the semantics community that understands the tech is still quite small.
(4) Over the next decades, knowledge graphs promise both scalability and substantial efficiencies in enterprises. But lack of awareness of its potential and how to harness it will continue to be stumbling blocks to adoption.
At Neo4j we believe that ‘Graphs Are Everywhere’. In this session, we’ll be looking specifically at graphs within the Financial Services industry. We’ll review the types of data that are typically available within a bank, illustrate the graphs can be formed from that data, and discuss the use cases that those graphs can enable and support.
The use cases presented will include Anti-Money Laundering and Fraud Detection and Prevention (including integration with AI and Machine Learning technologies), Regulatory Compliance (such as BCBS 239 and GDPR), Customer 360 View, Master Data Management, and Identity and Access Management.
Many players in the Financial Services industry already rely on Neo4j's graph database: such as Lending Club, the world's largest microservices credit marketplace, for Network and IT, the big German insurance company die Bayerische for graph-based search, Cerved for Master Data Management, Wobi for price comparison and real-time recommendation, or UBS for Identity and Access Management.
An introduction to Neo4j and Graph Databases. Learn about the primary use cases for Graph Databases and explore the properties of Neo4j that make those use cases possible.
Data Science Salon: Building a Data Science CultureFormulatedby
Catalina is a Data Scientist with a specialty in building out scalable data solutions for startups.
Next DSS MIA Event - https://datascience.salon/miami/
There's a huge hype around the power of data science across industries. However, not all companies have been able to successfully build out their data science capabilities, and some are just starting to think about doing so. Just as each business is unique, each data science endeavor is unique. In this talk, we explore both the non-negotiables in building a data science culture and how to tailor your data science initiatives to match your business needs at different stages of your journey towards reaping the benefits of a data science culture.
BIG DATA IN BUSINESS Implement and use Big Data to your organization’s advantageAurélie Pols
IE Business School - Executive Education
3-Day International Executive Program
June 22-24, 2015, Monday-Wednesday
Madrid, Spain
Session 9: Managing Privacy and Data Governance, a Risk based Approach
Abstract della presentazione di Fabio Rizzotto, IT Research & Consulting Director di IDC Italia, tenuta all’IDC Big Data Conference II, a Bologna il 19 novembre 2013
This Document Includes lecture/workshop notes for BIG DATA SCIENCE workshop at NTI 6-7th of Dec 2017
Hint: 1:This is an Initial Version, and it will be updated.
2: Telecommunication/5G parts were not covered through the workshop, although, I will add a comprehensive analysis regarding mentioned cases.
If anyone is interesting in working practically (HANDS ON) mentioned case study, just drop me an e-mail: m.rahm7n@gmail.com
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleVasu S
Real-world data science practitioners offer perspectives and advice on six common Machine Learning problems
https://www.qubole.com/resources/ebooks/oreilly-ebook-machine-learning-at-enterprise-scale
Big data course | big data training | big data classesNaviWalker
In your world of digitization, Data is an essential source. Businesses in various fields use this Data to get important ideas for their growth. Eventually, this creates a sense of urgency to start learning Big Data. By doing so, you can stay productive and solve real world problems.
Big Data helps to derive important business decisions. Furthermore, successful Big Data processing in huge industrial sectors has taught important lessons on various Big Data concepts.
Big Data training with various Big Data Analytics courses will help you master Data Analysis. In the present world, you have ample scope of becoming a Big Data Scientist. And also getting other Big Data job roles.
Engineering Content: The Discipline of Designing Future-Ready ContentJoe Gollner
A session delivered at Spectrum 2017 at the Rochester Institute of Technology for the STC Rochester Chapter. It pulls together many years of reflection on what really works when it comes to designing content management and publishing systems - and why this has become so important amid the changes wrought by Digital Transformation.
This talk was given at SEMANTiCS 2014 in Leipzig. It gives an overview how to develop an enterprise linked data strategy around controlled vocabularies based on SKOS. It discusses how knowledge graphs based on SKOS can extended step by step due to the needs of the organization.
Κnowledge Architecture: Combining Strategy, Data Science and Information Arch...Connected Data World
"The most important contribution management needs to make in the 21st Century is to increase the productivity of knowledge work and the knowledge worker", said Peter F. Drucker in 1999, and time has proven him right.
Even NASA is no exception, as it faces a number of challenges. NASA has hundreds of millions of documents, reports, project data, lessons learned, scientific research, medical analysis, geospatial data, IT logs, and all kinds of other data stored nation-wide.
The data is growing in terms of variety, velocity, volume, value and veracity. NASA needs to provide accessibility to engineering data sources, whose visibility is currently limited. To convert data to knowledge a convergence of Knowledge Management, Information Architecture and Data Science is necessary.
This is what David Meza, Acting Branch Chief - People Analytics, Sr. Data Scientist at NASA, calls "Knowledge Architecture": the people, processes, and technology of designing, implementing, and applying the intellectual infrastructure of organizations.
Anil Patel is Managing Director of GrantBook. At GrantBook, he is leading the development of their Real-time Impact Reporting and Data Visualization practice area. In developing this practice area, Anil spends considerable time searching for useful trends in other creative industries. Industries that make use of human-centered design, 21st management practices and action-learning. Anil is also a co-founder and current board member of Framework, a charity he started with friends over a decade ago. Framework’s marquee program is the Timeraiser. To date, it has generated over 150,000 volunteer hours, invested over $1 million to the careers of emerging artists and supported over 500 nonprofits volunteer programs. Anil is an Ashoka Fellow and Action Canada Fellow
An introduction to Neo4j and Graph Databases. Learn about the primary use cases for Graph Databases and explore the properties of Neo4j that make those use cases possible.
Data Science Salon: Building a Data Science CultureFormulatedby
Catalina is a Data Scientist with a specialty in building out scalable data solutions for startups.
Next DSS MIA Event - https://datascience.salon/miami/
There's a huge hype around the power of data science across industries. However, not all companies have been able to successfully build out their data science capabilities, and some are just starting to think about doing so. Just as each business is unique, each data science endeavor is unique. In this talk, we explore both the non-negotiables in building a data science culture and how to tailor your data science initiatives to match your business needs at different stages of your journey towards reaping the benefits of a data science culture.
BIG DATA IN BUSINESS Implement and use Big Data to your organization’s advantageAurélie Pols
IE Business School - Executive Education
3-Day International Executive Program
June 22-24, 2015, Monday-Wednesday
Madrid, Spain
Session 9: Managing Privacy and Data Governance, a Risk based Approach
Abstract della presentazione di Fabio Rizzotto, IT Research & Consulting Director di IDC Italia, tenuta all’IDC Big Data Conference II, a Bologna il 19 novembre 2013
This Document Includes lecture/workshop notes for BIG DATA SCIENCE workshop at NTI 6-7th of Dec 2017
Hint: 1:This is an Initial Version, and it will be updated.
2: Telecommunication/5G parts were not covered through the workshop, although, I will add a comprehensive analysis regarding mentioned cases.
If anyone is interesting in working practically (HANDS ON) mentioned case study, just drop me an e-mail: m.rahm7n@gmail.com
O'Reilly ebook: Machine Learning at Enterprise Scale | QuboleVasu S
Real-world data science practitioners offer perspectives and advice on six common Machine Learning problems
https://www.qubole.com/resources/ebooks/oreilly-ebook-machine-learning-at-enterprise-scale
Big data course | big data training | big data classesNaviWalker
In your world of digitization, Data is an essential source. Businesses in various fields use this Data to get important ideas for their growth. Eventually, this creates a sense of urgency to start learning Big Data. By doing so, you can stay productive and solve real world problems.
Big Data helps to derive important business decisions. Furthermore, successful Big Data processing in huge industrial sectors has taught important lessons on various Big Data concepts.
Big Data training with various Big Data Analytics courses will help you master Data Analysis. In the present world, you have ample scope of becoming a Big Data Scientist. And also getting other Big Data job roles.
Engineering Content: The Discipline of Designing Future-Ready ContentJoe Gollner
A session delivered at Spectrum 2017 at the Rochester Institute of Technology for the STC Rochester Chapter. It pulls together many years of reflection on what really works when it comes to designing content management and publishing systems - and why this has become so important amid the changes wrought by Digital Transformation.
This talk was given at SEMANTiCS 2014 in Leipzig. It gives an overview how to develop an enterprise linked data strategy around controlled vocabularies based on SKOS. It discusses how knowledge graphs based on SKOS can extended step by step due to the needs of the organization.
Κnowledge Architecture: Combining Strategy, Data Science and Information Arch...Connected Data World
"The most important contribution management needs to make in the 21st Century is to increase the productivity of knowledge work and the knowledge worker", said Peter F. Drucker in 1999, and time has proven him right.
Even NASA is no exception, as it faces a number of challenges. NASA has hundreds of millions of documents, reports, project data, lessons learned, scientific research, medical analysis, geospatial data, IT logs, and all kinds of other data stored nation-wide.
The data is growing in terms of variety, velocity, volume, value and veracity. NASA needs to provide accessibility to engineering data sources, whose visibility is currently limited. To convert data to knowledge a convergence of Knowledge Management, Information Architecture and Data Science is necessary.
This is what David Meza, Acting Branch Chief - People Analytics, Sr. Data Scientist at NASA, calls "Knowledge Architecture": the people, processes, and technology of designing, implementing, and applying the intellectual infrastructure of organizations.
Anil Patel is Managing Director of GrantBook. At GrantBook, he is leading the development of their Real-time Impact Reporting and Data Visualization practice area. In developing this practice area, Anil spends considerable time searching for useful trends in other creative industries. Industries that make use of human-centered design, 21st management practices and action-learning. Anil is also a co-founder and current board member of Framework, a charity he started with friends over a decade ago. Framework’s marquee program is the Timeraiser. To date, it has generated over 150,000 volunteer hours, invested over $1 million to the careers of emerging artists and supported over 500 nonprofits volunteer programs. Anil is an Ashoka Fellow and Action Canada Fellow
Business Assurance: The Quality Implications of Digital TransformationCognizant
To advance the digital business agenda, QA organizations must break loose from their traditional bug testing shackles and embrace frictionless, full lifecycle automation and a continuous delivery approach.
Digital Transformation Playbook: Guide to Unleashing Exponential GrowthBMC Software
BMC, the global leader in IT solutions for the digital enterprise, has teamed with PSFK, one of the world’s leading think tanks, to develop The Digital Transformation Playbook. This guide provides key insights and actionable steps for business executives and public sector organizations to follow as they seek to enhance customer experiences, processes, and business models through digital transformation. To download a complimentary copy of The Digital Transformation Playbook, visit http://www.bmc.com/playbook.
You had a strategy. You were executing it. You were then side-swiped by COVID, spending countless cycles blocking and tackling. It is now time to step back onto your path.
CCG is holding a workshop to help you update your roadmap and get your team back on track and review how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
La Importancia del Análisis de la InformaciónNexolution
Estudios demuestran que las empresas que aplican la analítica obtienen unos resultados mejores que los de sus iguales. Y aquellas organizaciones con un alto Cociente Analítico es decir, con una filosofía general basada en analítica, tienen un rendimiento medio tres veces superior.
La analítica de negocio permite que su organización identifique las tendencias y los patrones sutiles de modo que pueda anticiparse y controlar los acontecimientos para mejorar los resultados.
Lo invitamos a ver nuestro webcast "La importancia del análisis de la información para la toma de decisiones", donde le mostraremos:
- En qué están invirtiendo las empresas actualmente para optimizar su desempeño
- Descubra cómo lograr un análisis profundo de la información para la mejor toma de decisiones a través de una estrategia de Analítica de Negocios
- Analice el grado analítico de su empresa para la toma de decisiones
Presentador: Sergio Velazquez
Información de las soluciones: informacion@nexolution.com
Selecting the right data analysis tool for your audit function requires a risk based selection process. In this session you will learn how to select the best tool and more importantly integrate the process into your staff. The right approach minimizes the risk of selecting a product that might not fit your organization, which could impair your function as it sits underutilized or on the shelf. Finding the right issues quickly and timely improves the value of auditing and assists auditing to win more work.
Attending this webinar you will learn a step-by-step approach:
. How to select the software
. Build a short/long term on-boarding roadmap
. Realize the lost opportunity of not including all auditors (no auditor left behind)
Introducing Smartsheet Gov: The Trusted Work Execution Platform for GovernmentAmazon Web Services
Departments, agencies, and bureaus need a secure way to execute and scale their work to keep up with the growing demands on government programs. Smartsheet Gov is a secure and reliable platform built on the AWS GovCloud (US) that helps Federal agencies bring innovation, collaboration, and transparency to government initiatives. As the only FedRAMP Authorized work execution platform listed in the FedRAMP marketplace, Smartsheet Gov enables agencies to operate with an increased sense of agility, manage work in real time, and make better decisions with timely and accurate information. During this session, we’ll dive into the specific use cases of Smartsheet Gov, including Project and Program Management, Operations and Asset Management, and Organizational Budgets and Planning. Sponsored by Smartsheet.
How to build an it transformation roadmapInnesGerrard
An estimated 80 percent of #businesses will need to transform their current IT efforts to keep up with new business expectations and technological developments. These include investments such as cloud computing, IoT and BigData projects.
Agile Practices for Transitioning to SAP S/4HANA® panayaofficial
Attend this webinar for advice on best practices for transitioning to SAP S/4HANA. Topics include:
Uncovering five tips for organizations that want to implement both SAP S/4HANA and agile practices
Understanding the changes that a move to SAP S/4HANA requires
Selecting the best-fit solution to support a transition to SAP S/4HANA
How to Turn Raw Data into Product Revenue by Retrofit PMProduct School
Most companies have a goldmine of data, yet lack the ability to know what to do with it. In this talk, Monica shared perspective on how to evaluate data, package it, and turn it in to additional revenue streams.
Main takeaways:
- Identify use cases for data.
- Turn those use cases in to product offerings.
- Create a pricing model & collect revenue.
Similar to THE GOOD, THE BAD, THE DATA - Artificial Intelligence and Robotic Process Automation - DAMA March 2019 Event (20)
Robotics and Artificial Intelligence - The good the bad and the data - John T...Ken O'Connor
John Thompson from Client Solutions Ireland presents a brief history of Artificial Intelligence, why it's such a hot topic, the benefits it can bring and the challenges it presents.
The data value map for GDPR - How to extract Business Value from your GDPR Pr...Ken O'Connor
In this pack from the joint webinar between DAMA UK and DAMA Ireland, Ken O'Connor explains how smart businesses are using the DataValueMap.com (from Cork University Business School) to visually map their personal data supply chain and extract business value in the process.
The DataValueMap.com is a paper based, tech free, silo busting business tool that helps business managers build a shared understanding of any data initiative.
It's perfect for enabling business people to quickly sketch how critical information (such as personal data in the case of GDPR) flows through their business.
Ken explains how The Data Value Map applies "Nudge Principles" (including "Choice Architecture" and "Design Thinking") to Nudge the heads of each business function, i.e. the data stakeholders, to take responsibility for their role in the personal data "Information Supply Chain".
Data Protection Officers (DPOs) will find this very useful when performing Data Protection Impact Assessments (DPIAs).
Dama Ireland slides - Data Trust event 9th June 2016Ken O'Connor
Do we need a Data Trust / Data Quality Mark?
Presentation by Data Management Specialist, Ken O'Connor:
Our food packaging provides facts about the food we buy. It's required by law. These facts enable us to make informed decisions about the food we consume. What about when we seek to make informed decisions in our business processes? What do we know about the data we're consuming? How can we trust that the data we depend on is fit for the purpose for which we need it? In this presentation, you will learn:
Your rights and responsibilities as a data consumer and provider;
The questions you should ask about the data you consume;
The facts you should provide about the data you provide;
The need for a "Data Q-Mark" or a "Data Trust-Level" ;
The presentation was followed by a panel discussion with Ronan Brennan, the CTO of Silverfinch (a MoneyMate company). In October 2015, Silverfinch announced it was handing €2.5 trillion of look-through assets for asset manager clients worldwide. Ronan shared the SilverFinch success story with the attendees, which is built on solid data management practices.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
THE GOOD, THE BAD, THE DATA - Artificial Intelligence and Robotic Process Automation - DAMA March 2019 Event
1. THE GOOD, THE
BAD………..
THE DATA
Artificial Intelligence and Robotic Process Automation
Presentation by Ronan Fitzpatrick
March 2019
2. CEOs need to make better use of data
analytics as a means to identify
efficiencies and opportunities. Using
their data in the right way will also
enable them to take advantage of the
upcoming Artificial Intelligence
revolution. But in order to be confident
that their organisation is fit for the future
they must first solve the key skills
challenge.
2PwC
Digitisation encompasses ‘the process of moving from
analog to digital form’.2 Digitisation is the only way to meet
the greater demand for real- time fulfilment, 24/7
availability, a personalised consumer experience, greater
accuracy, predictive data, faster processing and improved
customer identity management. The digital landscape
spans the use of channels such as websites, social
media, mobile apps and so on to enable a more digitised,
interactive and improved experience. Digitised work is
also quicker, cheaper andmore reliable than manually
processed work, regardless of whether it is insourced,
outsourced, or executed on a perfect manualprocess.
The ultimate goal is to digitise the majority of a
company’s processes, only relying on people where
Digitisation is a logical and necessary next step
3. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Organisations both globally and in
Ireland are clear they know the
information they need in order to make
strategic decisions for their ongoing
business success. But, many are
struggling with the comprehensiveness
of that data they receive.
A striking finding from the report is the
significant information gap that exists
between the data CEOs need, and
what they get
Irish organisations lag global counterparts on leveraging data
%3
Irish CEOs said the data about their customers’
preferences and needs was critical or important
for long-term decision making
4. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Bridge the gap:
limitations in the data that enables
businesses to perform financial
forecasting, data about their brand and
reputation, and imminent business
risks. Interestingly, there was also a
scarcity of data about how the latest
technological trends will disrupt their
industries,
Irish organisations lag global counterparts on leveraging data
%4
said the data they receive about their
Customers was comprehensive.
5. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Build your data foundation
When you are using data to drive
organisational growth, there’s no
room for error. You need to develop a
data framework, build the strategy,
optimise your infrastructure,
processes and systems, and create
the right culture internally to become
a data-driven organisation.
Data & Analytics priorities
5
Apply advanced analytics
You have the right data architecture
and can rely on your data quality.
Now what do you do with it? That’s
where predictive analytics comes in.
It uses your data to give you the
potential to act, not react. Now you
can start filtering the signal from the
noise and look ahead with
confidence.
Improve business performance
Use new data-based insights to
pinpoint opportunities in your industry
to work smarter, focus and prioritise.
Then make change stick, by
delivering data and performance
measures to the right people at the
right time - and set up the right
incentives for people to act on them.
6. Activating the
AI revolution
64% of Irish CEOs believe that Artificial Intelligence (AI)
will significantly change the way they do business in the
next five years
7. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
51%
of Irish CEOs have no plans to
pursue any AI initiatives at the
moment
AI Planning lags significantly behind our global peers
7
10. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Automation roadmaps combine more than one technology
10
3
• Documents scanning and verification
• Validation and authentication of individuals
• Global search and screening
engines that provide relevant and
up to date customer information
• Workflow tool enabling
an efficient straight through process
• Data storage
• Self learning systems processing
unstructured data
• Automation of manual activities
using Robotics solutions
Case workflow tracker
and repository Biometric ID verification
Artificial Intelligence
Search & screening
1 2
4
6
Robotic Process
Automation • Standardisation and automated
analysis/ validation of files
Optical Character
Recognition (OCR) tool
5
7 Conversational Interfaces
• a computer program designed to simulate human
conversation, or chat, with a human user.
11. A simple system to demonstrate the functionality of
a small set of principles, used to prove out the
feasibility of a process use case.
Typically does not involve interfacing with
production systems and has not yet gotten to a
license discussion.
Implementation with end-usage
scenarios, of Production ready quality
but on a smaller scale.
Typically would interface with
production systems and has
secured appropriate licenses. May
or may not drive need for control
room/ orchestration. Typically run
as an attended bot.
Addresses exception handling for
agreed scope.
An early version of a solution with
nearly full functionality, that can be
further tested and refined.
Typically does not involve
interfacing with production
systems and has not yet gotten to a
license discussion.
Takes the “happy path” of the
process and not all error handling,
business referrals.
Deployment of the end solution based on
knowledge and feedback gained from the
pilot.
Interfaces with production systems and
has secured appropriate licenses.
As scale is added drives need for control
room/ orchestration conversations.
Can either run as attended BOT or
scheduled via Orchestrator
Addresses exception handling.
Requires Architecture and further
maturation of process controls, reporting,
error handling.
Agreement should be reached on further
scaling and support processes, who will
be controller for production processes. Is
there a Governance, COE framework
Scaling and establishing a broader
automation agenda within can happen in
parallel
Automation Delivery
PoC
Pilot
Production
Our delivery teams can work through different stages
to Production. The outputs vary in terms of maturity
and discussion is required to ensure expectations
match.
11
PoV
12. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Sample growth runway
12
ClientPwC Client Client Client Client Client
Wave 2
‘Do One’
Wave 3+
‘Lead One’
PwC Led
• Client project team identified and trained in approach
• Client project team is coached by the PwC team 0n
delivery
Client led with PwC Support
• Wave 1 Client project team take on coaching of
middle management
• Additional Client project teams identified and coach at team
level
Lead
Support
PwC
Wave 1 (Pilots)
‘See One’
Client
PwC
Client Client
Completely Client led
• Completely led by Client project team
• Quality review and maturity assessment conducted by PwC
Wave 3 responsibilities Time
PwC coach External quality review and maturity
assessment
25%
Client change
agent
Drives change across business teams 100%
Client team
manager
Leads the Client team to drive
implementation
100%
Client team
staff
Implement learnings from Wave 1 and 2
to engage with stakeholders and drive
programme delivery
100%
Wave 2 responsibilities Time
PwC coach Provides support as required to the
Client project team
50%
Client change
agent
Drives change across business teams
with PwC support
100%
Client team
manager
Leads the Client team to drive
implementation with PwC support
100%
Client team
staff
Implement learnings from Wave 1 to
engage with stakeholders and drive
programme delivery
100%
Wave 1 responsibilities Time
PwC coach Leads program by interfacing with the
Client project team
100%
Client change
agent
Shadows implementation to grow
in-house capability
65-80%
Client team
manager
Works directly with PwC to deliver tools 45-60%
Client team
staff
Experience programme approach and
work with project team to embed in
teams
10-25%
PwC
13. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Some Process Identification learnings
13
1. Focus on what “should” be automated, not what “can” be automated –
maintain a holistic approach focusing first on eliminating waste, re-
engineering processes, and considering use of existing technology.
2. Plug into continuous improvement initiatives – leverage RPA in
conjunction with broader continuous improvement initiatives as opposed to
only thinking about it as a stand-alone project
3. Consider End-to-End processes – avoid focusing narrowly on specific
activities to automate and consider the End-to-End processes
4. Look for value beyond efficiencies – opportunities may be prioritized
based on controls, scalability, or other non-cost factors
5. Proactively manage workforce implications – think about change
management up front
Traditionally organisations think
vertically, delivering change
and operating in isolation.
We see best benefit when you
join the dots by thinking
horizontally and working cross-
functionally.
14. PwC
PwC DAMA; The Good, The Bad and the Data March 2019
Accelerators
14
16. PwC
07/02/2019
16
1
Define and develop a future target state for an
organisation to succeed in a digital age;
Disruption and Innovation, Strategy, People,
Agility, Target Op. Model /TOM, Collaboration.
2
Transform Customer Contact/ interactions to
optimise engagement and experience across
all channels; reduce cost, drive revenue,
service and relationship.
3
Drive efficiencies by digitisation from the front
to back-office; Finance, HR, and Human
interactions, Robotic Automation and
message /voice / chatbot leadership.
Digital Evolution:
Strategy and Innovation
Methodology
Digital Experience:
Data Driven Customer
Transformation
Digital Enterprise:
Developing the Workforce
of the future
Primary
Offerings
Strategy, TOM and Transformation
Innovation, BXT and Design Thinking
Ideation, Portfolio and Program
Prioritisation
Partnering with 3rd party Vendors
Enablers
Architecture for a Digital Age (including cloud)
Digital Maturity and Fitness Assessments
1
2
3
4
13
14
Customer Experience Design
Customer Experience Enablement
Conversion and Funnel Optimisation
Digital Marketing Services
5
6
7
8
Intelligent Automation (RPA, SPA, AI) &
Conversational Agents
Contract Digitisation
Unified Collaboration and Communication
(Teams, Workplace, Hangouts)
HR, CRM, eCommerce, CMS, Spec and
Select
9
10
11
12
Cyber Security & Forensics for a Digital Age15
Behavioural & Customer Analytics & Visualisation (Qlik, Tableau, Google Studio)16
17 Realise, BXT, Digital Fitness UX, CRM, MarTech & AdTech expertise Seal Contract Digitisation, RPA, Chatbots
Value
Statement