This document provides an overview of a presentation by John Owens on the topic of "The DNA of Data Quality". Some key points:
1. John Owens is an international speaker and advisor on topics related to data quality, business transformation, and integrated information management. He has worked with large companies globally.
2. Owens discusses how in the past, before computers, information was seen as the most valuable asset for businesses and was owned and managed by the business functions that utilized it.
3. However, after executives became overwhelmed by computer terminology, they abdicated responsibility for information to IT departments, separating it from business functions - likened to splitting the DNA double helix.
4. Owens argues that
Solving the Wanamaker Problem for Healthcare (keynote file)Tim O'Reilly
Finding a solution to Wanamaker's complaint, "Half of my advertising doesn't work, I just don't know which half" fueled the consumer internet revolution. We are now in the process of finding and solving a similar dilemma in healthcare. I offer some lessons from Silicon Valley for Healthcare
Aiming to eliminate the compromises in organizational life. Covering some interesting and provocative ideas, spanning human rights, complexity science, the death of heuristics, influence flows, personal knowledge mastery, social physics, trust, the digital nervous system, Web 3.0, performance and learning, public relations, collective intelligence, sociocracy, Holacracy, podularity, wirearchy, emergent civilization, self-organization, organized self, socioveillance, middleware corporate, bread incorporated and the Mozilla manifesto.
A dual management operating system to improve digitalisation and automation o...Hendrik Lourens
It is possible to remove the cultural obstacles in trying to achieve success in Digitalisation, Internet of Things
and automation while improving productivity, employee engagement and managing the risks inherent in
change. We need to create a change platform to do this, not launch another change program. By changing
management paradigms, effort can be focussed where it will deliver outsized returns, and bottom-up
improvement becomes possible. This creates the stability from where implementations can be properly
sequenced and involve internal champions who buy into the change.
This talks about knowledge workers, what they look like, what the qualities of knowledge work are, some background in where mass production and scientific management came from, and then ultimately what technology that will support knowledge work will need to look like.
Solving the Wanamaker Problem for Healthcare (keynote file)Tim O'Reilly
Finding a solution to Wanamaker's complaint, "Half of my advertising doesn't work, I just don't know which half" fueled the consumer internet revolution. We are now in the process of finding and solving a similar dilemma in healthcare. I offer some lessons from Silicon Valley for Healthcare
Aiming to eliminate the compromises in organizational life. Covering some interesting and provocative ideas, spanning human rights, complexity science, the death of heuristics, influence flows, personal knowledge mastery, social physics, trust, the digital nervous system, Web 3.0, performance and learning, public relations, collective intelligence, sociocracy, Holacracy, podularity, wirearchy, emergent civilization, self-organization, organized self, socioveillance, middleware corporate, bread incorporated and the Mozilla manifesto.
A dual management operating system to improve digitalisation and automation o...Hendrik Lourens
It is possible to remove the cultural obstacles in trying to achieve success in Digitalisation, Internet of Things
and automation while improving productivity, employee engagement and managing the risks inherent in
change. We need to create a change platform to do this, not launch another change program. By changing
management paradigms, effort can be focussed where it will deliver outsized returns, and bottom-up
improvement becomes possible. This creates the stability from where implementations can be properly
sequenced and involve internal champions who buy into the change.
This talks about knowledge workers, what they look like, what the qualities of knowledge work are, some background in where mass production and scientific management came from, and then ultimately what technology that will support knowledge work will need to look like.
From Microfilm to Big Data - How Can One Brain Handle This Much Change Withou...John Mancini
How is Digital Disruption changing the role of Information in our organizations? How do we shift the focus from the "T"(technology) in IT to the "I" (information)?
The Now and Next of Learning and TechnologyDavid Kelly
These slides were used in support of a talk I deliver at conferences and events..
If you're interested in bringing this talk/workshop into your event or organization, please contact me at LnDDave@gmail.com.
Enhancing knowledge flows with enterprise social networks gordon vala webbGordon Vala-Webb
Organizations need to adapt faster - and that depends on the speed at which ideas and information flow through it. We look at Adrian Bejan's Design in Nature and his approach to knowledge flows and apply that thinking to email and enterprise social networks within organizations.
The nature of the knowledge work problem is growing faster than the capabilities of effective solutions for it. A few of the key problems faced by businesses over the next decade will involve the social contracts with their employees and partners as the adaptability and flexibility enabled by technology become requirements, not opportunities. How do businesses capture the critical tacit knowledge of their older employees as they retire? How do businesses enable new employees to be productive in different ways with new technologies and the skills that come with them? Much of what we know about today will not be relevant in 10 years.
In this presentation, Mark Bernstein shares research done on the Knowledge Work 2020 topic in a collaboration between PARC and Xerox Innovation Group researchers (in Canada, France, and New York). Findings point to more intelligent systems operating on information supporting humans engaged in complex tasks that require knowledge to make decisions; more use of collaborative and social technologies to mediate the time and space problem of distributed and even asynchronous work around the globe; and much more networked computation operating in the world at large.
What does a digital workplace look like? (Keynote presentation from IKO confe...James Robertson
The Innovations in Knowledge Organisation (IKO) conference in Singapore brought together a wide range of practitioners to explore practical solutions. This closing keynote by James Robertson from Step Two shared key definitions, themes from the conference and practical examples.
Digital employee experience (DEX) is a powerful concept that mirrors customer experience. Still new in the marketplace of ideas, it's already having an impact around the globe. Closing keynote at DEX 2019 (Sydney) by James Robertson, Founder, Step Two.
Social licence and digitisation require new thinking aus imm bulletinHendrik Lourens
Mining has become a complex adaptive system and is at a crossroads. The unexpected emergence of new things and relationships means ‘the
whole is greater than the sum of its parts’. In the Ecology Age, confusing dilemmas, ambiguous paradoxes and diverse con
The future of work is about more than technology. It’s about employees, managers, the company, and technology. This presentation takes a look at all of these areas from the past and compares them to what the future should and will look like. Leaders at organizations around the world are exploring how the changes in behavior and technology are impacting the way we work and this provides some context around those changes. Chess Media Group works with and has relationships with some of the world’s largest and most forward thinking companies. This presentation is based on observations and discussions with those companies.
DEX: the way ahead (keynote at IntraTeam Event in Copenhagen, March 2020)James Robertson
Digital employee experience (DEX) is providing a strategic approach to delivering a better experience for staff, beyond just providing new tools. This keynote by James Robertson shares the story so far, the current state of DEX, and the way ahead.
Seminar about the project "IonGAP: an integrated Genome Analysis Platform for Ion Torrent sequence data", presented at the University of Westminster, London, in October 2015.
From Microfilm to Big Data - How Can One Brain Handle This Much Change Withou...John Mancini
How is Digital Disruption changing the role of Information in our organizations? How do we shift the focus from the "T"(technology) in IT to the "I" (information)?
The Now and Next of Learning and TechnologyDavid Kelly
These slides were used in support of a talk I deliver at conferences and events..
If you're interested in bringing this talk/workshop into your event or organization, please contact me at LnDDave@gmail.com.
Enhancing knowledge flows with enterprise social networks gordon vala webbGordon Vala-Webb
Organizations need to adapt faster - and that depends on the speed at which ideas and information flow through it. We look at Adrian Bejan's Design in Nature and his approach to knowledge flows and apply that thinking to email and enterprise social networks within organizations.
The nature of the knowledge work problem is growing faster than the capabilities of effective solutions for it. A few of the key problems faced by businesses over the next decade will involve the social contracts with their employees and partners as the adaptability and flexibility enabled by technology become requirements, not opportunities. How do businesses capture the critical tacit knowledge of their older employees as they retire? How do businesses enable new employees to be productive in different ways with new technologies and the skills that come with them? Much of what we know about today will not be relevant in 10 years.
In this presentation, Mark Bernstein shares research done on the Knowledge Work 2020 topic in a collaboration between PARC and Xerox Innovation Group researchers (in Canada, France, and New York). Findings point to more intelligent systems operating on information supporting humans engaged in complex tasks that require knowledge to make decisions; more use of collaborative and social technologies to mediate the time and space problem of distributed and even asynchronous work around the globe; and much more networked computation operating in the world at large.
What does a digital workplace look like? (Keynote presentation from IKO confe...James Robertson
The Innovations in Knowledge Organisation (IKO) conference in Singapore brought together a wide range of practitioners to explore practical solutions. This closing keynote by James Robertson from Step Two shared key definitions, themes from the conference and practical examples.
Digital employee experience (DEX) is a powerful concept that mirrors customer experience. Still new in the marketplace of ideas, it's already having an impact around the globe. Closing keynote at DEX 2019 (Sydney) by James Robertson, Founder, Step Two.
Social licence and digitisation require new thinking aus imm bulletinHendrik Lourens
Mining has become a complex adaptive system and is at a crossroads. The unexpected emergence of new things and relationships means ‘the
whole is greater than the sum of its parts’. In the Ecology Age, confusing dilemmas, ambiguous paradoxes and diverse con
The future of work is about more than technology. It’s about employees, managers, the company, and technology. This presentation takes a look at all of these areas from the past and compares them to what the future should and will look like. Leaders at organizations around the world are exploring how the changes in behavior and technology are impacting the way we work and this provides some context around those changes. Chess Media Group works with and has relationships with some of the world’s largest and most forward thinking companies. This presentation is based on observations and discussions with those companies.
DEX: the way ahead (keynote at IntraTeam Event in Copenhagen, March 2020)James Robertson
Digital employee experience (DEX) is providing a strategic approach to delivering a better experience for staff, beyond just providing new tools. This keynote by James Robertson shares the story so far, the current state of DEX, and the way ahead.
Seminar about the project "IonGAP: an integrated Genome Analysis Platform for Ion Torrent sequence data", presented at the University of Westminster, London, in October 2015.
Case Study in Linked Data and Semantic Web: Human GenomeDavid Portnoy
The National Human Genome Research Institute's "GWAS Catalog" (Genome-Wide Association Studies) project is a successful implementation of Linked Data (http://linkeddata.org/) and Semantic Web (http://www.w3.org/standards/semanticweb/) concepts. This deck discusses how this project has been implemented, challenges faced and possible paths for the future.
IonGAP - an Integrated Genome Assembly Platform for Ion Torrent DataAdrian Baez-Ortega
http://iongap.hpc.iter.es
Computer Engineer Degree Final Project.
Universidad de La Laguna, Spain, July 2014.
Ion Torrent technology allows genome sequencing with reduced costs; however, its major drawback is the lack of tools dedicated to processing and assembling Ion Torrent reads.
IonGAP is a free graphical integrated pipeline designed for the assembly and subsequent analysis of Ion Torrent sequencing data. Both its components and their configuration are based on a research process aimed to discover the optimal combination of tools for obtaining good results from single-end reads generated by the Ion Torrent PGM sequencer, mainly from bacterial genomic material.
JF Gauthier, CEO of Startup Genome, on Global Startup Ecosystem Development. Presented at the Global Entrepreneurship Congress in Johannesburg, South Africa.
Igor Oliveira, partner at Semente, on Early-Stage Investing in Latin America.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Hedda Pahlson-Moller, business angel and impact investor, on the Impact Imperative and True Value Creation.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
From the World Bank Group on Innovation + Entrepreneurship: Drivers of Inclusive and Sustainable Growth.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Tomi Davies, president of the African Business Angel Network, on the African Business Angel.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Kalsoon Lakhani, founder and CEO of Invest 2 Innovate.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Nicolas Rouhana, general manager at IM Capital, on the "Seeders" of Lebanon.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Claire Munck, co-chair of the Global Business Angels Network, on the latest updates from GBAN.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Candace Johnson, co-chair of the Global Business Angels Network, on Making Global Impact Through Transformational Entrepreneurship, Innovation and Investment.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Presentation from the "Demystifying Big Data" Technical Conference (Universidad de La Laguna, Spain, June 2014).
Biomedical sciences rely on massive data sets. By using machines capable of generating large amounts of data with low cost, science has entered the 'Big Data' era, making computational infrastructures essential to maintain, transfer and analyze all this information.
Craig Mullett, president at Branison Group, on Angel Investing: An Overview.
Presentation delivered at the Global Entrepreneurship Congress in Johannesburg, South Africa (March 2017).
Genome Analysis Pipelines, Big Data Style
Allen Day, Chief Scientist, MapR
Powerful new tools exist for processing large volumes of data quickly across a cluster of networked computers. Typical bioinformatics workflow requirements are well-matched to these tools' capabilities. However, the tool Spark, for example, is not commonly used because many legacy bioinformatics applications make assumptions about their computing environment. These assumptions present a barrier to integrating the tools into more modern computing environments. Fortunately, these barriers are quickly coming down. In this presentation, we'll examine a few operations common to many bioinformatics pipelines, show how they were usually implemented in the past, and how they're being re-implemented right now to save time, money, and make new types of analysis possible. Some code examples will also be provided.
Video Presentation:
https://youtu.be/iwgfjHiHr7Q
Third presentation in our seminar on business intelligence dashboards. Derek Murphy works for National Grid and related learning points from over 30 years experience of delivering business intelligence projects
Presentation also available on YouTube https://www.youtube.com/watch?v=Er90qIA2S7U
The Fragmented Enterprise: ECM in the Era of Social Business.AIIM International
The traditional organizational structure of workers sat at desktops, connecting to a business application protected by a firewall is rapidly eroding. In a short period of time we have gone from a wired and bound world, to an unwired "internet in the pocket" world. Driven by the power of the cloud and the crowd, enterprise technology is experiencing innovation at an unparalleled pace with no sign of things slowing down. In this keynote session we will look at what this new digital infrastructure enables, both the positive opportunities for truly social business to emerge alongside the challenges and serious unresolved issues it also raises.
Developing people in a time of digital disruptionJuan Chamorro
La Dra. Jennifer Jordan, Profesora de Liderazgo y Comportamiento Organizacional en la escuela IMD, describe en este artículo las oportunidades y los desafíos que presenta la gestión de personas en la era digital.
El artículo completo, en el que participan Anouk Lavoie Orlick, Lindsay McTeague y Pascal Wicht (fundador de Whispers & Giants), puede leerse en el siguiente enlace:
https://lnkd.in/erbMTiJ
Rasgos y perfiles de los profesionales, enfoques ágiles basados en la tecnología y los comportamientos de algunas de las audiencias de una organización, forman parte del completo análisis reflejado en este artículo. Resulta de interés, por ejemplo, la actitud de los millennials hacia la tecnología, con una relación de afinidad natural con herramientas basadas en la nube, el móvil, o su consideración de la IT corporativa como poco intuitiva y compleja. A medida que se implantan nuevos sistemas , se debe recordar a los Millennials la necesidad de mantener la confidencialidad de los datos, ya que sus conceptos de privacidad difieren de los de las generaciones anteriores.
Information is at the heart of all architecture disciplines & why Conceptual ...Christopher Bradley
Information is at the heart of all of the architecture disciplines such as Business Architecture, Applications Architecture and Conceptual Data Modelling helps this.
Also, data modelling which helps inform this has been wrongly taught as being just for Database design in many Universities.
chris.bradley@dmadvisors.co.uk
Data come from everywhere and everyone, but we need to be able to analyze them in a way to improve performances
Companies need to work faster but they also have to use those data to anticipate and innovate
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
For over four decades, IT strategy has been about the alignment of technology with the needs of the “customer,” be it an organization, business, end user, or device. The most important part of system acquisition is deciding what to build or buy, as it is better to deliver no solution at all than it is to deliver the wrong solution. But there are two distinct dimensions to getting requirements and ensuring that they, and the IT solution that results, not only aligns with the business as it is, but is built in such a way that it can sustain that alignment in a cost-effective and time-efficient manner. Specifically, (1) narrow requirements, which focus on the short-term needs for specific parts, functions, or processes of the business; and, (2) broad requirements, which focus on a comprehensive, enterprise-wide approach with holistic and longer-range objectives like simplicity, suppleness, and total cost of ownership. We typically call these “Systems Analysis and Design” and “Enterprise Architecture” respectively. Ideally, organizations should be able to do both well, and effectively balance the inevitable tradeoffs between them. Sadly, in the vast majority of organizations, that is not yet the case.
Professor Kappelman will present the results of a ground-breaking study from the Society for Information Management (SIM) Enterprise Architecture Working Group that developed and validated measures for these two distinct types of requirements capabilities. Findings include:
• Empirical validation that there is, in fact, a difference between requirement capabilities in a narrow or individual system context (i.e., Systems Analysis and Design within the bounds of a specific development project), and requirements capabilities in a broad or enterprise context (i.e., Enterprise Architecture regarding how those individual systems fit together in an enterprise-wide strategic design).
• Strong evidence that requirements capabilities overall are immature, with narrow activities more mature than the corresponding broad enterprise capabilities.
• Solid evidence, based on fifteen years of studies, that software development capabilities are generally maturing, but are still fairly immature.
This research provides requirements engineers, software designers, software developers, and other IT practitioners with tools to assess their own requirements engineering and software development capabilities. and compare them with those of their peers. Suggestions for improvements are made.
A sample of my book "Business unIntelligence - Insight and Innovation beyond Analytics and Big Data", published by Technics Publications, 2013.
Chapter 5 shows the evolution of the Data Warehouse architecture and provides a description of some aspects of a modern Information architecture.
The book can be ordered in hard and softcopy formats at http://bit.ly/BunI-TP1
BIG DATA is having an enormous impact on the profile of workforces around the world. If you've ever seen the technology and experienced the impact it has on the pace of innovation in a business then the predictations made by McKinsey Global Institute will come as no surprise ( and just in case you've been on holiday for around two years, McKinsey is suggesting that by 2018 the US will face a shortfall of close to 200,000 analysts and 1.5 million managers with the right skills. In this presentation I outline the impact of BIG DATA on workforce design. I hope you find it informative and fun to read. Ian.
Intersection18: Meta & Meet: The Core of your Digital and Physical Workplace ...Intersection Conference
Presented at Intersection18 Conference - intersectionconf.com
This session focuses on the necessary unifying basic infrastructure for the company that you are designing. We provide cases and theory of what's possible through a unifying digital workplace that has a huge potential to connect people, information and things.
The cases that we show are practices from the Flemish Green Party, the Port of Antwerp Authority and some other Belgian organisations that have started their search for more unifying digital workplaces, and that I support as an employee and freelancer.
Organisations, corporations, companies have the mission to be ONE: one group of people gathering around one mission and goal. And to achieve that goal, they start a never-ending process of organising things, information and people.
But the traditional hierarchical, waterfall-type, unifying mechanisms fail today. The VUCA world makes it much harder than it used to be. Volatility, complexity, ambiguity, uncertainty force every member of the organisation to be a sensor and an agent connecting and dynamizing inner and outer networks. But is our organisation built for this information-model?
Similar to The DNA of Data Quality and the Data Genome (20)
Show drafts
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
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.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. Slide 2
About John Owens
I am an international speaker, advisor, coach, mentor and writer on rapid
business transformation, data quality and MDM.
I am the creator of IMM the Integrated Modelling Method, on which I
have written a series of five books, which have sold in 16 countries.
My regular blog articles are read in as many as 150 different countries.
I have worked with some of largest enterprises in a wide range of
sectors on both sides of the globe, including such names as Oracle, Shell,
BP, British Gas, NAM, London Underground, etc.
It was at NAM that my colleague Nicholas Hann and I built the first 'cradle to grave'
business model for the E&P Industry. The models we produced were later adopted by
Shell and have become something of an industry ‘standard’.
3. Slide 3
About John Owens
I am also a practicing consultant and in this role I work with two main
sets of enterprises.
The first set are those who are suffering the pains and losses caused
by complexity or fragmentation in structure, process, systems or data.
I help them to remove this pain and loss by enabling them to achieve
what I call "power through accelerated integrated simplicity", using
my innovative approach and highly effective techniques.
The second set are those who are already performing well, but who want to raise
their game to a whole new level. My unique insights and highly tuned techniques
enable these enterprises to excel.
4. Slide 4
“Data Quality is an indicator not a driver.
It is an indicator of how well or how badly
the enterprise is performing its core
activities – its Business Functions.”
Some of My Quotes
5. Slide 5
“Data has no intrinsic value.
It is only of value if it supports the
effective execution of the
Business Functions of the enterprise.”
Some of My Quotes
6. Slide 6
“Why spend time and money creating
data errors and then more time and
money trying to find and correct them?
Why not just get it right first time?”
Some of My Quotes
7. Slide 7
“Data is what you need to do analytics.
Information is what you need to do
business.”
Some of My Quotes
8. Slide 8
NAM Information Atlas
Over a period of fourteen months Nick Hann and I mapped all of the Business
Functions and Information Flows across every department of NAM.
This involved interviewing 127 people, ranging from senior executives to on-site
'doers’, from every organisational unit in the enterprise, in locations including
Assen, Gronigen, Den Helder, Schoonebeek, etc.
The outcome of the project was that NAM had a complete and comprehensive
model of everything it did and the information that it needed to do it. This model
comprised a complete set of a Business Function Models (BFMs), one for every
operational area of the business (e.g. exploration, drilling, work overs, etc.) plus
information flow diagrams for every bottom level function in each BFM.
It was, at that time (and may still be), the most comprehensive modelling of an Oil
& Gas E&P enterprise that had ever been done.
9. Slide 9
NAM Learnings
• The power of the Function Model as the backbone of
every enterprise and of all other business models.
• The difference between data and information.
• That information must be ‘pulled’ not ‘pushed’.
• The power of patterns in highlighting similarities and
differences.
• How modelling ‘what’ instead of ‘how’ overcomes the
‘illusion of constant change’.
13. Slide 13
An Historic Perspective
Our current perceived ‘data’ problems did not always
exist.
To understand where they began we need to take a look
back in time.
We actually need to look back to the era BC.
14. Slide 14
For thousands of years business men and women across the world
new that high quality INFORMATION was invaluable to them.
Information about their products, markets, customers,
competitors, etc.
Information was the most valuable asset they possessed as,
without it, they could not capitalise on their other assets.
The Historic Time BC
Before Computers
16. Slide 16
As enterprises grew in size the 19th
century, information began to be
handled in a more organised fashion.
Organised Commerce 19th Centruy
But the business
still owned this
information.
17. Slide 17
Until the commercial computer came along information very obviously
belonged to and in the business.
Although an enterprise might have had rooms full of clerks writing in
ledgers, nobody ever imagined that the information they were collecting
and collating belonged to them.
Where does information ownership lie?
18. Slide 18
Even in the very early days of computerisation nobody would
ever have considered that responsibility for and ownership of
information was not in the business.
Early Computerisation
So, what
went wrong
and when?
19. Slide 19
Quiz Question!
Do you know what the first computer related virus was?
• It first struck some time in the 1980s
• Its spread was global
• Most enterprises are still infected today
• It never infected a single computer
20. Slide 20
Quiz Question!
Do you know what the first computer related virus was?
• It first struck some time in the 1980s
• Its spread was global
• Most enterprises are still infected today
• It never infected a single computer
• It did infect almost every C-Level Executive
• It is known as the Boggled Boss virus
21. Slide 21
Boggled Boss Symptoms
Infected executives:
• Became gibbering idiots with regards to computers.
• Lost all common sense & judgement in this area.
• Defered to anyone who could even spell ‘computer’.
• Could be made to sweat and feel faint with the use of
terms like bit, byte, data, hexa, mega, etc.
• Acquiesed to any ‘data’ demand by anyone using the
above terms.
22. Slide 22
Although this ‘virus’ might sound comical, it did have
consequences that still seriously effect enterprises:
• The operational side of enterprises lost access to and
control of information, its most valuable asset.
• Function (what the enterprise does) was split from data.
• A phantom ‘data’ enterprise was born inside every
enterprise.
• The concept of information as an enterprise asset was
lost and replaced with the misconception that data is its
equivalent.
Serious Side
23. Slide 23
To get to the root cause of this virus
would require a time machine to
enable us to travel back and stop
executives panicking over bits, bytes
and electronic data!
Is there an alternative?
Root Cause
24. Slide 24
Alternatively, we can do a time-thought
experiment that I call:
Back to the Future
‘Back to the Future’
We take the enterprise back to
where it used to be in order to take
it forward to where it needs to be.
25. Slide 25
How Do We Travel Back?
Information (not data) is the most valuable
asset in any enterprise.
1.
We ‘travel back in time’ by re-establishing four key
principles in the enterprise:
26. Slide 26
How Do We Travel Back?
All information belongs to, and is the
responsibility of, those carrying out the core
Business Functions of the enterprise.
2.
27. Slide 27
How Do We Travel Back?
Ownership and responsibility for information
can NEVER be delegated (much less abdicated)
to another party, though other parties may be
used to assist the owners in the effective
management of enterprise information.
3.
28. Slide 28
How Do We Travel Back?
Function and information are inextricably
linked and must always remain so.
4.
29. Slide 29
How Do We Move Forward?
Once we have re-established these four key
principles in the enterprise we will have taken it to
where it was before viral insanity set in.
In order to move forward into the future,
enterprises will now need to re-learn (some have
never known it) effective Integrated Information
Management.
31. Slide 31
This brings me to the subject of my talk:
The DNA of Data Quality
While watching a TV programme on genetics, I became
fascinated by the power of the DNA double helix and how a
single strand could hold all of the instructions to build a living
entity, be it a mouse, a mammoth or a man.
Shortly after the Programme an image started to form in my
mind and I realised that there is an equally powerful structure in
every enterprise.
There is a double helix that contains all of the instructions to
define every function that an enterprise ought to perform and
the information structures needed to enable it to do so.
It is that double helix structure that is the subject of this talk.
32. Slide 32
The double helix
structure of DNA
epitomizes the core
information structure
that underpins every
effective enterprise.
It shows the two key
elements of information
architecture – Business
Functions and Data
Entities – and how they
are inextricably linked.
You can’t have one
without the other.
The
DNA of Data
33. Slide 33
F
E
Business Function
Data Entity
Business Functions are
the Core Activities of
every enterprise
Business Functions
create, use and transform
all Data Entities
All Data Entities are
created, used and
transformed by Business
Functions
Data Entities are those
things about which the
enterprise needs to
know and hold data for
the effective execution
of Business Functions
34. Slide 34
E Data Entity
Data Entities are only of
value to an enterprise if
they can be used to create
the INFORMATION required
by the Business Functions
35. Slide 35
The Great Abdication Split
After bosses became boggled by bits
and bytes and abdicated responsibility
for information to IT departments, a
great split occurred.
For the first time in history, information
was removed from the heart of the
enterprise.
38. Slide 38
Splitting a Ladder
Splitting Functions from Entities
gives the enterprise as much
stability as a split ladder!
39. Slide 39
F
EEE
EF
F
F
F
F
F
EEE
E E
Functions were chopped
up and let roll all over the
place in the business.
The original role and
significance of Entities
was forgotten.
What Happened Next?
F
F
F
F
F
F
FFF F F
EE
E EE E
EEEEE
E EE
FF F
E
E
FF F F
F
E
40. Slide 40
F
F
F
F
F
F
F
Many Functions were lost and never used again.
What Happened to Functions?
F
F
F
F
F
F
FFF F F
FF F
FF F F
F
Some enterprises, having forgotten about functions,
tried to model processes but, as processes are based
on functions, this was a failure.
How information ought be
created and used became a
mystery.
The enterprise lost its
precious information asset.
41. Slide 41
EEE
E
EEE
E E
The original role and significance of Entities, i.e. that they
form the basis for information for the enterprise, has been
forgotten
Data is now created, updated and deleted in part or in whole
without any explicitly defined purpose.
What Happened to Entities?
EE
E EE E
EEEEE
E EE
E
E
E
IT has come to believe
that data has a value in its
own right and that
‘managing’ it is providing
a valuable service to the
enterprise.
44. Slide 44
Why an Impossible Task?
IT and Data Quality departments do not have the means to
deliver quality data!!!
All data is created in and by
the business.
At best, IT and Data Quality
can clean up dirty data and
put it back into the
unhealthy business.
45. Slide 45
Why an Impossible Task?
IT and Data Quality departments do not have the means to
deliver quality data!!!
All data is created in and by
the business.
At best, IT and Data Quality
can clean up dirty data and
put it back into the
unhealthy business.
I call this “Data Dialysis”.
46. Slide 46
Is Rescue Possible?
Sadly, until IT and all other data
management teams realise and accept that
they have been handed a poison chalice
and that they are fighting a loosing battle,
then no rescue is possible.
If they have the insight to make this
realisation and the courage to accept it,
then a quantum change is possible by
knowing and using the DNA of Data.
47. Slide 47
The DNA of Entities
Let us look more closely at the DNA of Data.
Data Entities have a:
• Fingerprint.
• Structure.
• Usage profile
48. Slide 48
Data Entity ‘Fingerprint’
Character
Date
Integer
Each Data
Entity contains
a unique
fingerprint.
Legend
Mandatory
Optional
Unique Identifier
First Name
Surame
DoB
Gender
Wgt
Hgt
49. Slide 49
Data Entity ‘Fingerprint’
Data Fingerprint Rules:
• The fingerprint of each Data Entity is
unique.
• If two Entities have the same
fingerprint, then they are the same
Entity – even if they are currently called
by different names.
Contractor
First Name
Surame
DoB
Gender
Wgt
Hgt
First Name
Surame
DoB
Gender
Wgt
Hgt
Contractor
Employee
50. Slide 50
Entity Relationships
Few (hardly any) Data Entities in any
enterprise stand in isolation. Nearly every
Entity is related to another Entity in some
way.
It is these relationships that create the
structures to provide all of the information
required by the Business Functions.
I call this integrated structure of entities the
Data Genome.
E
E
E
E
E
E
E
E
EE
51. Slide 51
Data Genome
The Data Genome is the means by which we
can see how all of the Data Entities of the
enterprise are related to each other.
In order to give consistency, robustness and
integrity to the Genome, these relationships
must conform to strict rules and formats. E
EE
E
E
52. Slide 52
Entity Relationship Rules
Every relationship occurs between two Data Entities and
must be defined in terms of:
• Name: Clearly describes and names the relationship.
• Optionality: Is the relationship mandatory or optional?
• Degree: Does the Entity have this relationship with one,
or more than one, occurrence of the Entity at the other
end of the relationship.
NB: All relationships are two-way and must be defined in
both directions.
53. Slide 53
Relationship Drawing Conventions
Relationships must carry all of the information required to
enable all the Business Functions to execute effectively.
Infinity Sign (∞) indicates that 1 occurrence
of Entity 2 can be associated with 1 or more
occurrence of Entity 1.
Broken Bar means that relationship from
Entity 2 to Entity 1 is optional
∞
1
The figure 1 indicates that 1 occurrence of
Entity 1 can be associated with 1 and only 1
occuernce of Entity2.
Solid Bar means that relationship from
Entity 1 to Entity 2 is mandatory
57. Slide 57
Function to Entity Relationships
Business Functions can have up to four different
relationships with Data Entities, which can be Create,
Read, Update and Delete.
Create
Update
Delete
Read
58. Slide 58
Relationship Quality Checks
If a Business Function does not Create, Read, Update or
Delete any Data Entity, then it is NOT a true Business
Function and should be discarded.
If a Data Entity is not Created, Read, Updated or Deleted
by at least one Business Function, then it is not a true
Data Entity and should be discarded.
?
59. Slide 59
How do Functions Use Data?
By zooming in
on any Function
in the Genome
you will be able
to see exactly
how it creates
and transforms
data.
Create
Update
Delete
Read
60. Slide 60
How are Entities Used by Functions?
By zooming in
on any Entity in
the Genome you
will be able to
see exactly how
it is created and
transformed by
Functions.
Create
Update
Delete
Read
61. Slide 61
Should We Ever Delete Data?
Our previous slides showed Business Functions could
delete occurrences of Data Entities.
• Should we allow this to happen?
• In previous times we did this to save space.
• Now storage that is so cheap can we avoid this?
• Sometimes policy or law will dicate that data must be
deleted.
62. Slide 62
Deleting Data
Deleting for Policy
The enterprise might
decide to retain data only
for so long as it is
compelled to by law to
avoid the liability that
incomplete historic
records might place on it
in, e.g. a class action.
Deleting for Legislation
The enterprise has to
delete data to comply with
legislation, even though it
would prefer to keep it for
opertational purposes, e.g.
data about individuals.
63. Slide 63
More on Entity Fingerprint
It is Business Functions that dictate the fingerprint and
profile of Entities in the Genome.
First Name
Surame
DoB
Gender
Wgt
Hgt
The Fingerprint and Profile reflect the data structures
required to generate the information needed to support
Function Logic and Business Rules.
64. Slide 64
Format Reflection(1)
The definition of the Fingerprint and Profile of Data
Entities might seem counter intuitive in that:
• It is the Business Functions that read or use Entities
that dictate their Fingerprint and Profile.
• Business Functions that create Entities have the
Fingerprint and Profile dictated to them.
• This is called “Format Reflection”
First Name
Surame
DoB
Gender
Wgt
Hgt
65. Slide 65
Format Reflection(2)
Diagram showing Format Reflection.
Creating Function Using Function
Format Flow
Data Flow Data Flow
Format Flow
In effect, the Function that uses the data
dictates the structure and format of the
data to the Function that creates it.
66. Slide 66
This brings us to the fundamental rule that drives all data
and information management in every enterprise around
the globe, which is:
Function Defines Data
It is the Business Functions in an enterprise that define the
format and structure of every item of data required by the
enterprise.
This is true for every enterprise of every size in every sector.
67. Slide 67
Function Defines Data Example 1
Example Function: Sell Product to Customer
This Function gives us three Entities: Sale (from the
active verb ‘sell’), Product and Customer and the
relationships between them.
68. Slide 68
Function Defines Data Example 2
Example Function: Analyse Sales by Product by Sales Rep
by Region. This Function gives us four Entities:
Sale, Product, Region and Sales Rep.
69. Slide 69
Pushing Data Quality Upstream
The interface between the Function Genome and the
Data Genome enables us to push Data Quality upstream.
Creating Function Using Function
Format Flow
Data Flow Data Flow
Format Flow
By knowing which Functions CREATE
which data entities we can push the
required format and structure upstream
to them and embed it in them.
70. Slide 70
This is why the DNA
double helix is so apt
in representing the
tight interrelationship
between Functions
and Data.
Business Functions define
the format and structure
of all Data Entities.
The only purpose of Data
Entities is to provide the
information necessary to
support the effective
execution of the Business
Functions.
Function
Defines Data
71. Slide 71
Legacy Systems & Legacy Data
The Function and Data Genomes are essential for
establishing the ‘fitness for purpose’ of legacy systems by
answering questions such as:
“Does the business logic and data usage of the system
modules match the Business Functions?”
“Does the structure of the data in the system tables match
the profile and structures in the Data Genome?”
72. Slide 72
Legacy Systems and Function
The System modules are mapped against the
Function Genome to assess how well they
match in terms of Function Logic and Entity
Usage.
If they are a good match, then the system is
still relevant and viable, if they are not, then
the system ought be retired operationally.
F
M
M
M
M
MF
F
F
F
73. Slide 73
Legacy Data (1)
Legacy system tables and columns are compared to the
Entity Fingerprint and Profile in the Data Genome.
E
EE
E
E
T
T
T
T
T
Entity Profile
in Genome
Data Table Profile
in legacy system.
Match or
mismatch?
TE
E
E
E
T
T
T
System
Tables
compared
to Entity
Fingerprint
74. Slide 74
Legacy Data (2)
The fit between the Genome and the legacy system tables
will tell you how suitable legacy data is in supporting the
needs of enterprise.
E
EE
E
E
T
T
T
T
T Comparing
Profile
First Name
Surame
DoB
Gender
Wgt
Hgt
Middle Name
Surame
DoB
Gender
Wgt
Hgt
First Name
Comparing Fingerprint
75. Slide 75
What happens to an enterprise when it looses sight of its
Business Functions?
Question!
It becomes DysFunctional!
When everyone has to deal with a dysfunctional
enterprise, strange practices begin to emerge to
compensate for the unpredictable behaviour.
76. Slide 76
It’s Official!
DysFunctional Enterprises
Breed Delinquent Data!
Data is created in all sorts of uncoordinated and disjointed
ways in all parts of the enterprise – often without any
clearly stated purpose.
77. Slide 77
What’s The Answer?
Good Parenting!
Every Entity needs a Function as a
‘Parent’!
To tell it who it is, why it’s there and
how to behave!
78. Slide 78
The DNA in
Balance
Functions are now
looking after Entities,
who know their
purpose, their place
and their role.
The enterprise is
back in balance.
80. Slide 80
Are There Any Benefits?
1. Data will be created correctly first time, every time.
2. The purpose of every piece of data created will be
clearly known.
3. The illusion of ‘data re-use’ will disappear.
4. The required format and structure of all entities will
be known by the functions that create them.
5. The functionality and logic to create data correctly
first time can be built into applications.
81. Slide 81
6. The unique identifiers of all entities will be known,
preventing duplicates being created.
7. Data will be in the structure required to provide the
enterprise with the information it requires.
8. Correct data structures will eliminate the need for
complex logic and coding.
9. The use (CRUD) of every item of data will be clearly
known across the enterprise.
Are There Any Benefits?
82. Slide 82
10. The Modelling the ‘what’ of Business Functions will
eliminate the ‘illusion of constant change’.
11. The functionality of all applications, 3rd Party and in-
house, can be mapped to the Function Genome to
establish that they are fit for the enterprise.
12. The data structures of all applications, 3rd Party and
in-house, can be compared to the Data Genome to
ensure that they will support the information needs
of the Business Functions.
Are There Any Benefits?
83. Slide 83
13. Customer service will be greatly improved.
14. Business process will be greatly simplified.
15. Processing time will be shortened.
16. Processing errors will be reduced.
17. Stock outages and shrinkage will be greatly reduced.
18. Delivery errors will be reduced.
19. Staff turnover will be reduced.
20. Training costs will be reduced.
Are There Any Benefits?
84. Slide 84
21. Time to market for new products will be reduced.
22. New channels to market will be easily added.
23. Compliance in all areas will be higher.
24. Revenues will be increased.
25. Operating costs will be reduced.
26. Profits will be increased.
27. The enterprise will be doing what it ought to have
been doing had Business Functions and information
remained at the heart of the enterprise.
Are There Any Benefits?
85. Slide 85
Thank you for your attention
Questions & Answers
Please continue to be
Email: john@jo-international.com
Phone: +64 21 774 785
Skype: johnowensnz