Uploaded bySteven Miller
Where are the data professionals
This document is a keynote presentation about the growing field of data professionals given by Steven Miller at the 2nd EDISON Champions Conference in Madrid, Spain on March 15, 2017. The presentation discusses the rapid growth of data jobs and emerging roles like data scientists, data engineers, and chief data officers. It also examines trends shaping the future like artificial intelligence, the internet of things, and the need for improved data literacy and data-driven decision making across all professions.
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Where are the data professionals
- 1. © 2017 IBMCorporation Where are the data professionals? Keynote for the 2nd EDISON Champions Conference in Madrid Spain Steven Miller March 15th 2017
- 2. © 2017 IBMCorporation2 Fastest Growing Data Job in the US in 2016 Audience Responses Correct Answer: 54%
- 3. © 2017 IBMCorporation3
- 4. © 2017 IBMCorporation4 1 AI and Advanced Machine Learning 2 Intelligent Apps 3 Intelligent Things 4 Virtual and Augmented Reality 5 Digital Twin 6 Blockchain and Distributed Ledgers 7 Conversational System 8 Mesh App & Service Architecture 9 Digital Technology Platforms 10 Adaptive Security Architecture Gartner’s Top 10 Trends Shaping the future – 2017 http://www.gartner.com/newsroom/id/3482617
- 5. © 2017 IBMCorporation5
- 6. © 2017 IBMCorporation6 Tremendous growth of sensors generating data McKinsey - The Internet of Things: Sizing up the opportunity
- 7. © 2017 IBMCorporation7 Sensors in the iPhone 6 front & rear Cameras multi-touch touchscreen display triple microphone GPS Apple M8 motion coprocessor 3-axis gyroscope 3-axis accelerometer digital compass iBeacon proximity sensor ambient light sensor touch ID fingerprint reader barometer connect any sensor w/Bluetooth or headphone jack
- 8. © 2017 IBMCorporation8 Putting Sensors to work in your city IBM Center for Applied Insights
- 9. © 2017 IBMCorporation9 Data & Work
- 10. © 2017 IBMCorporation10 Talent: New cognitive & analytics professions are emerging Data Scientist Data Policy Professional Chief Data Officer Data Engineer Machine Learning Developer Cyber-Physical Systems Engineer
- 11. © 2017 IBMCorporation11 The Citizen Analyst The data driven economy places data in the hands of every professional.
- 12. © 2017 IBMCorporation12
- 13. © 2017 IBMCorporation13
- 14. © 2017 IBMCorporation14 Data Science & Analytics (DSA) Jobs Framework
- 15. © 2017 IBMCorporation15 Defining the DSA Jobs Landscape Inconsistent nomenclature prevents stakeholders from answering key questions. Over 300 core analytical skills were identified, which were used to score occupations based on their level of analytical rigor. Occupation NYC Analytical Score (Q3 2015 – Q2 2016) Data Scientist 100 Data Engineer 97 Biostatistician 96 Data Architect 91 Statistician 90 Top Analytical Occupations in New York
- 16. © 2017 IBMCorporation16 DSA in New York: By the Numbers 231,562 DSA JOBS Number of jobs in the New York area in a 12 month period (2015-2016) 40,462 NEW POSTINGS Number of additional DSA job postings projected in New York in 5 years 45 DAYS Average time to fill a DSA role in New York $97,300 PER ANNUM Average annual salary of a DSA job in New York 83% PERCENT Proportion of jobs in New York requesting experienced workers (3 or more years of experience)
- 17. © 2017 IBMCorporation17 Framework Category Postings Projected 5 Year Growth Estimated Postings in 5 Years Average Time to Fill (days) Average Advertised Salary % Postings requiring MA or higher % Requesting Experienced Workers (3 years or more) All 231,562 17% 272,024 45 $97,300 9% 83% Data-Driven Decision Makers 82,618 17% 96,963 47 $105,672 7% 91%* Functional Analysts 72,472 18% 85,430 41 $83,265 8% 71% Data Systems Developers 51,093 17% 59,837 49 $98,957 5% 87% Data Analysts 11,987 16% 13,860 44 $90,007 8% 76% Data Scientists & Advanced Analysts 7,170 24% 8,890 45 $117,432 46% 79% Analytics Managers 6,222 13% 7,045 44 $126,840 17% 94%* Quantifying the NYC DSA Job Market
- 18. © 2017 IBMCorporation18 Analytical Scores required are HIGHER in NYC than nationally Occupation Analytical Score (National) Analytical Score (New York) Social Science Researcher 74 82 Survey Researcher 71 79 Clinical Data 70 78 Fraud Examiner / Analyst 60 74 Quality Control Systems Managers 50 60 Supply Chain / Logistics Manager 48 56 Human Resources Manager 44 52 Talent Acquisition / Recruiting 43 55 Chief Executive Officer 42 52 Operations Manager / Supervisor 34 48
- 19. © 2017 IBMCorporation19 NYC Analytical Scores for a broad range of occupations Occupation NYC Analytical Score Auditor 55 Accountant 54 Social Media Strategist 51 Recruiter 44 Business Development / Sales Manager 44 Bookkeeper 40 Graphic Designer 40 Audio / Visual Technician 33 Sales Representative 33 Legal Secretary 25
- 20. © 2017 IBMCorporation20
- 21. © 2017 IBMCorporation21 Data Science is a diverse field Human Data Scientist Primary focus is advising the business Make sense of any dataset(s) Apply any form of analytics from descriptive to cognitive Visualization experts Data Storytellers Machine Data Scientist Primary focus is writing advanced algorithms for: Advanced Robotics Self driving cars Recommendation engines Virtual Assistants IBM Watson
- 22. © 2017 IBMCorporation22 The Data Engineer https://www.linkedin.com/job/data-engineer-jobsThe Data Engineer builds the - modern data systems needed by data scientists & developers. - Complex - Scale, often extreme scale - Near-real time performance - Diverse data sources & types - Secure
- 23. © 2017 IBMCorporation23 Engineering ? Data Engineer a trending job title. 62 open positions in Madrid (LinkedIn March 14th) Data Engineers are responsible for building COMPLEX SYSTEMS. But… does the average person hired into one of theses have training in SYSTEMS Engineering? Likely NOT. (Graphic removed pending permission to publish)
- 24. © 2017 IBMCorporation24 What is the best path to creating an engineering DISCIPLINE? Data Systems Engineer Systems Software Sensors & Things Data Database Algorithms Mission Critical Cyber Physical Systems Engineer Systems, not technologies Empowering, not determining Future by Design Design Values as a feature, not a bug (Source: 4th Industrial Revolution Workshop Proceedings)
- 25. © 2017 IBMCorporation25 Data What data could solve this problem? What existing business data is relevant? What can I attach a sensor to? Is there available government open data? Can data be acquired from other sources? Analyze What models & methods can I apply to solve this problem? Descriptive Predictive Prescriptive Cognitive / Machine Learning Visualization / Story telling Operations How to apply to our business? • Create / amend business processes? • Create new businesses? Close existing ones? • Enter new markets? … Design Thinking Communication T-shaped Skills The Data Driven Decision Maker
- 26. © 2017 IBMCorporation26 The Chief Data Officer Chief Data Officers understand how to use data to create strategic opportunities; responsible for organizational data strategy & governance
- 27. © 2017 IBMCorporation27
- 28. © 2017 IBMCorporation28 Growing Demand for Data Policy Skills Data is a core business asset! • Curated • Consistent • High Quality • Protected • Available • Complies • Preserved • Managed Lifecycle
- 29. © 2017 IBMCorporation29 Data literacy Understanding how to use & program computers is not enough in a data driven world. Every profession. Every career is impacted by data, by analytics, by cognitive. Everyone must become data literate.
- 30. © 2017 IBMCorporation30
- 31. © 2017 IBMCorporation31 In the Cognitive Era everyone must be data literate Define problems Wrangle Data Self-Manage Data Choose Methods and Tools Analyze Data Communicate findings Engage in Lifelong Learning
- 32. © 2017 IBMCorporation32
- 33. © 2017 IBMCorporation33
- 34. © 2017 IBMCorporation34 When you think about what a doctor does every day: they gather evidence about a patient they form a set of hypotheses (possible diagnoses) they make a diagnosis and recommend a treatment Can we improve their degree of confidence in the diagnosis and chosen treatment with Cognitive?
- 35. © 2017 IBMCorporation35 • A female patient was initially diagnosed with leukemia • She underwent standard treatment for leukemia BUT… What if the diagnosis was WRONG?
- 36. © 2017 IBMCorporation36 Provides evidence-based suggestions to support oncologists’ decisions by: Combining patient data with massive volumes of medical literature, including journal articles, physicians’ notes, and NCCN guidelines and best practices Ongoing learning from new oncology techniques, treatments, and evidence IBM Watson for Oncology
- 37. © 2017 IBMCorporation37
- 38. © 2017 IBMCorporation38 Reimagining Ethics Education … moving beyond traditional compliance and ethics courses: Building Foundations for Trust & Integrity project recommendations include focusing on: Values & Ethical dilemmas Levering Interactive materials, group-based work and action-learning initiatives https://www.weforum.org/agenda/2017/03/why-we-have-to-reimagine-education-to-fight- corruption
- 39. © 2017 IBMCorporation39
- 40. © 2017 IBMCorporation40 References Dropbox: bit.ly/edison-papers Slideshare: http://bit.ly/WoW2016presentations
- 41. © 2017 IBMCorporation41 http://bit.ly/dataskillsgap @brandsteve
Editor's Notes
- #2 1
- #4 Data is the new oil. Our ability to make use of ALL data anytime anywhere is transforming our world.
- #5 Data plays a key role in every single one of these trends. AI and Advanced Machine Learning Artificial intelligence (AI) and advanced machine learning (ML) are composed of many technologies and techniques (e.g., deep learning, neural networks, natural-language processing [NLP]). The more advanced techniques move beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously. This is what makes smart machines appear "intelligent." "Applied AI and advanced machine learning give rise to a spectrum of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as apps and services (virtual personal assistants [VPAs], smart advisors), said Mr. Cearley. "These implementations will be delivered as a new class of obviously intelligent apps and things as well as provide embedded intelligence for a wide range of mesh devices and existing software and service solutions." Intelligent Apps Intelligent apps such as VPAs perform some of the functions of a human assistant making everyday tasks easier (by prioritizing emails, for example), and its users more effective (by highlighting the most important content and interactions). Other intelligent apps such as virtual customer assistants (VCAs) are more specialized for tasks in areas such as sales and customer service. As such, these intelligent apps have the potential to transform the nature of work and structure of the workplace. "Over the next 10 years, virtually every app, application and service will incorporate some level of AI," said Mr Cearley. "This will form a long-term trend that will continually evolve and expand the application of AI and machine learning for apps and services." Intelligent Things Intelligent things refer to physical things that go beyond the execution of rigid programing models to exploit applied AI and machine learning to deliver advanced behaviors and interact more naturally with their surroundings and with people. As intelligent things, such as drones, autonomous vehicles and smart appliances, permeate the environment, Gartner anticipates a shift from stand-alone intelligent things to a collaborative intelligent things model. Virtual and Augmented Reality Immersive technologies, such as virtual reality (VR) and augmented reality (AR), transform the way individuals interact with one another and with software systems. "The landscape of immersive consumer and business content and applications will evolve dramatically through 2021," said Mr. Cearley. "VR and AR capabilities will merge with the digital mesh to form a more seamless system of devices capable of orchestrating a flow of information that comes to the user as hyperpersonalized and relevant apps and services. Integration across multiple mobile, wearable, Internet of Things (IoT) and sensor-rich environments will extend immersive applications beyond isolated and single-person experiences. Rooms and spaces will become active with things, and their connection through the mesh will appear and work in conjunction with immersive virtual worlds." Digital Twin A digital twin is a dynamic software model of a physical thing or system that relies on sensor data to understand its state, respond to changes, improve operations and add value. Digital twins include a combination of metadata (for example, classification, composition and structure), condition or state (for example, location and temperature), event data (for example, time series), and analytics (for example, algorithms and rules). Within three to five years, hundreds of millions of things will be represented by digital twins. Organizations will use digital twins to proactively repair and plan for equipment service, to plan manufacturing processes, to operate factories, to predict equipment failure or increase operational efficiency, and to perform enhanced product development. As such, digital twins will eventually become proxies for the combination of skilled individuals and traditional monitoring devices and controls (for example, pressure gauges, pressure valves). Blockchain and Distributed Ledgers Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other tokens) are sequentially grouped into blocks. Each block is chained to the previous block and recorded across a peer-to-peer network, using cryptographic trust and assurance mechanisms. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise to transform industry operating models. While the current hype is around the financial services industry, there are many possible applications including music distribution, identity verification, title registry and supply chain. "Distributed ledgers are potentially transformative but most initiatives are still in the early alpha or beta testing stage," said Mr. Cearley. Conversational System The current focus for conversational interfaces is focused on chatbots and microphone-enabled devices (e.g., speakers smartphones, tablets, PCs, automobiles). However, the digital mesh encompasses an expanding set of endpoints people use to access applicatons and information, or interact with people, social communities, governments, and businesses. The device mesh moves beyond the traditional desktop computer and multiple devices to encompass the full range of endpoints with which humans might interact. As the device mesh evolves, connection models will expand and greater cooperative interaction between devices will emerge, creating the foundation for a new continuous and ambient digital experience. Mesh App and Service Architecture In the mesh app and service architecture (MASA), mobile apps, web apps, desktop apps and IoT apps link to a broad mesh of back-end services to create what users view as an "application." The architecture encapsulates services and exposes APIs at multiple levels and across organizational boundaries balancing the demand for agility and scalability of services with composition and reuse of services. The MASA enables users to have an optimized solution for targeted endpoints in the digital mesh (e.g., desktop, smartphone, automobile) as well as a continuous experience as they shift across these different channels. Digital Technology Platforms Digital technology platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business. Gartner has identified the five major focal points to enable the new capabilities and business models of digital business — information systems, customer experience, analytics and intelligence, the IoT, and business ecosystems. Every organization will have some mix of these five digital technology platforms. The platforms provide the basic building blocks for a digital business and are a critical enabler to become a digital business. Adaptive Security Architecture The intelligent digital mesh and related digital technology platforms and application architectures create an ever-more-complex world for security. "Established security technologies should be used as a baseline to secure Internet of Things platforms," said Mr. Cearley. "Monitoring user and entity behavior is a critical addition that is particularly needed in IoT scenarios. However, the IoT edge is a new frontier for many IT security professionals creating new vulnerability areas and often requiring new remediation tools and processes that must be factored into IoT platform efforts."
- #6 This next section provides clear examples of innovating with data.
- #8 https://en.wikipedia.org/wiki/IPhone_6 The Apple iWatch has a heart rate sensor
- #9 Everything can be measured. Cities are actively measuring air quality, water quality, traffic, transit, noise, weather, tides, people, anything that be sensed & measured.
- #10 Data is the new oil. Our ability to make use of ALL data anytime anywhere is transforming our world.
- #12 Every professional needs to become a citizen analyst in the data driven economy
- #13 Everyone needs data literacy. EVERYONE!!! Free stock photo from: https://unsplash.com/collections/164957/crowd?photo=TZCppMjaOHU
- #22 Human data scientists support the business or lines of business helping them understand and make better decisions. Machine data scientists drive the machines that run much of the cognitive world. Michael Li’s article http://data-informed.com/two-types-of-data-scientists-which-is-right-for-your-needs/
- #23 With the data engineer data scientists will accomplish little.
- #26 A business leader needs a comprehensive view of data, analytics, and putting it to work
- #27 http://bit.ly/ibmcdostudy The chief data officer is growing fast… not sure what drove the plunge in Indeed’s data but instead focus on the trend line.
- #28 Graphic published with permission of ThotWave. https://www.thotwave.com/
- #29 Other possible adjectives: Controlled? Pedigreed? Grey Data? Black Data? Version control? The Data Self by Rob Horning http://thenewinquiry.com/blogs/marginal-utility/dumb-bullshit/ http://www.gartner.com/newsroom/id/2506315 “The underlying message of all these examples is that information is an asset in its own right. It has value. Gartner calls this emerging discipline of valuating information "Infonomics.It is not something of the far future, in fact, this is happening today in various industries, in commerce and public sector, in large and small enterprises.” However, Mr. Buytendijk underlined the fact that as exciting as all new business opportunities are, there are also reasons for concern. Concerning the ethics of big data, a recent Gartner Circle study showed that "governance and privacy" was the most important concern around big data – clearly there is a fine line between superior customer insight and being "creepy."
- #32 In partnership with Oceans of Data we brought a group of experts together from industry & academia to define data & analytics literacy. These are the top level recommendations. Michael Bowen Associate Professor, Science Education, Mount Saint Vincent University, Halifax, Nova Scotia Ben Davison Quantitative User Experience Researcher, Google Rob Gould Faculty, UCLA Department of Statistics Ryan Kapaun Crime Analyst, Eden Prairie Police Department Cliff Konold Director, Scientific Reasoning Research Institute, University of Massachusetts, Amherst Juan Miguel Lavista Ferres Principal Data Scientist at Bing/Microsoft Odette Merchant Project Manager, Nova Scotia Community College (NSCC), Halifax, Nova Scotia, Canada Andrew Schaffner Professor of Statistics, California Polytechnic State University, San Luis Obispo Hunter Whitney Consultant, Author, and Instructor; UX and Data Visualization Sponsored by Steven Miller IBM Moderated by the Oceans of Data Team
- #33 Making better decisions requires confidence. Let’s talk about how Watson uses Cognitive to do just that.
- #34 In 2011 Watson competed against Ken Jennings & Brad Rutter. As we have all heard, Watson beat the best players in the world. Watson knew more, could answer faster, and pressed the button only when Watson determined its answer a high degree of confidence, otherwise it didn’t push the button at all. IBM donated the $1M prize to charity.
- #35 When doctors face challenges they face every day.. Their knowledge and experience is easily up to the task. Many problems they see, however are rare, or at least rare for them. What would happen if we applied Watson to one of the greater challenges of our time? Cancer
- #37 NCCN = National Comprehensive Cancer Network This slide is self explanatory. Yes, Watson has proven to be quite adept at helping doctors diagnose and recommend treatment for cancers. Poor diagnoses are a huge burden on the cost of health care and an even bigger burden on the patient. If the correct treatmet is the 3rd or 4th one tried it’s often too late.
- #40 What will you invent?
- #43 42