You have been temporarily restricted. Please be more thoughtful when adding content for your portfolio. Your portfolio and digital media kit and should be reflective of the professional image you wish to convey. Accounts may be temporarily restricted if we receive reports of spamming or if the system detects excessive entries.
Membership
Publish your original ideas on the Thinkers360 platform!
This feature is available for Pro and Pro-Plus Members Only.
Speaker Bureau functionality whereby individuals can be featured speakers within our Speaker Bureau service and enterprises can find and work with speakers.
This feature is available for Pro, Pro-Plus, Premium and Enterprise Members Only.
Highlight your featured products and services within our company directory for enhanced visibility to active B2B buyers worldwide. This feature is available for Pro, Pro Plus, Premium and Enterprise Members Only.
Contribute to the Thinkers360 Member Blog and have your thought leadership featured on our web site, newsletter and social channels. Reach our opt-in B2B thought leader community and influencer marketplace with over 100M followers on social media combined!
You’ve reached your daily limit for entering quotes. Please only add personally-authored content which is reflective of your digital media kit and thought leadership portfolio.
Thinkers360 Content Library
For full access to the Thinkers360 content library, please join ourContent Planor become a contributor by posting your own personally-authored content into the system viaAdd PublicationorImport Publication.
Dashboard
Unlock your personalized dashboard including metrics for your member blogs and press releases as well as all the features and benefits of our member plans!
Interested in getting your own thought leader profile? Get Started Today.
David Sweenor
Founder at TinyTechGuides
South Burlington, United States
David Sweenor is an analytics thought leader, international speaker, author, founder of TinyTechGuides, and has co-developed several patents. David has over 20 years of hands-on business analytics experience spanning product marketing, strategy, product development, and data warehousing. He specializes in artificial intelligence, machine learning, data science, business intelligence, the internet of things (IoT), and manufacturing analytics.
David Sweenor
Points
Academic
15
Author
446
Influencer
54
Speaker
15
Entrepreneur
100
Total
630
Points based upon Thinkers360 patent-pending algorithm.
The Illusion of Control: Generative AI and the CIO's Dilemma
LinkedIn
February 22, 2024
If you’re in the market for a new car, you may want to consider interacting with the dealer's chatbot. One customer was interacting with Chevrolet’s chatbot from a dealer in California, and it recommended the customer buy the rival Ford F-150.[1] In separate interaction, curiously enough, at the same dealership, customers negotiating with the chatbot were able to get the deal of a lifetime on a truck–they were able to persuade the chatbot to offer a hefty $58,000 discount on a new vehicle, lowering its cost to a mere $1.[2] Sadly, this sales price wasn’t honored. These innocuous AI failures highlight the inherent risks in deploying generative AI technologies, but there are countless other examples that are much more serious and damaging.
Future-Proof Your IT: The CIO's Guide to Generative AI Vendor Selection
LinkedIn
February 15, 2024
Did you know that by 2028, approximately 70 percent of businesses will integrate generative AI into their core operations?[1] So, given the prognostication, how prepared is your organization to adapt over the next four years?
Analytics Democratization vs. Governance: Are They at Odds?
Import from medium.com
September 27, 2022
Democratizing Analytics at UBSPhoto Courtesy of UBS Media Kit (https://www.ubs.com/global/en/media/photos/our-locations.html)Well, are they?Are you finding that governance and democratization are at odds in your organization? Are your line-of-business managers slow to adopt analytics in general and
Data use and Ethical Responsibility
Compliance Magazine
September 24, 2022
Big data and the insights that lie hidden within it have become an integral part of the German economy. As a Bitkom survey revealed, the vast majority of companies are already collecting information in order to analyze it and use the results to optimize internal processes and increase business value. At the same time, however, most people overlook the fact that with this success comes a new responsibility.
Democratizing Analytics for Organizational Success
TDWI
September 16, 2022
Data and analytics used to be the province of anyone with a task to complete, so how did it become a field for the specialists only? How can we make it for everyone once again?
The Art of The AI KPI
Import from medium.com
September 12, 2022
Creating a KPI Game Plan“Not everything that can be counted counts and not everything that counts can be counted.” -Albert EinsteinImage Courtesy of Author — David E. SweenorSome say data is the new oil. It’s not, as the World Economic Forum pointed out in 2018. Petroleum is a finite
Crossing the Analytics and AI Chasm
Import from medium.com
September 06, 2022
A Framework for leaders to build out their data and analytics practicesPhoto Courtesy of Author — David E. SweenorA recent study from NewVantage Partners found that 92% of organizations are increasing their investments in data and artificial intelligence (AI). The study goes on to say that on
Scaling cloud analytics: can governance keep pace with the democratisation imperative?
Digitialization World
August 23, 2022
See Page 52.
Cloud is one of the most discussed – and arguably least understood - topics
of the last decade. The move to cloud was the ultimate catch-all term for a
long period of time – something that could deliver health, wealth, happiness,
a better hairline, or even that endearing sports car that caught your eye.
The key myths impeding AI and Machine Learning success – and why there’s no truth in them
The AI Journal
August 22, 2022
Any successful endeavor — from house building to digital transformation — requires the establishment of strong foundational knowledge, and this holds true when trying to unlock AI and produce positive, actionable outcomes. However, many companies battle to get past some of the more common AI myths and misconceptions.
Top 5 Strategies to Future-Proof Analytics, Data Science, and ML Investments
Import from medium.com
August 22, 2022
A Guide for Business Leaders to Maximize Their InvestmentsPhoto by Dominik Scythe on UnsplashWhen COVID-19 struck in early 2020, everyone’s data science and ML models broke. The pandemic fundamentally changed the nature of work and accelerated activities to become data driven.Wow, times have cer
Why So Many Organizations Are Getting AI and Machine Learning Wrong
Import from medium.com
August 17, 2022
The Future Flail of AI: Automating Bad Decisions FasterWaikiki, HI Photo Courtesy of Author — David E SweenorIf you want ROI on your data science investment, you must understand what it can (or can’t) do. Otherwise, you’re throwing time and money away.Artificial intelligence (AI) was sup
The Biggest Challenges When Adopting Data and AI Technologie
InsideBigData
August 16, 2022
With the right technical infrastructure and data-literate work culture, the challenges with the adoption of data science and machine learning technologies can be easily addressed.
Data Analytics - Here's How SMEs Can Get on Board Now
BigData-Insider
August 16, 2022
Every business has vast amounts of data at its disposal, and the midmarket is no exception. Every human being already generates an average of more than one gigabyte a day, and the trend is rising. According to statistics, however, only two percent of the data generated is actually saved. This means that their great potential for processing and analysis for new insights is lost. But even when information stays in the system, it's often hidden in spreadsheets that are difficult to analyze.
Data Ethics - Here's How SMEs Can Get on Board Now
IT-Business
August 15, 2022
Every company has huge amounts of data - even in medium-sized companies. According to statistics, however, only two percent of the data generated is actually saved. This means that their great potential for processing and analysis for new insights is lost.
Why Data Ethics Leadership Needs to Become the New Normal in Finance
Global Banking and Finance Review
August 13, 2022
If data is the fuel needed to drive modern business insights, then AI is the turbo engine that powers this process – delivering new solutions and insights far faster than previously possible. Conversely, however, using AI automation at this scale without a data ethics leader in such a highly regulated environment is the equivalent to starting a road trip with no map, no sense of direction, nor an ability to adjust course to get back on track.
Artificial intelligence and data ethics: Four tips on how companies can reconcile the two
All About Security
August 10, 2022
Algorithms influence our lives: they personalize recommendations for our music and television consumption, recognize fraudulent online orders and decide who is invited to an interview. The use of AI models has grown rapidly over the past 20 years, going as far as being used for mortgages, financial applications, and even targeted advertising. But what can companies do to ensure their AI projects are ethical?
Five myths about artificial intelligence and machine learning
Computer Weekly
May 06, 2022
There are a number of myths surrounding artificial intelligence and machine learning. Those responsible should be aware of these points in order to lead AI and ML projects to success.
The biggest misconceptions about artificial intelligence
IT Daily
March 12, 2022
79 percent of companies in Germany expect that artificial intelligence (AI) will noticeably change our economy and society - and not at some point, but already in the course of this decade.
Accelerate Digital Transformation with Automated Analytics
Import from medium.com
March 05, 2022
Photo by David E Sweenor. ‘Iao ValleyAutomated analytics is the fuel for your organization’s growth, keeping it relevant, agile, and one step ahead of your competitors.Change is inevitable, change is constant, and for business, change can be scary. However, rather than hide from this eventualit
The Case for a Global Responsible AI Framework
Import from medium.com
February 23, 2022
A Global AI Framework is NeededThe design and use of artificial intelligence is proving to be an ethical dilemma for companies throughout the United States considering its implementation. While currently only 6% of companies have embraced AI-powered solutions across their business, according to a s
The Case for a Global Responsible AI Framework
KDNuggets
October 30, 2021
Framework
Public and private organizations have come out with their own set of AI principles, focusing on AI-related risks from their perspective. However, it’s imperative d=to have a global consensus on Responsible AI – based on data governance, transparency and accountability – on how to utilize and benefit from AI in a way that is both consistent and ethical.
Generative AI Business Applications: An Executive Guide with Real-Live Examples and Case Studies
TinyTechMedia LLC
February 01, 2024
Within the past year, generative AI has broken barriers and transformed how we think about what computers are truly capable of. But, with the marketing hype and generative AI washing of content, it’s increasingly difficult for business leaders and practitioners to go beyond the art of the possible and answer that critical question–how is generative AI actually being used in organizations?
With over 70 real-world case studies and applications across 12 different industries and 11 departments, Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies fills a critical knowledge gap for business leaders and practitioners by providing examples of generative AI in action. Diving into the case studies, this TinyTechGuide discusses AI risks, implementation considerations, generative AI operations, AI ethics, and trustworthy AI.
The world is transforming before our very eyes. Don’t get left behind—while understanding the powers and perils of generative AI. Full of use cases and real-world applications, this book is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI’s transformative power.Gain a competitive edge in today’s marketplace with Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies. Remember, it’s not the tech that’s tiny, just the book!
The CIO’s Guide to Adopting Generative AI: Five Keys to Success
TinyTechMedia
October 24, 2023
In a world full of generative AI hoopla, it's easy to get lost in the maze of options and marketing hype. Don't get distracted by the vendor hype; instead, focus on building resilient, high-value platforms that will set you apart from the competition. The CIO’s Guide to Adopting Generative AI: Five Keys to Successfills a critical knowledge gap for CIOs and business leaders by succinctly offering five success factors that need to be met before an organization can successfully incorporate generative AI.
To unlock the transformative business value of generative AI, business leaders must: 1) identify enterprise use cases, 2) apply context to large language models (LLMs) using their organization's data, 3) take special precautions to ensure data security and privacy, 4) implement an artificial intelligence (AI) governance framework, and 5) build manageable AI applications for business users. This report provides the keys to unlocking the true potential of generative AI.
Full of use cases and real-world applications, this report is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI's transformative power.
Gain a competitive edge in today's marketplace with The CIO’s Guide to Adopting Generative AI: Five Keys to Success. Remember, it's not the tech that's tiny, it's the book!
Artificial Intelligence: An Executive Guide to Make AI Work for Your Business
TinyTechMedia LLC
April 02, 2022
In the business world, the very term artificial intelligence (AI) is shrouded in mystery. For some, it’s the brains behind a robotic apocalypse. For others, it provides hope for a better society with self-driving cars, food security, and medical breakthroughs. But what about for businesses? For most executives , the term “AI” is vague, confusing, and although intriguing, it seems unapproachable.
Artificial Intelligence: An Executive Guide to Make AI Work for Your Business is designed for non-experts—it’s for business teams, business leaders, and executives who never seem to have enough time in the day to learn about the latest technology trends. TinyTechGuides are meant to be read in under two hours and focus on the application of technologies in business, government, and educational settings.
This book covers the fundamentals of AI: data, analytic, and automation technologies—from modern data management techniques to chatbots, machine learning, natural language processing (NLP), robotic process automation (RPA), and computer vision. It discusses the business benefits of AI, the importance of AI ethics, MLOps, and provides real steps on how to start your AI journey.
With real-world examples of businesses applying AI, you’ll learn how to use AI within Accounting & Finance, Marketing & Sales, Research & Development, Supply Chain, IT, Human Resources, and Service and Support. There are practical industry examples across Banking & Finance, Energy & Utilities, Insurance, Government, Healthcare, Life Sciences, Manufacturing, Retail, Telecom, and Transportation & Logistics.
If you want to know how AI can be applied to improve your business, this TinyTechGuide is for you! Remember, It’s not the tech that’s tiny, just the book!
It's All Analytics – Part II: Designing an Integrated AI, Analytics, and Data Science Architecture for Your Organization
Routledge, Taylor and Francis Group
September 29, 2021
Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It’s All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful.
TinyTechMedia, the makers of TinyTechGuides. TinyTechGuides are designed for non-experts — they’re designed for business teams, business leaders, and executives who never seem to have enough time in the day to learn about the latest technology trends. They are designed to be read in an hour or two and focus on the application of technologies in a business, government, or educational institution.
THE USE OF POLYNOMIAL NEURAL NETWORKS IN PREDICTING SURVIVAL OF SWINE IN HEMORRHAGIC SHOCK
Telemedicine Journal
July 01, 2004
The first 20 to 30 minutes after an injury is the time window faced by the Army medic within which triage and rescue decisions must be made. In the battlefield setting, roughly 20% of mortalities occur before injured soldiers can he transported to the Battle Aid Station (BAS). After arriving at the BAS, mortality rates fall to about 3%. This research addresses the utility of polynomial neural network (PNN) models in predicting mortality during hemorrhagic shock (HS) for use in trauma triage. Data from over 100 swine were acquired from two HS experimental protocols. Swine in the first group had HS induced through a Grade V liver injury, whereas those in the second group received an aortotomy. Four time-stamped physiological variables were measured: systolic and diastolic blood pressure, mean arterial pressure, and heart rate. Sampled every 10 seconds, these data will be used to predict mortality one hour after injury. The hypothesis is that the PNN models will be able to learn effectively the dynamic characteristics of HS data and will be an effective aid in mortality prediction for trauma triage.
The use of polynomial neural networks for mortality prediction in uncontrolled venous and arterial hemorrhage
Journal of Trauma
January 01, 2002
The ability to rapidly and accurately triage, evacuate, and utilize appropriate interventions can be problematic in the early decision-making process of trauma care. With current methods of prehospital data collection and analysis, decisions are often based upon single data points. This information may be insufficient for reliable decision-making. To date, no studies have attempted to utilize data at multiple time points for purposes of enhancing prediction, nor have studies attempted to synthesize prediction models with data reflecting both large-vessel venous and arterial injuries. Therefore, we performed a retrospective study to examine the potential utility of dynamic neural networks in predicting mortality using highly discretized uncontrolled hemorrhagic shock data.
On defining the optical gap of an amorphous semiconductor: an empirical calibration for the case of hydrogenated amorphous silicon
Solid State Communications
April 08, 1999
It is pointed out that there are a number of different means whereby the optical gap of an amorphous semiconductor may be defined. We analyze some hydrogenated amorphous silicon data with respect to a number of these empirical measures for the optical gap. By plotting these gap measures as a function of the breadth of the optical absorption tail, we provide a means of relating these disparate measures of the optical gap.
Escaping operational black holes with unified ‘full-fidelity’ observability
IDG Connect
June 26, 2022
As tech leaders now look to gain deep and granular tranches of management control across their IT estates, there is a reasonable (if not compelling) argument for questioning the form, focus and fidelity of our observability viewpoint – the alternative may be something like a journey down an operational black hole, which is clearly a fairly suffocating experience for everyone.
A new recipe for enterprise data, 'too many cooks' is over
IDC Connect
January 20, 2022
The adage 'too many cooks' might still apply in the soup kitchen, but in cloud-centric data analytics, there is an argument for more ingredients (data sources), more cooks (data scientists) and more servings all round.
Getting Started with Data Science as an SMB
EM360
July 09, 2021
science is out of their reach because they can’t afford to hire an expensive data analyst. In fact, Michael Guta reports that 67% of small businesses spend more than $10,000 per year on analytics. However, analysing data doesn’t have to come with a high cost and you don’t have to be an online titan like Amazon to be able to compete in the data-driven business movement. Modern technology means that the ability to take data and turn it into a problem-solving insight is no longer exclusively within the realms of those companies with big budgets or individuals with years of experience or a specific university degree. These myths against the use of data in SMBs need to be dispelled. It's time for SMBs to leverage data in order to survive and thrive!
Method and a system for on-boarding, administration and communication between cloud providers and tenants in a share-all multi-tenancy environment
USPTO
September 12, 2013
A method of ascertaining requirements for onboarding new users to a multi-tenant computing environment is provided herein. The method starts off with the stage of recognizing the organizational roles of the new users. The method continues to the stage of identifying parameters pertaining to the service. The method then goes on to mapping the organization roles of the new users and the service parameters to a set of rules. The method further includes determining actions needed to be taken on the computer environment based on the set of rules. Finally, the method goes on to the stage of onboarding the new users to the computer environment.
Learning based logic diagnosis
USPTO
July 07, 2009
A system and method for diagnosing a failure in an electronic device. A disclosed system comprises: a defect table that associates previously studied features with known failures; and a fault isolation system that compares an inputted set of suspected faulty device features with the previously studied features listed in the defect table in order to identify causes of the failure.
What continued growth for Digital Transformation means for CIOs
Intelligent CIO
February 18, 2022
Digital Transformation is the incorporation of computer-based technologies into an organisation’s solutions, processes, and strategies. Industry pundits look at how enterprises in the Middle East and Africa (MEA) are winning with Digital Transformation, business benefits and digital technologies as the growth trajectory continues.
Analytics Democratization vs. Governance: Are they at odds?
Gartner.com
May 11, 2022
As companies embark on their journey to democratize analytics across their organization, questions of governance often come up. Is the very concept of analytics governance and democratization at odds? Join this session to hear how UBS balances the seemingly conflicting approaches.
Training Day: How to Optimize Predictive Algorithms (ML)
DMRadio
December 02, 2021
The power of prediction is well known in the analytics industry. The big question for today: How do you optimize, both from a design and production perspective? Join this conversation to hear Host @Eric_Kavanagh interview Kathleen L. D. Maley of Experian, David Sweenor of Alteryx and Tim Wyatt from Lookout.
Mcdonald's Journey to Analytics Enablement
DATACated
March 29, 2022
See how McDonald's is using analytics automation to democratize data
Every organization needs insights, but the path to analytics maturity can be daunting if leaders don’t know where to start. Listen to this on-demand webinar with McDonald’s’ director of global data and analytics enablement, Jeff Nieman, to hear how he’s helping McDonald’s on its path to enterprise-wide analytics enablement.
Up-Skilling for Analytics – Keys to Success
Inside Analysis
January 19, 2022
The key to success in analytics tends to be a moving target. First, we focused on the data, then the queries. With data science, we pivoted to more complex algorithms to find those meaningful insights. But regardless of which approach you take, there is one common thread that leads to breakthrough outcomes for your business: Automation!
Check out this episode of #InsideAnalysis to hear Host @eric_kavanagh interview several industry experts: Melissa Burroughs and David Sweenor of Alteryx, and Nick Jewell of Datacurious.ai. They’ll discuss the importance of knowing which automations can generate the optimal value, as well as the critical need for up-skilling your team.
Join Thinkers360 for free! Are you a Reader/Writer, Thought Leader/Influencer (looking to increase your earnings), or an Enterprise User (looking to work with experts)?
The Illusion of Control: Generative AI and the CIO's Dilemma
Future-Proof Your IT: The CIO's Guide to Generative AI Vendor Selection
Analytics Democratization vs. Governance: Are They at Odds?
Data use and Ethical Responsibility
The Art of The AI KPI
Crossing the Analytics and AI Chasm
Top 5 Strategies to Future-Proof Analytics, Data Science, and ML Investments
Why So Many Organizations Are Getting AI and Machine Learning Wrong
The Case for a Global Responsible AI Framework
Generative AI Business Applications: An Executive Guide with Real-Live Examples and Case Studies
The CIO’s Guide to Adopting Generative AI: Five Keys to Success
Artificial Intelligence: An Executive Guide to Make AI Work for Your Business
Automating Analytics: A Human Centered Approach to Transformative Business Outcomes
It's All Analytics – Part II: Designing an Integrated AI, Analytics, and Data Science Architecture for Your Organization
ML Ops: Operationalizing Data Science
Reporting, Predictive Analytics, and Everything in Between
Democratizing Data Science to Better Mitigate Risk
