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
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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.
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Tags: Analytics, AI, Big Data
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?
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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
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Tags: AI, Analytics, Big Data
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
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Unconscious bias in AI models: is synthetic data the ethical solution?
Journal du Net
August 23, 2022
Previously considered the preserve of the data scientist, artificial intelligence is now omnipresent in our daily lives.
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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.
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Tags: AI, Analytics, Big Data
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.
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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
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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
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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.
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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.
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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.
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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.
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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?
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Unconscious Bias in #AI Models - Can Synthetic Data be an Ethical Solution?
Netzpalaver
July 19, 2022
How can unconscious biases in AI models be detected and reduced?
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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.
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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.
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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
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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
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Finding the right problem to solve is unique to each business
Business Transformation
February 09, 2022
To become data-driven, we need to start with data literacy programmes.
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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.
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Developing a data-driven business: Four scalable strategies for any SMB to turn data into problem-solving insight
ITProPortal
September 23, 2021
There exist a range of myths against the use of data analytics that need to be dispelled
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The Rise of the Citizen Data Scientist
DataScienceCentral.com
October 08, 2017
The development of Big Data, artificial intelligence and predictive analytics has created extravagant expectations for enterprise productivity growth — and aroused popular anxiety about intelligent information systems taking jobs from human workers. It is ironic, against that backdrop, that what is holding back widespread adoption of these technologies is, of all things, a manpower shortage.
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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!
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Automating Analytics: A Human Centered Approach to Transformative Business Outcomes
O’Reilly Media
October 22, 2021
Transformation without analytics is just digitization. Analytics makes it transformative.
—David Sweenor, Alteryx
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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.
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ML Ops: Operationalizing Data Science
O’Reilly
April 01, 2020
Four Steps to Realizing the Value of Data Science Through. Model Operations
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Reporting, Predictive Analytics, and Everything in Between
O’Reilly Media
November 01, 2019
A Guide to Selecting the Right Analytics for You
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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.
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Democratizing Data Science to Better Mitigate Risk
Raconteur
March 28, 2022
Businesses with agility react better to disruption, but a data skills gap is holding them back.
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Data Science Job Market Trends
Datamation
January 27, 2022
5 Top Data Science Job Market And Career Trends
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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.
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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!
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