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December: Best of the Web

Read below for a roundup of interesting sites, resources, and articles from around the web, curated and contextualized by unbiased analytics experts at IIA. Highlights include articles about creating a data-driven company from a VC’s perspective; how to make agile work for analytics; using digital twins to manage supply chain disruption; and the roles and responsibilities for a successful data governance program. There is also a great article on one of earliest known computers, an ancient Greek mechanical device for calculating celestial movements. Follow us on Twitter (@iianalytics) and LinkedIn to receive daily updates on IIA content and curated content as it becomes available.

“Article of the Week” from IIA’s Normal Distribution

Each week, IIA’s Normal Distribution email (sent to anyone that has filled out a form on our website – subscribe here or with footer form below) features timely and relevant third-party articles. Here are the articles highlighted in the “Article of the Week” from the December Normal Distribution emails.

The Building Blocks of a Data-Informed Company (Sequoia Capital)

A company’s ability to compete and innovate is increasingly driven by how successfully it can apply analytics to mine for insights across vast, unstructured data sets from disparate sources. This article outlines the characteristics of a data-informed company from the perspective of Sequoia Capital, including a maniacal focus on impact and building a culture of measurement and truth-seeking.

How to Make Agile Actually Work for Analytics (Toward Data Science)

Good article on how to apply "the spirit of agile" to analytics, including four key guiding principles: 1.) Decisions over dashboards; 2.) Functional analysis over perfect outputs; 3.) Sharing data over gatekeeping data; and 4.) Individuals and interactions over processes and tools.

Method is All You Need: 7 Mistakes to Avoid in Data Science (Toward Data Science)

Good overview of seven common data science project mistakes, including: 1.) Pretending data science is not software development; 2.) Pretending data science is just software development; 3.) Isolating your data scientists; 4.) Neglecting the data; 5.) Skipping documentation; 6.) Trying to get the first model right; and 7.) Thinking that a model is forever.

Analytics and AI in 2022: Innovation in the Era of COVID (ZDNet)

This ZDNet article features a roundup of 2022 analytics and AI predictions from a variety of articles. Topics include supply chain challenges, continued talent shortages, growing interest in data mesh/data fabric architectures, and increased use of no-code/low-code.

​​Featured Articles on Analytics Strategy

The Essential Components of Digital Transformation (Harvard Business Review)

Companies often embark on a digital transformation agenda without having a clear definition or vision for what it means. This article outlines that the goal of digital transformation is to become a data-driven organization, ensuring that key decisions, actions, and processes are strongly influenced by data-driven insights, rather than by human intuition, and the five essential components of a successful digital transformation.

Managing the Data Science Debt (Medium)

As data science transitions from a research-oriented mindset to software-oriented mindset, it will be critical to strike the proper balance between the modeling and software dimensions of data science. This article outlines a useful framework for balancing these dimensions and communicating the unique nature of data science work.

10 Key AI & Data Analytics Trends for 2022 and Beyond (KD Nuggets)

This is a good list of ten AI and analytics trends for 2022 from KD Nuggets, including hyper-parameterized models, augmented workforces, low-code/no-code AI, and the rise of XOps.

Featured Articles on Data and Analytics Culture

4 Practical Actions for Embedding a Data Culture (Toward Data Science)

This Toward Data Science blog post sets out four practical examples you can use to embed a data culture within your organization, including: 1.) Find data champions; 2.) Level up with training, lunch & learns, and documentation; 3.) Quick wins; and 4.) Agile methodologies.

10 Steps to Creating a Data-Driven Culture (Harvard Business Review)

For many companies, a strong, data-driven culture remains elusive, and data are rarely the universal basis for decision-making. This article outlines ten data principles for creating and sustaining a data-driven culture.

The Cultural Benefits of Artificial Intelligence in the Enterprise (MIT Sloan Management Review)

This report identifies a wide range of AI-related cultural benefits at both the team and organizational levels and offers a detailed analysis of the dynamic between culture, AI use, and organizational effectiveness.

Featured Articles on Analytics Leadership and Talent

Remote Teams in ML/AI (O’Reilly Radar)

The key ingredient to successful remote work is, quite simply, whether company leadership wants it to work. This article provides some great perspective on how to successfully lead remote data science teams.

Guide to Data Governance Roles and Responsibilities (Medium)

Many organizations are putting a renewed emphasis on data governance. This article provides a good outline of different roles required for a successful data governance initiative.

Featured Articles on Data and Analytics Technology

6 Best Practices for NLP Implementation (Information Week)

Recent advances in AI and ML have made NLP powerful enough to surpass human performance. This article outlines six useful best practices for successfully leveraging the technology.

Featured Articles with Analytics Uses and Case Studies

How AI Digital Twins Help Weather the World’s Supply Chain Nightmare (MIT Technology Review)

With the supply-chain disruptions showing no sign of easing anytime soon, businesses are turning to a new generation of AI-powered digital twins to help them get goods and services to customers on time.

Autonomous Weapons Are Here, but the World Isn't Ready for Them (Wired)

Are we on the path to Skynet? Advances in artificial intelligence, sensors, and electronics have made it easier to build more sophisticated autonomous systems. This article outlines the growing debate around the development and use of machines that can decide on their own when to use lethal force.

How Enterprise AI Architecture Is Transforming Every Industry from Commerce to Wealth Management, And Beyond (Forbes)

Enterprises often struggle to implement AI. This article highlights how startups focused on commerce and wealth management are architecting solutions to help companies overcome the challenges.

Featured Articles on AI

AI Generates Hypotheses Human Scientists Have Not Thought Of (Scientific American)

Creating hypotheses has long been a purely human domain, but scientists and engineers are beginning to leverage machine learning to create original insights and suggest new hypotheses based on data patterns instead of relying on human assumptions.

The Movement to Hold AI Accountable Gains More Steam (Wired)

This Wired article provides a great round up of recently released AI accountability research and the growing legislative and regulatory momentum to audit and document the impact of AI in society.

Interesting Sports and Science Articles

An Ancient Greek Astronomical Calculation Machine Reveals New Secrets (Scientific American)

Fascinating Scientific American article on the ancient and mysterious Antikythera mechanism, a mechanical computer that stored astronomical data and calculated the movement of celestial objects.

We Crunched the Numbers On 2021’s Best (And Worst) Teams (FiveThirtyEight)

An interesting data-driven review of the best teams of 2021 across the NBA, NFL, MLB and NHL including best overall champion, best team not to win it all, most improved team and worst team.

About IIA

IIA is the industry’s leading source of insights and advisory services for companies transitioning to data-driven decision-making and advanced analytics. IIA continuously seeks out insights, information and experts to elevate our client’s and our community’s analytics expertise through two service lines. IIA's Research and Advisory Network (RAN) provides clients with access to the world's largest analytics-focused expert network; a resource designed to accelerate analytics teams' progress against their projects and initiatives. IIA’s Analytics Leadership Consortium is a closed network of analytics executives from diverse industries who meet to share and discuss best practices, as well as discover and develop analytics innovation, all for the purpose of improving the business impact of analytics at their firms. IIA’s family of analytics assessments provide actionable, diagnostic insights for organizations looking to maximize their analytics performance.