Here is a roundup of interesting sites, resources and articles from around the web, curated by IIA. This month’s edition includes great articles on data literacy, data engineering, AI strategy, diversity and GPT-3. Follow us on Twitter (@iianalytics) and LinkedIn to receive daily updates on IIA content and curated content as it becomes available.
Featured Article from Analytics Leadership Consortium Newsletter
Each month, IIA’s Analytics Leadership Consortium (ALC) publishes a newsletter featuring reviews of timely and relevant 3rd party articles. Here is one of the articles highlighted in a previous newsletter.
IIA’s article summary: As business needs evolve and more sophisticated technology is needed to solve critical business problems, it’s important to be aware of the skills gap that will result from the introduction of more advanced solutions. If an organization wants to capitalize on the benefits of new technology solutions, then there are two elements that cannot be ignored: training and infrastructure support.
When evaluating new technologies, it’s critical to build in buffers for additional cost (and time) to ensure the right infrastructure is in place and there’s a solid plan for training or reskilling. Partner with your IT team as well as your L&D team to build out a plan that includes milestones and metrics to measure progress.
If your L&D team is not equipped to design tech training, especially new vendor offerings like AI, you may need to work with an external consultant who can set up a train-the-trainer program to scale basic training across the organization.
Once a new tech solution has been selected and deployed, encourage employees to keep the learnings and skills fresh; actively promote how the tech is being used internally to solve specific business problems. For those trained in the new technology, create different scenarios that people can work through on their own and share a “tips and tricks” email to keep people engaged and learning.
If you're looking to build data literacy at your organization, this article outlines four traits you'll need to be highly successful: 1.) widespread access to data, 2.) leadership by example, 3.) a platform for sharing and 4.) critical thinking.
Key Ingredients to Being Data Driven (Towards Data Science)
Five key areas of focus for becoming a data driven organization.
Tom Davenport explores Cigna’s commitment to data and analytics transformation. A good overview of their Global Data & Analytics organization and how analytics groups supporting multiple business units are becoming more tightly aligned while additional groups that are more horizontal in nature are focused on more specific data and analytics needs such as: Marketing Analytics, Measurement, Reporting and BI, and Enterprise Data.
Data Engineering in 2020 (Towards Data Science)
This article provides a good overview of data engineering and its evolution over the last several years.
Many organizations now have both data scientists and data engineers on staff. Unfortunately, there can be some issues with getting these two types of resources to work well together. This article has some useful insights for making it happen.
The Building Blocks of an AI Strategy (Sloan MIT Review)
Organizations need to transition from opportunistic and tactical AI decision-making to a more strategic orientation. This article covers three essential building blocks: 1.) a robust and reliable technology infrastructure 2.) new business models and 3.) ethics.
An interesting article on how GPT-3 program can write articles, produce code, and compose poetry.
Diversity in AI: The Invisible Men and Women (MIT Sloan review)
An insightful overview of bias in AI and three things we can do to address the problem: 1.) recognize that differences matter, 2.) recognize that diversity in leadership matters and 3.) recognize that accountability is necessary.
A good overview of Quantum computing, its potential to revolutionize analytics and AI and early signs of commercialization.
The Future of Data Science (Towards Data Science)
Good article on how data science and business context are converging.
Evaluating New Technology? You're More Biased Than You May Realize (Sloan MIT Review)
A good overview on how unconscious ideas about new technology can lead to poor investment decisions.
The Essential Skills Most Data Science Courses Won't Teach You (Towards Data Science)
This article provides a good overview of three vital skills needed to deliver business value through data science (software engineering, communication & business acumen) and how you can acquire them.
Autonomous vehicles have been just around the corner for a long time. This article discusses the history of trying to create self-driving cars.
The NFL’s Analytics Movement has Finally Reached the Sport’s Mainstream (Washington Post)
An interesting article on how analytics is transforming the NFL.
COVID19 Resources and Articles
To Fight Pandemics, We Need Better Data (MIT Sloan Review)
Tom Davenport, Blanton Godfrey and Thomas Redman explore the need for better professional management and leadership in the health data supply chain to combat pandemics.
COVID19 data from a network of 202 hospitals in 12 health systems formatted as questions and answers.
Featured News and Information Sites
The Machine consolidates AI and ML news and information from VentureBeat
This Medium site serves as the Journal for Data Visualization Society.
Great new online Coursera course by Eric Siegel (Predictive Analytics World). Includes three separate tracks or a combined specialization.
Top 25 Data Science YouTube Channels you should subscribe to in 2020 (Towards Data Science)
A good list of 25 YouTube sites covering data science, analytics and AI.
Leverage analytics to set your lineups in fantasy football.
Ed Feng's The Power Rank uses data and analytics to make accurate football, sports and March Madness predictions.
Featured Blog Sites
Reflections from Dr. Kirk Bone on advanced big data analytics for data-driven discovery, decision support, and innovation through data science.
Great insights from the team at Storytelling With Data including CEO and founder Cole Nussbaumer Knaflic.
Kaggle's Winner's Blog features interviews of contest winners on Kaggle.
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.