The value of data lies in its ability to bring about tangible positive change. Leveraging data can help solve complex business decisions and improve everyday routines. Here are some recent favorite articles that demonstrate the practical role of data in different areas, such as survival analysis, decision trees, personal habit tracking, customer lifetime value modeling, and improving training logs for athletes.
Real-World Problems, and How Data Helps Us Solve Them
As middle managers, you understand the importance of leveraging data to drive positive change in your organization. It’s not just about using the latest tools and models, but about making a real impact in the real world. To help you connect the dots more effectively and inspire you to try new approaches, we’ve gathered some of our favorite articles that offer practical solutions to common problems. These articles cover a wide range of use cases and provide a detail-oriented outlook on the role of data in our lives.
Exploring Time-to-Event with Survival Analysis
In this article, Olivia Tanuwidjaja provides an accessible introduction to survival analysis. She explains how this approach can be applied to various problems, such as medical field, maintenance prediction, and customer analytics. Survival analysis can help you make data-informed decisions in complex scenarios.
How Does a Decision Tree Know the Next Best Question to Ask from the Data?
Gurjinder Kaur shares a beginner-friendly primer on decision trees. Decision trees are a fundamental machine learning technique that can be used for binary classification tasks. This article explains in detail how decision trees work and how they can be used to make predictions in different contexts, such as determining whether a fish is more likely to be tuna or salmon.
My Life Stats: I Tracked My Habits for a Year, and This Is What I Learned
Pau Blasco i Roca presents a yearlong project that combines data analytics and the quantified self. By tracking his daily activities for 332 days, Pau shows how even seemingly trivial data can provide meaningful insights. This article demonstrates the value of analyzing personal data to improve habits and routines.
Methods for Modelling Customer Lifetime Value: The Good Stuff and the Gotchas
Katherine Munro’s comprehensive guide to customer lifetime value (CLV) modeling offers clarity on this common goal for industry data scientists. She explores various modeling options, their strengths, and limitations. Understanding CLV can help you make informed decisions about customer acquisition and retention strategies.
Improving the Strava Training Log
In this deep dive, barrysmyth takes us through the process of analyzing and visualizing his Strava training log. Whether you’re a marathoner or not, this article provides insights into using data to improve performance. It highlights the practical application of data analysis in a specific context.
These articles are just a sample of the fascinating topics our authors have covered recently. From tackling data manipulation to exploring serverless technology, there’s something for everyone. If you’re interested in staying updated on the latest AI insights, consider becoming a Medium member.
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