AI Today Podcast: AI Glossary Series – Analytics, Data Visualization, Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Proscriptive / Projective Analytics
Sep 22, 2023
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This podcast episode discusses the importance of understanding analytics and data visualization in AI projects. It explains key terms such as descriptive, diagnostic, predictive, and projective analytics and highlights the tools and methods used for each. Understanding these concepts is crucial to the success of AI projects.
Thorough preparation and fundamental business buy-in are crucial for success in AI projects.
Understanding the different types of analytics (descriptive, diagnostic, predictive, projective) enables better decision-making and project planning in AI projects.
Deep dives
Understanding the importance of AI project preparation
The podcast episode highlights the significance of thorough preparation in AI projects. It shares a story of a project manager who, in the midst of an AI project, realized that they lacked access to essential data. This realization forced them to reassess their project, emphasizing the importance of having fundamental business buy-in from the start. It serves as a reminder that basic understanding of common terms and proper planning is crucial for success in AI projects.
Exploring different types of analytics
The episode delves into the different types of analytics: descriptive, diagnostic, predictive, and projective analytics. Descriptive analytics focuses on analyzing historical data to understand relationships and trends. Diagnostic analytics aims to identify cause-and-effect relationships in data. Predictive analytics leverages past and current data to make future predictions, such as forecasting or predictive maintenance. Projective or prescriptive analytics focuses on analyzing current data to determine potential impacts of decisions, often used for what-if analyses. Understanding these different types of analytics enables better decision-making and project planning.
The value and use cases of different analytics
The episode highlights that each type of analytics presents different value and serves different purposes. Descriptive analytics, relying on traditional reporting and charts, helps answer the question of 'what happened?' without the need for complex machine learning. Predictive analytics, powered by machine learning models, allows for future prediction based on past and current data. Projective or prescriptive analytics pushes the boundaries of machine learning, often requiring human creativity to analyze potential scenarios and determine the impact of decisions. Recognizing the value and applications of different analytics types helps in choosing the right approach for specific AI projects.
Analytics are statistical and other methods to gain informational insight from data. Since data is the heart of AI, it makes sense analytics should be understood. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Analytics, Data Visualization, Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Proscriptive / Projective Analytics.