What is The Purpose of Business Data Analysis?
Blog post from Sigma
Sigma Computing suggests augmenting business users' decision-making capabilities beyond exploratory analysis by incorporating four interactive functionalities: Driver Importance Analysis, Sensitivity Analysis, Goal Inversion Analysis, and Constrained Analysis. These tools aim to address the limitations of traditional exploratory data analysis (EDA), which often falls short in helping non-experts make informed business decisions due to cognitive overload, confirmation bias, and increasing data complexity. Inspired by John Tukey's emphasis on EDA as a vital part of data analysis, the article argues for a shift towards a synthesis that balances exploratory insights with practical decision-making needs. The proposed functionalities allow users to explore relationships between input variables and key performance indicators (KPIs), dynamically experiment with data, set and achieve specific goals, and apply domain knowledge through constraints. SystemD, a prototype developed at Sigma, embodies these concepts, aiming to empower business users to leverage data more effectively without requiring them to have expertise in data science, thus enhancing the overall value of business intelligence systems.
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