Exploratory Data Analysis
A paradigm of data analysis that emphasizes discovering patterns, anomalies and correlations in data without a well-defined hypothesis, placing high demands on flexibility and iteration speed.
Timeline (last 90 days)
Conversational analytics tools are suitable for exploratory data analysis, and for key decisions it is still recommended to manually review the definitions and data sources.
Exploratory data analysis emphasizes discovering patterns, anomalies, and associations without a clear hypothesis and places high demands on flexibility and iteration speed; confirmatory analysis conducts statistical testing or causal inference on existing hypotheses and places high demands on rigor and reproducibility.
Data cleaning, feature engineering, and exploratory data analysis (EDA) are the most frequently occurring actual work tasks in internship positions.
面对低对比度困难数据应先进行探索性数据分析（EDA）理解数据分布再调整模型架构
All Facts (4)
Conversational analytics tools are suitable for exploratory data analysis, and for key decisions it is still recommended to manually review the definitions and data sources.
50%UnverifiedExploratory data analysis emphasizes discovering patterns, anomalies, and associations without a clear hypothesis and places high demands on flexibility and iteration speed; confirmatory analysis conducts statistical testing or causal inference on existing hypotheses and places high demands on rigor and reproducibility.
50%UnverifiedData cleaning, feature engineering, and exploratory data analysis (EDA) are the most frequently occurring actual work tasks in internship positions.
50%Unverified面对低对比度困难数据应先进行探索性数据分析（EDA）理解数据分布再调整模型架构
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