gegevensverkenning
Gegevensverkenning, also known as exploratory data analysis (EDA), is a critical phase in the data science workflow. It involves an initial investigation of data to discover patterns, spot anomalies, test hypotheses, and check assumptions. The primary goal of gegevensverkenning is to understand the data's characteristics before applying more formal statistical modeling or machine learning techniques.
During this process, analysts use a combination of statistical summaries and graphical representations. Common statistical summaries
Gegevensverkenning helps in identifying data quality issues like missing values, inconsistencies, or errors, which can then