Hosts discuss anomalies in data documentation, importance of clear communication, anomaly detection in data, challenges during COVID-19, visual markers for anomalies, and necessity of central documentation for data integrity.
Documenting anomalies and changes in a central repository fosters transparency and trust in data.
Deciding to normalize anomalies in data depends on predictive needs and use cases.
Centralizing documentation of anomalies in a common repository promotes accessibility and data transparency.
Deep dives
The Importance of Documenting Data Anomalies
Documenting data anomalies and significant events is crucial to ensure transparency and maintain trust in the data. Having a central repository for documenting changes, anomalies, and impacts can help in keeping track of these occurrences and providing easy access to relevant information over time. Communication and transparency regarding data modifications and anomalies are key to fostering trust in the data within an organization.
Consideration for Smoothing Out Data
Smoothing out data and normalizing it during anomalies depends on the predictive needs and the use case. Organizations should weigh the decision based on the impact of anomalies on forecasting, reporting, and predictive modeling. Identifying the purpose of the data and its usage can guide whether to normalize anomalies or have them visible depending on the predictive and reporting requirements.
Central Location for Documentation
Having a central repository for documenting data anomalies, changes, and impacts is essential to ensure transparency and accessibility for all team members. By centralizing documentation in a common location, such as a confidence page or report reference section, organizations can provide easy access to information about anomalies, significant data changes, and ownership details, fostering a culture of data transparency.
Consideration for Toggle Filters
Incorporating toggle filters in visualizations to highlight anomalies and allowing users to include or exclude them can provide flexibility in data analysis and reporting. By enabling users to effortlessly toggle anomalies on or off, organizations can tailor the data visibility based on their specific needs and analysis requirements, enhancing the overall user experience and data exploration.
Enhanced Data Visualization Features
Exploring advanced data visualization features that can highlight anomalies in real-time and provide options for filtering them can improve the data analysis process. Utilizing visuals that automatically filter out anomalies or allow users to toggle their visibility can enhance the user experience and facilitate better decision-making based on accurate and reliable data views.
We have another mailbag! Mike, Seth, & Tommy dive into a question from a listener, on how do we document and review outliers in our data.
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