This post is part of the series, Deep Dive.
Those of us who handle data for our organizations are used to rapid change. We are met daily with new data points, deprecated data, and demands to deliver informed answers in short timeframes. However, this past year brought unprecedented change that upended routine practices in modeling and analytics.
How can you anticipate and handle significant changes as they arise? How can you deal with aberrations and outliers in modeling data? How do you decide which analyses are most likely to yield actionable information under novel circumstances?
In this Deep Dive, we will share solutions, including:
- Standardizing data
- Deriving other metrics and more meaning from your data
- Giving meaning to what look like anomalies
- Seeking to eliminate bias