While 3NF was ideal for machine processing, the segmented nature of the data model can be difficult to consume by a human user. Analytics via query, reporting, and dashboards were often facilitated by a different type of data model that provided pre-calculated analysis such as trend lines, period-to-date calculations (month-to-date, quarter-to-date, year-to-date), cumulative calculations, basic statistics (average, standard deviation, moving averages) and previous period comparisons (year ago, month ago, week ago) e.g. dimensional modeling and beyond dimensional modeling, flattening of stars via Hadoop and data science.
