I'm building a DW with a star schema modeling. I'll use it for a BI project with pentaho. I'll have of course a time dimension table. I'll analyze my fact table with differents granularity (day, week, month year, perhaps other)
Should I put one attribute for each of those granularity in my dimension table (so I have one day attribute, one month attribute, one year attribute ...) or should I just write the date and then calculate everything with this date (get the month of the date, the year of the date ...)?
thks a lot for your help
I would add the attributes of the dates as their own columns. This does not take up significantly more space, and generally gives the query optimiser a better shot at working out how many of the dimension table records match a given criterion (for example, that the day_of_month = 31).