title: Periodic snapshot fact table with large dimensions
body: <p>I have been asked to model a star diagram.<br>
  I have 3 dimensions:  </p>
  
  <ol>
  <li>Date (day,month, year, week, quarter, ...)</li>
  <li>place (500 distinct values)</li>
  <li>Product (80k different products)</li>
  </ol>
  
  <p>The main question is how many items (products) are stored at the end of a day in every place.</p>
  
  <p>After some study-time with regards to dimensional modeling. I think I should implement a <strong>Periodic snapshot table</strong>. However reading trough the Kimball Docs, I noticed that a periodic snapshot demands an entry for every combination of the dimensions. This means I should add <strong>40M</strong> rows every day (80k*500).<br>
  Knowing that the products are (real) slow movers and that many places store <strong>zero</strong> products during long periods, this sounds like an extreme overkill.<br>
  FYI the transactions in the source DB are 150k rows after three years.  </p>
  
  <p>So should I really add 40M rows every day, or could I just add the non-empty stores with their products specified? Also if for whatever reason one day all stores are empty, should I make an entry for that day (with dimensions N/A for store and product)?</p>