There are many ways to write DAX code to implement measures in the tabular model but writing improper DAX code may slow down the performance of the tabular model. I have encountered this problem during a recent tabular project implementation where, when you use conditional checking commands in DAX against a large number of rows, it may cause performance issues.

According to Gartner, the famous technology research group, 70% to 80% of Business Intelligence (BI) and data warehousing (DW) projects end up in the trash bin. BI projects often fail, incurring colossal losses to organizations. Why do DW/BI projects fail? What can organizations do to avoid pitfalls that cause DW/BI projects to fail?