Initially, it seems like just a different sequence of the two characters “T” and “L”. But this difference often separates successful big data projects from failed ones. Why is that?
And how can you avoid falling into the most common data management traps around mastering big data? Let’s examine this topic in more detail. Why are big data projects different from traditional data warehouse projects?
Author: Ralf Goetz