The driving force behind enterprise data analytics today is obtaining valuable insights more quickly from large, diverse data sets. A key issue blocking easier access for data scientists, business analysts and IT has been finding an alternative to the current data modeling process.
The current options don’t work all that well — the data warehouse and conventional data lake, as well Hadoop-based point solutions, all have their challenges. The truth is, data modeling is most easily configured, structured and analyzed within the context of a smart data lake.
Author: Sean Martin