In Part 2, we will examine how to exploit Application Compatibility (APPLCOMPAT) which was introduced in DB2 11, and Function Levels which is introduced in DB2 12 to safely manage change. The levels of APPLCOMAT you can specify is limited by the Function Level of your system.
When we compare past methods of mainframe data analysis to the capabilities of modern data relationship visualization software, it’s amazing how much more information a well-designed visualization can provide.
I recently attended a seminar of Edward Tufte—a statistician, artist and Professor Emerit
Until recently, this ACID compliancy wasn’t fulfilled by Hadoop transactions, but the advent of Hive 2 (June 2016) and others has changed this. Now you can have an equally valid acidity on Hadoop as you would expect on DB2.
This brings up once more the question on the relevance of DB2.
There’s good news from the IBM lab: IBM dashDB for Transactions now offers high availability plans, and offers “pay per use” plans that are billed by-the-day.
Analytics using R is often driven from client side applications such as RStudio and generally involves transmission of the large amounts of data from the database server to the clients for analysis. This method of doing the analysis can be slow given the limited resources on database client machines