What kind of RAM to choose for data analysis?
It's not easy to compare two RAMs with different frequency and latency, since both of them affect your performance with not the same way.

The short answer is:


If you have two RAMs with same capacity and frequency, choose the one with lower latency.
If you have two RAMs with same capacity and latency, choose the one with the higher frequency.


From lifehacker.com


  Essentially, you have two things to worry about when it comes to RAM "speed": frequency, which deals with how much data can be transferred to the stick at one time, and latency, which is how quickly it responds to requests. In the current market, as you get to higher frequencies, latency tends to increase, so in many cases, they tend to balance each other out. Buying RAM with a higher speed doesn't matter a ton.


The long answer:

Don't worry about RAM. Yes, if you have a crappy RAM, you will also have a problem with your performance. But, the most important thing in Data Analysis is the performance of your code. An example from my personal experience:

I had a text dataset, about 30GB. I needed to create a corpus for a simple TF-IDF. The brute-force code, spent about 15 hours, whereas a map-reduce algorithm spent about 1.5 minute for the same dataset.

I work on a MacBook Pro with 16GB RAM. I didn't have any problem with performance. However, if you have huge datasets and even code improvements and RAM upgrades cannot help, you may reconsider to move to Hadoop or similar.