The Difficulties of ‘Toolifying’ Data Analysis

There’s plenty of software like Splunk to muck around with IoT data, but to gain the skills to really get something out of it, that takes time and experience. Mikio Braun, a post doc in machine learning, explains.

For a number of reasons, I don’t think that you cannot “toolify” data analysis that easily.

So my top four reasons are:

• Data analysis is so easy to get wrong
• It’s too easy to lie to yourself about it working
• It’s very hard to tell whether it could work if it doesn’t
• There is no free lunch

Let’s take these one at a time.

Read the rest of the article at Mikio’s blog:
The important parts of data analysis