Thinking About Real-Time Analytics

Martin Willcox offers some advice for people getting into the real-time analytics game:

  1. Clarify who will be making the decision – man, or machine? Humans have powers of discretion that machines sometimes lack, but are much slower than a silicon-based system, and only able to make decisions one-at-a-time, one-after-another.  If we chose to put a human in the loop, we are normally in “please-update-my-dashboard-faster-and-more-often” territory.

  2. It is important to be clear about decision-latency. Think about how soon after a business event you need to take a decision and then implement it. You also need to understand whether decision-latency and data-latency are the same. Sometimes a good decision can be made now on the basis of older data. But sometimes you need the latest, greatest and most up-to-date information to make the right choices.

There are some good insights here.

Related Posts

Multi-Threaded R With Microsoft R Client

David Parr shows us how to get started with Microsoft R Client and performs some quick benchmarking: This message will pop up, and it’s worth noting as it’s got some information in it that you might need to think about: It’s worth noting that right now Microsoft r Client is lagging behind the current R version, and […]

Read More

Image Clustering With Keras And R

Shirin Glander shows us how to use R to extract learned features from Keras and cluster those features: For each of these images, I am running the predict() function of Keras with the VGG16 model. Because I excluded the last layers of the model, this function will not actually return any class predictions as it would normally […]

Read More

Categories

January 2017
MTWTFSS
« Dec Feb »
 1
2345678
9101112131415
16171819202122
23242526272829
3031