The Concept

Replace the human data scientist with a robot for predictive data mining.

The Implementation

Our robot lives on Amazon Web Services. We are currently using 16 processors for data analysis. There is no charge, no advertising. Completely FREE, in the interest of disrupting the marketplace for analytical software!!

Compare our new way of doing with the current old way:

The old way The new way
  1. Human data scientist obtains data from client
  2. Data scientist interviews client and studies sources and meaning of data
  3. Data scientist prepares data in a form suitable for machine learning algorithms
  4. Data scientist selects learning method and sets various parameters
  5. Data scientist revises parameters or data prep to try to improve results
  6. Data scientist repeats steps for other methods
  1. Client prepares data in a standard data-base table format and uploads to cloud
  2. Robot completes the analysis and reports results

The human analyst has the potential for major insight and that can lead to superior results. Let's postulate that a robotic analyst can be built. Then there are incredible advantages to this form of processing data. Among them are the following

Getting the data ready for predictive analysis

Who does this? The traditional view is that the data scientist gathers the data, gathers some knowledge of the domain, possibly interviews the domain experts, and then proceeds to organize the data in a form suitable for specific predictive methods.

We chose an alternate path. The actual mathematical formulations and machine learning methods might be obscure to a client, yet the client is far more familiar with the data. Following a few simple rules, data can be prepared for analysis. You the client often have insight into the meaning of the data, and can organize data in a form that lends itself to more favorable predictive results. If we separate the task of data preparation from the actual analysis, the data owner has the advantage in preparation.