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SAP InfiniteInsight – Explorer


I have not seen much posted regarding InfiniteInsight. I thought I would take some time to demonstrate parts of this product.

InfiniteInsight is predictive analysis tool SAP has acquired form the acquisition of the company KXEN.

This tool is designed to make the process of using a predictive tool easier and with less reliance on a data science. Also everything done is done by just CLICKING AWAY.

When you launch the product you will see Figure 1 as your entry point. In this blog I will focus purely on the explorer part. Explorer is used to get your datasets in a format that we can used to build predictive models on.

1. Explorer.png

Figure 1 – InfiniteInsight

So first step is to create explorer objects, will need to select the source of the data. In this scenario we are pulling from HANA.

2. Connect To Data.png

Figure 2 – Create or Explorer Objects

You can then create your datasets. In my example I have already created the datasets, all done by clicking and no code. I have created three types of data sets.

  1. Entity
  2. Time Stamped
  3. Analytical Record


Figure 3 – data sets

I wont be showing how I created each data set as there is a few screens that would need to be captured and will make the blog too long. Here is a example of the entity data. Data that shows entity that will be analyzed.


Figure 4 – entity data

Example of time stamp data, here we just create time entries.


Figure 5 – Time Stamp Data

The analytical record we have basically taken the time stamp data and joined the entity data, when creating this we can choose what fields to keep or exclude.


Figure 6 – Analytical Record

You can create different versions of the types of data, here I have a second analytical record set. It is the same as the first one except we have added some calculation columns being a sum, count and count distinct. Once again created just with clicks and no code.


Figure 7 – Analytical Record 2

I have also created a third analytical record where we have added extra columns that are pivoted so we can use to analyse even further.

As seen above, the explorer part allows you to get different sets of data and combine them, do counts, pivots and more. Once the data is arranged in desired format you can now move to the next section to predict data on it.

I will try cover that on another blog. 🙂

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