Difficult analytics features

In order to process data into an analytics workbench, as you will know from experience, data comes in various formats and has to be ingested in order to be made useful. It is then transformed by your data factory and made fit for purpose along the journey. All this processing leads up to the point where data can be explored via analytic capabilities. Data’s purpose is to be transformed into information, knowledge, wisdom, insights, and, ultimately, value to the business. All data is big data in time since the volume of data being collected is always increasing. Even when limited referential data is joined with big data, the sum becomes huge data. There will be many dimensions across a multi-dimensional dataset that will exist. All this data is subject to operations of the analytics workbench.

Key capabilities in the analytics workbench

You will need a number of key capabilities in the analytics workbench to be effective in your mission. Some...