Who hasn’t suffered from the slowness of exchanges with the IT teams to obtain one or more data extracts in order to refine their analyses? Who hasn’t encountered any difficulties in understanding why sales figures in Germany fell last month on a particular product benchmark?
To meet the demands of Data Analytics teams and to guarantee them acceptable access times, IT teams are forced to provide fragmentary “extracts” of giant databases.
Data Analytics tools are unable to access the data quickly and easily to exploit large volumes.
The users see themselves reducing their fields of analysis by crossing only a few axes of data, when billions are present today in the information systems.
In the age of Big Data, being DATA-DRIVEN means being able to make all the available data available to users.