The popular conception at the moment is that in order to take advantage of Big Data, an organization has to recruit data scientists, who are hard to retain. But Salesforce, with the launch of updates to the Salesforce Marketing Cloud at a Salesforce World Tour event, is making the case for embedding machine learning algorithms inside a cloud application in a way that promises to eliminate the need for many marketing organizations to hire their own dedicated data scientist.
Meghann York, director of product marketing for Salesforce Marketing Cloud, says that Salesforce Marketing Cloud Predictive Journeys, with Predictive Scores and Predictive Audiences, now makes it possible to essentially predict how customers will respond to, for example, an email marketing campaign. In addition, York says organizations can leverage Predictive Audiences to segment customers based on the predictive scores created by Salesforce Marketing Cloud.
At this juncture, it’s fairly obvious that Big Data analytics will transform just about every application and process. Less clear is the degree to which organizations will have to build the algorithms needed to transform those processes themselves. Instead, it’s much more likely that organizations will rely more on algorithms that will increasingly be slipstreamed in applications running inside and out of the cloud.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=i
That doesn’t necessarily mean that demand for data science skills will slacken. But organizations need to be careful about distinguishing between algorithms they need to build versus advanced analytics features that will be increasingly embedded within just about every application.
There’s no doubt that Big Data analytics will be a crucial tool for remaining competitive. But in the age of the cloud, it doesn’t necessarily follow that every organization will need to build those Big Data capabilities from the ground up on their own.