Tag Archives: Cognitive analytics

Big Data Simplicity

I have posted information and comments recently on our Talent Insights product and described how it uses cognitive analytics from Watson to support HR professionals. John Medicke is our IBM Distinguished Engineer working in this area. In the post below John adds a Big Data perspective to HR Analytics. Big Data has become an overused term in HR analytics and John brings some clarity to how we can think about Big Data, Cognitive Computing, and how it all works for HR professionals.

Headshot - John Medicke
John Medicke, IBM

Big Data Simplicity

Big data does not just mean “big.”  There is much more to this transformation to big data and to the analytics around big data than just supporting ever-increasing data volumes.  A large part of what will – and is with products like IBM Kenexa Talent Insights – bring this transformation is simplification of the data analysis experience.  HR organizations, just like any other business organization, have big data already.  The problem is that much of that data is inaccessible for analysis because of the cost involved in creating analytical insights from that data.

Kenexa Talent Analytics images
IBM Kenexa Talent Analytics images

Traditionally, analytics involves creation of complex warehouse data models, construction of costly Extract, Transformation, and Load (ETL) processing, and custom built dashboards.  This is a very rigid approach in which each new analytical business requirement translates into required changes in the dashboard design, in the warehouse model, and in the ETL processing.  Changing technology alone – for instance switching from a relational data warehouse to hadoop – does not solve the problem.  Intelligence and automation need to be built into the big data analytics platform.

This is what makes the Talent Insights approach different.  The system applies advanced data analysis, statistical analysis, natural language processing, and cognitive analysis to automatically understand the data, align that data with other data, and to prepare recommended analytical views for the user.  This brings immediacy to the analytical experience for the HR business user; load your data in, and then directly onto asking questions of your data.   It empowers the HR Professional to do perform their own analysis, gaining insights without a dependency on IT to create custom analytics for them.