The SAS High Performance Analytics involved not only querying, descriptive statistics, summarizations or reports but also solved complex business problem scenarios using high-end analytical techniques at high speed. It makes organizations enjoy swiftly and confidently grab the firsthand opportunities, better decision making putting them at a competitive edge and achieve new high valuable insight from big data as it focuses on the whole model of development life cycle and its deployment life cycle (Bolohan & Ciobanu, 2013). The new innovative technology High Performance Analytics (HPA) have aided marketing analyst through running of algorithms and routines to process the firm’s huge amounts of data through a millions of scenarios in order to extract key insights (Liebowitz, 2013). There are three modern distributed processing approaches that give HPA power to handle these data volumes. This includes: grid computing, in- memory, and in- database. They allow firms enjoy a competitive edge by utilizing HPA advancements whereas providing scalability, flexibility, IT- resource utilization and unprecedented profits.