With the growth of Big Data tools and technologies, the state-of-the-art in marketing is rapidly evolving. Business Intelligence (BI) solutions have become synonymous with online marketing thanks to new software applications used to analyze an organization's raw data. Instead of traditional campaign planning and KPI-based analysis, marketers now have the power to fully track individual customer journeys and understand the impact of each interaction on business outcomes. Unlocking access to such granular levels of data gives marketers the opportunity to do what they do best: Ask "How can I improve the experience of my customer and the outcome to my business?" BI that is purpose-built for Big Data is the best way to visualize large datasets over time and allows data-savvy marketing professionals improve customer interactions by learning from and iterating faster on their marketing initiatives.

Companies such as Yahoo, Merck, Macy's and eBay have moved to clear obstacles that were blocking the path to success with big data analytics applications.

Even with the expanding array of advanced analytics tools now available for use, analytics teams still face plenty of challenges in developing big data applications and getting useful information from them.

In this new era where Big Data is starting to have a big impact on economy; something I called Bigdatanomics in my doctoral thesis (SARSAR, 2015); practitioners are seeking new levers to drive fast (h1), proactive (h2) and or better decisions (h3).