Assessing the Bounties and Boundaries in Big Data Analytics

Many companies are finding a huge upside potential in data analytics to grow revenues and profits, and cut costs. Sharper analysis of rich data from an expanding range of sources is enabling more cost-effective marketing and improved customer engagement. As a result. companies are investing in information management infrastructure to extract the gains. Yet, data analytics cannot be effective beyond a point, and companies need to keep their approaches grounded in reality, say Peter Fader, Wharton marketing professor, and K. R. Sanjiv, global head of analytics and information management at Wipro Technologies.

Citing Knowledge@Wharton


For Personal use:

Please use the following citations to quote for personal use:


"Assessing the Bounties and Boundaries in Big Data Analytics." Knowledge@Wharton. The Wharton School, University of Pennsylvania, 21 December, 2012. Web. 18 October, 2017 <http://knowledge.wharton.upenn.edu/article/wipro/>


Assessing the Bounties and Boundaries in Big Data Analytics. Knowledge@Wharton (2012, December 21). Retrieved from http://knowledge.wharton.upenn.edu/article/wipro/


"Assessing the Bounties and Boundaries in Big Data Analytics" Knowledge@Wharton, December 21, 2012,
accessed October 18, 2017. http://knowledge.wharton.upenn.edu/article/wipro/

For Educational/Business use:

Please contact us for repurposing articles, podcasts, or videos using our content licensing contact form.