Having worked for years in telecom, which is a data-intensive industry, I am used to data mining, prediction models, and clustering. I can clearly see this trend spreading as more of our actions are moving to the digital—and quantifiable—world. Business intelligence and data warehousing are poised to grow and become more closely integrated with the sales and marketing departments. We can already see the rise of BI cloud software ready with application performance interfaces for a seamless integration with enterprise software.

Epic work! I agree that we need the right kind of analysis of the huge amount of data the world generates, but I want to bring your attention to an often ignored area—data quality. We can be very smart with our analysis tools, but if the data itself is wrong or false, it will always be “Garbage In/Garbage Out.”

I deal with environmental and genomic data, the amount of which is just growing exponentially, that we collect with sensors and next-generation sequencing facilities. You can apply these insights to the public sector as well, and to spin-off companies from universities and research institutes that can create knowledge from “big data.”

In my view, we are welcoming a new dot-com boom, or the “dot-com MK II,” which is not the simple replication of the last boom that we experienced a decade ago.

This new dot-com boom is driven by the new Web-based corporate data storage and analysis systems—such as SAP BW, Microsoft SharePoint, and Oracle APEX—that are changing the landscape of corporate business management and that enhance productivity, speed, and accuracy.

In my opinion, Apple (with the iPhone and iPad) is leading the way, followed by Google, Samsung, and Nokia. They are truly revolutionizing the way people live, and the level of changes they are catalyzing can only be matched by that of the personal computer (in the 1980s) and the Internet (in the 1990s), both of which changed our way of life on such a large scale. Today, iPhone users hardly use their desktop PCs now since everything is now in their palms.

Also in my view, the current dot-com boom is a natural progression from the first one, which was characterized by the isolated database (Oracle, SAP R/3), the Internet, and text-based mobile phones. When all this was linked together, it became the dot-com MK II.

Given the data explosion, the need for analysts and managers who can extract value and make decisions based on the information is clear. But I wonder if there exists the “desire” to do this work among the Generation Y’s who would likely be tapped as our future analysts? Stereotypically, they don’t appear to be interested in detailed, disciplined work. So unless it can be made fun and compelling (like a crime scene investigation), I doubt whether the need for analysts will be filled by Gen Y. This may be a better role for the “semi-retired” boomers.

As our ways of collecting data improve every day, it is no longer the real challenge; that lies in the collection and use of data when also managing human capital.

Your earlier article said that 70 percent returns are based on market variability, and only 30 percent is due to management style and strategy. Management of more data does not change this puzzle, as the 70 percent deals with chaos and fractals that are operating under the principles of uncertainity. I wonder how this increased data collection is going to increase profitability—has anyone done any computer modeling to know how likely this is to mean something positive for profits?

After reading your article, it seems a business-intelligence application that relies on big data could become a good tool for deal-designing and deal-making.

As a pioneer in data extraction on a global basis, we see not only the tip of the iceberg but also the greater mass below the surface. The impact of data to track competition, product development, and distribution feeds the strategies that you have noted. Today, this topic is absolutely crucial. We find that data can be old, aging, and stale—and the volume can be so large as to become useless. We approach these issues with a hosted on-demand service, and our clients share a common request: real-time data in usable formats and volume. I hope to read the second installment in what I hope will be a series.