Expert Talk: Anjul Bhambhri (IBM) on Big Data paradigm shifts, Hadoop and transforming data
Jun 17, 2012
“Businesses are able to figure out what is relevant to them, so they can be serviced on what they care about.”
“We mining all this data not just for doing traditional slicing and dicing, but we are mining this data to gain new knowledge”
Exploring the Big Data realm, we often talk to some of the most profound experts in the industry. We talk to them about their visions on technology and business, the impact of Big Data and what key concepts we should consider in our research. We would like to share these ‘Expert Talks’ with you during the next couple of months. We also would like to encourage you to share your reflections in the comments. Today in our video section: Anjul Bhambhri, Vice-President of IBM Big Data.
Anjul Bhambhri has 23 years of experience in the database industry with engineering and management positions at IBM, Informix and Sybase. Bhambhri is currently IBM’s Vice President of Big Data Products, overseeing product strategy and business partnerships. In 2009, she received the YWCA of Silicon Valley’s “Tribute to Women in Technology” Award.
We talked with Anjul about how Big Data is changing our approach of IT and in what way it will change the way we look at the web. We also talked about the process of transforming information: how can we turn messy data into valuable information? One way of transforming data is Hadoop, a framework for reliably running applications on large hardware clusters. Companies ranging from Facebook and eBay to Hulu and IBM all employ Hadoop as part of their respective data-crunching infrastructure. Anjul talks about Hadoop’s way of transforming information and how it became such a fast adopted technology. If you have any thoughts on these issues yourself, please feel free to share them in the comments.
Q: What is the big turn that makes Big Data change our approach to IT?
Q: Can you explain Hadoop’s transformation of information and making it one of the most readily adopted technologies in history?
Q: How can you turn the messy ‘gray’ data into valuable information?