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KDnuggets Exclusive: Interview with Anjul Bhambhri, VP of Big Data Products at IBM


KDnuggets talks with Anjul Bhambhri, IBM’s Vice President of Big Data Products about Big Data Trends, developing the Big Data capabilities in-house vs. outsourcing, five crucial steps to adopting a success big data strategy and advice for beginners.



Anjul Bhambari IBMAnjul Bhambhri is currently IBM’s Vice President of Big Data Products, overseeing product strategy, development and business partnerships. Previously at IBM, Anjul focused on application and data lifecycle management tools and spearheaded the development of XML capabilities in DB2 database server. She has 25 years of experience in the database industry and has held engineering and management positions at IBM, Informix and Sybase. In 2009, she received the YWCA of Silicon Valley’s “Tribute to Women in Technology” Award.

Twitter: @AnjulBhambhri

Here is my interview with her:

Anmol Rajpurohit: 1. IBM has clearly been one of the leaders in Big Data industry with ahead-of-times technology such as Watson. According to you, what key trends will drive the growth of Big Data industry for the next 2-3 years and what factors will play a critical role in the success of Big Data projects?

TrendsAnjul Bhambhri: We’ve only just begun to tap into the potential of what is in store for the world of big data. In the years ahead, organizations will need to become much more data driven, applying insights to everything from key business process and decisions to the way they fundamentally operate. Rather than rely on decisions stemming from gut feelings, businesses will infuse analytics into everything that employees, partners, and customers touch (management systems, machine to machine processes, daily decisions & tasks) leading to highly curiosity-driven, evidence-based cultures, and workforces. The factors that will better ensure success including: fostering a culture that is analytics-savvy; making security, privacy and governance protocols a requirement for big data implementations; the creation of a Chief Data Officer as part of organizations’ C-suite; and a heightened focus on harnessing data generated outside of the organization in conjunction with data in the enterprise with the increased use of social media and mobile devices.


AR: 2. One of the biggest Big Data implementation issues is to decide between developing the Big Data capabilities in-house vs. outsourcing. What are the key factors in this decision and what selection criteria you suggest to evaluate Big Data outsourcing vendors? In-house vs Outsourcing AB: Whether you are evaluating big data development in house or via an outside vendor the most important factor to think about is longevity. You don’t want to base a strategy on ‘right now,’ you need a technology infrastructure that will support big data and analytics into the future, ensuring your business’ growth and success. Taking a big data platform approach is key as it allows users to address the full spectrum of big data challenges. You want a solution that is open and can scale as you continue your big data journey and your data-driven needs expand.

A big data platform has attributes such as the ability to perform quick and accurate analytics, can leverage and enhance existing technologies in use such as open source Hadoop technology; and is cloud-enabled to scale as needed while optimizing resources. Keeping these principles in mind, managing big data and deploying the IT infrastructure to support it, should no longer be a cumbersome process. In this new era, simple, easy-to-use tools and platforms exist that can help organizations make sense of the new data-driven norm.


AR:3. What do you see as the biggest challenges towards successful deployment of Big Data projects? What advice would you give to firms who are trying to make Big Data an integral part of their business strategy?

Big Data AB: You touched on it in your previous question – the key to success is thinking broadly, having foresight and planning - recognizing that a strategy is needed that not just tackles how to start but how to sustain. Therefore the crucial steps to adopting a success big data strategy includes:

  1. Defining the challenge and understanding the opportunity that big data presents for the organization. Establish the larger end goal – whether it is cost savings, increased ROI, or reduced risk when beginning a big data program.
  2. Discovering the data that needs to be analyzed and where it is located. Depending on the industry, different types of data are more critical to the organization than others. These various types of data need to be located and analyzed in order to obtain critical insights. Also, a federated approach to big data, which is taking the analytics where the data resides, is a faster and more cost effective than stuffing all the data inside a data warehouse.
  3. Obtaining the business buy-in– big data is no longer just an IT issue, it affects the entire business as a whole so it is necessary to start with the C-suite and get them to apply big data to growth opportunities. Show them the larger implications that their data presents for the organization. Map out potential savings and increased ROI that will impact the bottom line and future growth of the business.
  4. Establishing the right technology which was discussed previously and lastly
  5. Ensuring the right team and skills are in place. Having people with the right skills is equally as important as having the right technology. Because the data is only as good as the value it provides – so you need people with the expertise to find the insights in the data. Building out a data scientist role or data science team, and the adoption of the Chief Data Office role, will foster collaboration among the organization and provide ‘champions of data’ whom can derive the maximum business value from their organization’s data.





























AR: 4. Data Scientist has been termed as the sexiest job of 21st century. Do you agree? What advice would you give to people aspiring a long career in Data Science?

Data Scientist AB: The role may not be specifically called ‘data scientist’ in every organization, but the need for people skilled in data is very much a reality and will continue to be fundamental in shaping industries and driving successful businesses. Gartner cites there are already over 100 Chief Data Officers serving large enterprises today and that’s double the number from 2012. We believe that role will continue to emerge as a vital member of the C-suite charged with determining the most strategic way to make data a tangible business asset. But beyond that, every line of business worker will need to be able to understand data to drive decision-making from marketing and sales to create compelling customer experiences to HR departments needing to develop more precise ways to recruit, cultivate, develop and retain their top performers. Big Data is developing curiosity-driven and evidence-based cultures and workforces.

There are resources out there for students and professionals who want to explore a career in data. IBM is very committed to training tomorrow’s data workers and has partnerships with over 1,000 universities around the world to prepare students with big data skills. Going beyond just technology donation, IBM supports faculty with curriculum materials, case study projects based on real business challenges, and IBM data scientists who guest lecture in classes. IBM also launched http://BigDataUniversity.com, an online educational site of over 100,000 members run by new and experienced Hadoop, Big Data and DB2 users who want to learn, contribute with course materials, or look for job opportunities.


AR: 5. What book (or article) have you read recently and liked?

AB: "And the Mountains Echoed" by Khaled Hosseini.