Data Management, Data Science, and the growth of Data Education Worldwide: A DATAVERSITY™ Interview with Deepak Advani

by Charles Roe

In an effort to leverage the knowledge of some of the top minds in the Data Management industry, DATAVERSITY has been conducting a series of interviews on some of the most relevant topics in the field today. Recently, we interviewed Deepak Advani, IBM’s Vice President of Business Analytics Products & Solutions.

The primary focus of the interview was to question Mr. Advani on the work that IBM has been doing with universities around the world regarding new academic programs in Analytics and Data Science. Other aspects of the interview include a discussion of some of IBM’s other major academic partnerships, work with Big Data Initiatives, the evolution of Big Data, the need for more trained data professionals, and some of Mr. Advani’s opinions cognitive computing and other important topics.

DATAVERSITY (DV): What are the primary reasons for suggesting to schools like Northwestern that they offer a new Master’s Degree in Analytics or other advanced degrees in data?

Deepak Advani (DA):  As the world’s data grow exponentially, organizations are seeking new ways to tap information in traditional databases and unlock data tucked away in an unstructured format including videos, comments on social media sites and text messages.

The 2.5 quintillion bytes of “Big Data” we produce every day is everywhere – it is in every industry and touches all layers of a business, from the C-suite to entry-level. And this information overload shows no sign of stopping. In fact, IDC predicts total data volume will reach 35,000 exabytes in 2020, compared to 1,200 exabytes in 2010, representing a 29 fold increase over ten years.

Today, the key to business success is having the ability to capture, sift through, and analyze these vast amounts of data, presenting an enormous opportunity for companies to improve customer relationships, provide better services and generate insight to drive new business opportunities. However, Forrester estimates firms effectively utilize less than 5 percent of available data, mainly due to the lack of training and skills necessary for the type of information gathering and analysis needed to transform big data.

Key insights ranging from helping businesses operate more efficiently to gauging consumer sentiment to deliver the ultimate personalized shopping experience is causing data-driven jobs to migrate from the IT department to the boardroom. As data-related decisions continue to be made across enterprises, analytics skills are becoming increasingly sought-after.

Once thought to be a computer science-only discipline, analytics has morphed into an in-demand concentration in business and engineering schools. For example, the importance of competency in data analysis across businesses has been recognized by the Northwestern University McCormick School of Engineering, which recently partnered with IBM to launch two new Masters of Science degree programs with analytics concentrations.

Additionally, the University of Rochester Simon Graduate School of Business recently named three teams of winners in a case competition that challenged MBA and master of science students to explore real-world applications for Watson’s technology. Interestingly, two of top winning teams held concentrations in marketing – signaling the need for hands-on expertise in analytics is pushing outside the realm of computer science.

DV: IBM has recently teamed up with Rutgers to build a high-performance computing center (HPC) that will specifically focus on Big Data analytics. What are some of the main reasons for doing this? And do you see IBM working with more partners in the future for similar reasons?

DA: The Rutgers University new high performance computing center, which will house an IBM Blue Gene/P supercomputer, was created with several goals in mind. The center will act as an HPC resource for industry in New Jersey and the surrounding region as well as for Rutgers University faculty members and regional organizers who are expanding their use of extremely large data sets. The center will also aid in educating Rutgers students and the New Jersey workforce in working with advanced analytics in fields such as computer science, engineering, cancer and genetic research, and materials science, and will also familiarize them with working in a state-of-the-art center – all experiences they will need for a profession in the field of data science.

The HPC will help New Jersey become a processing hub for the hottest natural resource on the planet – data – and is the only supercomputer available to commercial users in the state.

IBM is already working with schools like the University of Louisville and the Rensselaer Polytechnic Institute on supercomputer systems. IBM’s plans are to continue these types of partnerships and expand them to focus on new types of research, which can have a positive economic impact on the communities they are based in.

DV: There have been numerous studies the past couple of years that claim there is a current lack and future lack of trained data professionals. How is IBM working to address this issue?

DA: As we enter a new era of cognitive systems, IBM is using Watson to help spark student interest in the most advanced technology to inspire future leaders and innovators. Cognitive systems like IBM’s Watson system are able to look at information from a variety of sources. Using analytics, these systems can build relationships between data sets. By processing and reprocessing information, these new “thinking machines” can become more accurate over time to help cull insights that can help tackle some of the world’s complexities and most pressing issues.

Recognizing the need – and desire – for companies to employ business and technology professionals that are armed with the knowledge and skills necessary to apply the latest advanced technologies, IBM is initiating programs with educational institutions worldwide that will prepare students for post-graduation work within the big data industry.

Since 2002, IBM has nurtured an academic program by partnering with more than 6,000 universities across the globe to help meet this demand and keep the evolving global workforce strong. In the area of analytics, specifically, IBM is currently working with more than 200 academic organizations globally to expand and strengthen analytics curricula to meet the growing demand of highly skilled analytics business workers of the future. What’s unique about IBM’s initiatives is that we are working with Business Schools to develop new course curricula and merge business and IT skills.

Schools include universities such as: Fordham, Yale School of Management, DePaul, Syracuse, Northwestern, University of Rochester Simon School of Business, University of West Scotland, Indian Institute of Management Calcutta, Xi’an Jiao Tong University, University of Ulster, IAE Aix-en-Provence, EDC business school in France, and Ottawa University Telfer School of Management.

IBM offers colleges and universities access to the latest advances in analytics technology and business industry expertise, curriculum materials, project-focused case studies for students to gain hands-on experience in analytics, access to a wide spectrum of software solutions, IBM thought leaders as guest speakers, as well as faculty awards to accelerate program.

By partnering with these universities, IBM hopes to provide students the requisite analytics skills they will need to be able to apply to real business jobs when they graduate.

DV: Do you see a problem with current university education in terms of preparing students for jobs in Data Management and specifically Big Data? If yes, what would you recommend as some of the major changes that need to be enacted by universities to alleviate this problem in the future?

DA: As universities prepare students for future job opportunities, it is important to look beyond traditional computer science and engineering courses. Rather, incorporating analytics and evidence-based reasoning across all areas of business ranging from marketing to economics and brand development to entrepreneurship allows students combine their technical savvy and business skills.

The knowledge gained through a business class is only valuable if and when students apply the lessons of their coursework in the real world. Outside case studies and textbooks, IBM is teaming with universities to take a hands-on approach, making the learning experience unforgettable. Here are a few video examples:

· First Academic Case Competition Proposes Novel Ways to Put IBM Watson to Work
· IBM Collaborates with Northwestern University to Launch Two New Masters Degree Programs
· Yale SOM and IBM Prepare Students with Analytics Skills for Next Generation of Jobs
· DePaul University Center for Data Mining & Predictive Analytics – Jonathan G.

DV: What are some of the primary skills that students leaving university need to be able to move into Big Data jobs?

DA: Students entering the field of data science upon graduation will need to develop mathematical and statistical skills and gain experience with advanced computational and data analysis. Students will need to understand how to identify patterns and trends, know how to interpret and gain insight from the data and communicate their findings in effective business language. Skills related to predictive, descriptive and prescriptive data analysis will also be necessary. To be an effective addition to the business world, students should also look to supplement their mathematical study with courses that will increase their business acumen which is why we are seeing this trend of analytics training being integrated into business school curriculum in particular.

DV: Do you see a need for the growth of Data Science courses at the university level?

DA: As mentioned, generally, those interested in pursuing a career in data science should complete course in modeling, data mining and analytics. While this functional expertise cannot guarantees success, it is critical that a data scientist have the ability to be creative and analytical, while also being willing to explore new sources of data both within and outside the enterprise.

While courses may not need to focus on data science, specifically, it is imperative that education institutions begin to more fully embrace holistic data science programs of study, wherein students will enroll in a number of mathematical, statistical and business-related classes that will help them prepare for and gain experience in the field of data science.

DV: Do you believe that Data Science will be a more important trend going into the future?

DA: Yes. Data Scientists work to find actionable trends and patterns in Big Data by examining and establishing what questions should be asked, which data should be collected and connects IT strategy to the broader business challenges. These are all tasks that won’t soon become obsolete, as data is not useful until patterns are identified and context and intelligence are applied, and often, data scientists work with executives to provide critical counsel on how to maximize business value. Given this, the position of the data scientist can be considered a change agent since the individual innovates the way organizations leverage information and incorporates new actions into the operations.

Reports from Indeed.com show there are currently 10,000 job openings for this role from a broad variety of companies – from deal-of-the-day websites, retailers and consumer goods companies. As an emerging career path, data scientists are at the core of organizational success with Big Data to help businesses better understand their consumer.

DV: What do you believe is the greatest need in terms of university data education? How might universities start addressing such a need?

DA: The University of Rochester Simon Graduate School of Business has always taken an analytical approach to coursework. Over the course of their studies, students at the Simon School master the FACt approach (Frame, Analyze, Communicate) to handle unstructured problems: they first frame the issue in the context of economics, analyze each dimension of the problem, and then come to a decision that must be communicated throughout the organization.

With the help of IBM and the recent Simon School case competition, the Simon School took the learning experience one step further. The students were asked to look at industries that the Watson technology could be used to manage information from a variety of sources to create long-lasting value to all business stakeholders.

This type of open-ended question required students to think differently and more critically about how technology can be applied to solve business challenges. The teams were evaluated based on the ability of the students to clearly articulate the business case including market research, tactical planning and feasibility while exhibiting an understanding of how to harness Big Data for strategic outcomes.

This type of hands-on learning experience helped students become familiar with new technologies such as analytics and cognitive computing that are re-defining businesses and transforming entire industries.

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