Visha Chadha ’15 spent last summer in Seattle working at Microsoft, where she interned as a product marketing manager intern. After graduation she will return full time to Microsoft and do product management/marketing in the company’s cloud computing group and work on Microsoft Azure.
One of the most valuable realizations Chadha had as a Microsoft intern was how she constantly applied lessons learned in Kellogg’s data analytics courses.
Chadha, who previously designed semiconductor chips for microprocessors and smartphones at AMD (Advanced Micro Devices), took time to talk about why it was important to build a strong foundation in data analytics while at Kellogg.
Why was it important for you to focus on data analytics?
Today, we’re living in a world where things are changing at a much faster pace than they ever did in the past. Technology is disrupting any and every industry, and it is becoming much harder to stay competitive and gain market leadership consistently. On top of that, the convergence of social, mobile, cloud and big data technologies poses new requirements of getting the right information to the consumer as quickly as possible.
No matter which path I chose to pursue after school, it was clear to me that data-driven insights and strategies are key to becoming an important point of competitive differentiation for organizations.
What were some of the most impactful courses you took?
Kellogg offers a range of exciting courses in data analytics. My interests are primarily in technology, marketing and entrepreneurship, so I chose to take analytics courses across these disciplines. A few interesting analytics courses I took were:
- Social Dynamics and Network Analytics
In this course, we learned the science behind virality and contagion, and we analyzed why some things go viral over others. We also learned the power of social networks, social media, wisdom of crowds, prediction markets and social capital and how they can be applied to organizational growth and competitiveness.
- Startup Programming
We used Ruby on Rails framework to build a simple database-backed web application and deploy it to a production server.
- Programming for Analytics
In this course, we used Python, one of the most popular languages used in app development and data analytics, and learned how to design software systems for analytics.
- Entrepreneurial Tools for Digital Marketing
This course focused on the customer relationship funnel on web/mobile channels. We learned basic concepts of UI/UX, A/B testing, SEO, SEM, conversion funnels, Google Analytics, and Google Webmaster Tools and how they can be applied to effective digital marketing strategies.
- Retail Analytics, Pricing and Promotions
In this course, we used data from field experiments to gain a deeper understanding of consumer and firm behavior and how we can use data to make informed pricing and retailing decisions.
What will you be doing at Microsoft?
I’m part of a one-year rotation program and will do three rotations of four months each in different functions within Azure. My role will be primarily inbound focused, which involves business planning, building pricing/licensing/subscription models, analyzing existing and new market opportunities for specific products and services, and assessing B2B partnerships.
How do you think your data analytics coursework will set you up for success at Microsoft and beyond?
I interned at Microsoft last summer in the same group and my project revolved around building models to identify and analyze strategic partnerships for their new Internet of things service. We were able to use real-time data to generate meaningful insights into which type of partnerships would be most effective.
I used a lot of concepts from the analytics courses I took in my first year for my internship project. That has further strengthened my belief in the power of using data analytics as an effective means towards gaining a competitive edge for organizations.
I also think that focusing on analytics, especially early on, will help build a strong foundation in developing a comprehensive skill set, as well as a sharp business acumen, in the long term.
In your mind, what stands out about Kellogg’s approach to data analytics?
Kellogg has a very strong and practical approach to data analytics for a few reasons.
First, the faculty at Kellogg is at the forefront of data analytics and data science, and that ensures that you’re learning from the very best.
Second, all courses take a data-driven approach to solving business problems to come up with the most effective solutions.
Finally, I feel like Kellogg takes a very practical approach to using data to solve real world problems. As one of our professors rightly said, “Any model will always give you a result as long as you input some data into that model. So, you could still be analyzing data but not getting the desired results. It is definitely important to learn how to model and crunch all the numbers but it is much more important to ask the right questions to make sure you’re solving the right problem to get to the desired outcome.” That has stuck with me ever since.
Is there anything else you would tell prospective students about data analytics at Kellogg?
Kellogg recognizes that big data and analytics matter in today’s business world like never before. In the past few years, a number of new courses have been introduced focused on data analytics and how managers can be more effective at establishing analytics competence across all areas of an organization. These courses are taught by some of the best professors in the school.
Last year, a group of students formed a Big Data and Analytics club, which is another great step. The club organizes exciting big data events and brings in guest speakers from the business world that talk about how they use data in their organizations to gain a competitive edge. This helps the students get a holistic understanding of how all the concepts we learn in the classroom are applied in the real world.