Now, I’d like to introduce you to Shambahvi Vashishtha, who is a Business Analyst at Opera Solutions. >> Hello, this is Shambahvi Vashishtha. I’m going to be working a Business Analyst with Opera Solutions. I did my Master’s in Mathematics back in India, and then I did another Master’s of Engineering Management from Duke University. I have taken multiple courses of Professor Daniel Adder, and I have absolutely enjoyed them. I'm going to talk about how I use them into my corporate life. So Opera Solutions is a big data analytics, and we have clients over multiple industries. We are right now catering to travel, healthcare, retail, capital markets, private equity, these sectors. Opera Solutions started in 2004 so it's been 11 years. We have grown into a big company, we have offices overseas. We have offices in India, Shanghai, London, and in US we have locations in Boston, New York, and San Diego. We currently have more than 500 employees in US itself. And we keep growing. So as a business analyst, I have worked with different industries. Currently, I'm working with a retail client, and it's a Fortune 50. They are working towards their personalization effort, as you can imagine. That everybody wants to see offers customized to them. We are working towards that effort. So we prepare different stories on different analyses and we take different grafts and cuts on the data and then put it into a PowerPoint site, build a story around it, and then present it to our clients. And if they like something, then we execute it. To a retail company, loyalty is very important because you want to maintain loyalty of your customers. You want them to come again and again and shop with you. That's why you want to make their experience better and better every day. That's why you want to customize their shopping experience. Our metrics is, we want to improve their trips, we want to improve their basket, and we want to improve our margins and our profits from them. So, number of items in your basket, value of shopping. We would like to improve that. We want you to explore different aisles in a retail store. We would want you to spend more with us and on things that are important to you, so we would send you offers which are relevant to you. So business analysts, they actually build a bridge to non technical people and technical people, because I explain the analysis to my analyst that is super, super technical, then I explain the findings to the client, which has to be totally business oriented and no technical terms. So when you are a business analyst you have different audiences to cater to. My audiences would be my business client, my other audience would be my technical team to whom I have to explain how to build the models and what kind of outcome I'm expecting. Unless the outcome is there I try to put it into very plain words to explain it to business people so that they're able to make the right decision and they have all the information that they require for making decisions. So once we started working with this client we got a huge data dump and we had to clean it up. The different kind of cleaning processes that I know of that we used were text matching, removing spaces, removing hyphens, and anything that could make noise to your data. After that we started using SQL and I, we used my SQL to run all the queries and to get all the data that is required for us. Once I get the clean data from my analysts, I put that into Excel, and I bring up different charts and graphs to analyse where the opportunities are. Once we find a bit of opportunities, we have to develop a story around it and we develop the story on PowerPoint. We have to come up with different data points to support our hypothesis, that if you do this this is gonna happen. And then you support it with some data points, some graphs and some charts and then you present it to the client because the clients know most about their business, if it makes sense then we execute it. So once I get the team data, I put it in Excel. Excel is a very powerful tool and is bread and butter to most of the analysts. I create different cuts and graphs and charts in Excel to prepare my story. Once I see there is something standing out, I would deep dive into it and again Excel is a tool for it. Tables that you want to do Excel is right there for you. In corporate life you get open-ended problems, you really don't know the solution because you have to come up with it. And data mining did that for me. It would, the course would give us opportunity to explore different kinds of problems, different type of problem solving skills and then come up with multiple solutions and then probably figure out as a team which one works best for that particular kind of a problem. Because whenever you are solving a problem you solve it as a team. And all your team expects is that you ask the right questions and you are moving in the right direction. So I work with great people, we have a great team, and I have a team of statistician and mathematicians who are working with us who will build a actual model for us. I would give them business requirement. Say, for example, my requirement is I want to analyze all my customers. But it's difficult to analyze them on an individual basis. So I would want to profile them. Yeah, so I would ask my team members to build me a model which would give me an output of different clusters. They will be combining customers into different clusters based on their spend, based on their behaviors, spending pattern, based on what they purchase, what they like, how often they come, and etc. So this is the profiling exercise, and that's how you don't have to go on an individual level, but you can combine them together and give them out something that is very relevant to them.
