28 May Part 1:As I am interested in working for a busines
Part 1:As I am interested in working for a business industry such as P&G a multinational consumer goods corporation. We assume that they want to analyze the data of all ice-cream brand. The first question designed to elicit the data needs is what data we need? For my industry, we need data from all ice-cream brand. For instance, if we want to know the annual sales of all the ice-cream brand, we can collect the sales data through our financial statement directly. The second question can be what do we do with data before analysis? This is because pre-processed is important such as check the missing value and deal with the outlier. These might be obstacles for the accuracy of our data analysis results and impact our findings and decision-making. So before analyzing data, we may spend much more time on pre-processed to ensure our data is accurate and clean.The first question when I anticipate being asked given my organization, leaders, colleague, and the business problem can be How was the data showing? This question helps us know what problem can data indicates to us. For example, the data may show the sales trend of the four-season in one year, we can know the business will dipping in winter, or sales may markedly increase for those brands who use superstar as their prolocutor to catch the customer. The second question is What method to use to analyze the data? For dealing with data, we use several methods; for example, build the linear/logistic models to find the relationship between each variable, or predict the data with time series.Part 2:I would like to work in the technology and entertainment and media provider industries like Netflix. It’s a data-driven company and has a lot of opportunities to get experience in product analytics and customer analytics. The first question I would like to ask a data analyst at companies like Netflix is how do you handle missing data? Specifically, what techniques would you recommend to handle missing data in users’ datasets? Taking care of missing values in the right way will increase the success rate in the customer targeting outcome. The second question is how to determine which metrics would you use for different AB testings? Large companies have a mature infrastructure developed to randomly select customers for group A and group B. How can a company without an infrastructure to select customers?Assuming that I’m working as a data scientist in the financial services industry like Paypal and I get a question from a sponsor asking potential customer growth during a specific timeframe. The first question I would like to be asked is where I get the data from? What are the data sources? It is important to ensure the data source is reliable so that the data quality will be reliable. When we work on solving business questions from our clients, we can clearly tell them that the outcome will be accurate and reliable. The second question I would like to be asked is what methodology and algorithms I use to solve a business question? I think that different approaches to solving a problem will eventually result in a slightly different insight.
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