Master in Data Science (SMS, TU) Fundamentals of Data Science Question Paper 2081 Nepal

Data science is often considered a blurry subject. What do you think are the reasons behind it?

Discuss the importance of data validation in data science. Name some common methods of data validation.

What do you mean by time series analysis? What are the frequent patterns observed in time series analysis?

Describe the common data enrichment techniques often used by data scientist.

Write short notes on:

a. Stereotyping b. Data Lake

Define and explain the TDSP lifecycle in data science.

OR

A leading retail chain in Nepal wants to use data science to enhance its customer experience and optimize inventory management. They have data from customer transactions, online browsing behavior, and social media interactions.

Briefly explain how data science can be applied in the retail industry to improve customer experience and optimize inventory management. Provide specific examples of data science techniques that could be used in this context.

Describe the common data quality issues with tabular data and their mitigation techniques with appropriate examples.

How does machine learning differs from traditional learning? Explain the various type of machine learning techniques.

Explain the generic process of real time data analytics in big data in context to Apache Kafka.

OR

Apply map-reduce paradigm to the following set of data:

Data, Science, Engineering Engineering, Data, Analytics Analytics, Intelligence, Science

You are analyzing a dataset containing information about customer orders for an e-commerce platform. However, upon initial inspection, you notice several data quality issues that may impact the reliability of your analysis.

Describe the common data quality issues that you may have identified in the dataset, providing specific examples for each issue. Explain the potential consequences of these issues on your analysis and propose strategies to address them effectively.