Best Data Analytics Interview | Data Analyst Live Mock Interview | Must Watch - 2024 !!!

Summary

In this interview, Chris, an electronics and telecommunication engineering student, expresses his passion for data analytics. He shares his proficiency in SQL, Python, and Excel, and discusses his understanding of database transactions and their ACID properties. Chris also touches on the differences between OLTP and OLAP systems and his familiarity with Power BI, including calculated columns, measures, and DAX. He admits to being less versed in certain areas like broadcasting in AI and pandas' Group by function but shows eagerness to learn. The interview concludes with Chris highlighting his strengths, such as a strong drive for learning, and a weakness of perfectionism that can lead to delays.

Takeaways

• 👨‍💻 Chris is a final-year electronics and telecommunication engineering student with a strong interest in data analytics.
• 📈 He has a solid foundation in technical skills such as SQL, Python, Excel, and Power BI, which he has applied during internships and projects.
• 🔍 Chris discovered his passion for data analytics through internet research and a childhood fascination with numbers and patterns.
• 💡 He views data analytics as a career path that involves working with data to uncover trends and patterns, which aligns with his interests.
• 📊 Chris rates his proficiency in SQL as an 8 and has experience with window functions, although he admits to being less familiar with specific functions like 'RANK'.
• 💼 He understands the ACID properties of database transactions, emphasizing the importance of atomicity, consistency, integrity, and durability.
• 📊 Chris is less confident about the differences between OLTP and OLAP systems, acknowledging that he has heard of them but hasn't studied them in-depth.
• 📈 He rates his Excel skills at 7.5, with knowledge of functions like SUMPRODUCT, but is not well-versed in advanced topics like array formulas.
• 📊 In Power BI, Chris differentiates between calculated columns, which create new columns, and measures, which are aggregate calculations based on existing data.
• 🔐 He has a basic understanding of Row Level Security in Power BI, mentioning its connection to third-party involvement and data visualization.
• 🛠 Chris suggests optimizing Power BI reports by cleaning the data, using Power Query for ETL operations, and sharing the reports through the Power BI service.

Q & A

What is Chris's educational background?

Chris is in the last year of his electronics and telecommunication engineering program.

Why is Chris interested in data analytics?

Chris has always been passionate about numbers and problem-solving, which led him to develop an interest in data analytics.

What technical skills has Chris acquired during his studies?

Chris has acquired skills in SQL, Python, Excel, and Power BI.

What is Chris's proficiency level in SQL?

Chris rates his proficiency in SQL as a solid 8 on a scale.

Can you explain the concept of window functions in SQL as described by Chris?

Window functions in SQL are used to apply aggregate, ranking, and analytic functions over a set of rows, partitioned and ordered as specified.

How did Chris approach the task of finding the second highest salary in a table using SQL?

Chris mentioned using two methods: the LIMIT function and subqueries to find the second highest salary.

What is the concept of ACID properties in database transactions as understood by Chris?

Chris understands ACID properties as Atomicity, Consistency, Integrity, and Durability, which ensure the reliability and accuracy of database transactions.

What is the difference between OLTP and OLAP systems according to Chris?

Chris is not very well-versed in the difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems.

How proficient is Chris in Excel, and what functions is he familiar with?

Chris rates his proficiency in Excel at around 7.5. He is familiar with the SUM function but is not very well-versed with other functions like SUMPRODUCT.

What is the difference between calculated columns and measures in Power BI as described by Chris?

Chris explains that measures are like aggregated facts, such as the count of sales, while calculated columns create new columns based on existing data.

What is Chris's understanding of RLS (Row Level Security) in Power BI?

Chris has a basic understanding of RLS as a security feature that prevents unauthorized access to data in visualizations and dashboards.

How does Chris approach optimizing Power BI reports for performance?

Chris would start by cleaning the data, removing null values, and then use Power Query and various visualizations in Power BI to optimize the report.

What is Chris's experience with Python and pandas, particularly with the Group by function?

Chris is not very familiar with the Group by function in pandas, indicating a limited experience with Python for data manipulation.

What is Chris's perspective on the difference between a data scientist and a data analyst?

Chris sees the key difference as data scientists using machine learning to predict future outcomes, while data analysts work with existing data to create reports and draw conclusions.

What are Chris's strengths and weaknesses as he sees them?

Chris's strength is his strong enthusiasm and hunger for learning in the field of data analytics. His weakness is a tendency to focus excessively on making tasks perfect, which can lead to delays.

What projects has Chris worked on related to data analytics?

Chris has created various dashboards using Power BI and has worked on a patient monitoring system that involved storing data using SQL. He also conducted A/B testing during an internship.