A Guide to Success at Udaan.com Data Analytics Interviews Questions and Answers

Are you aspiring to join the dynamic world of data analytics at Udaan, one of India’s fastest-growing B2B marketplaces? Whether you’re a seasoned professional or a fresh graduate, preparing for an interview is key to landing your dream job. In this blog, we’ll delve into some common data analytics interview questions and provide insightful answers to help you shine during your interview at Udaan.

SQL Questions

Question: What are the main applications of SQL?

Answer: Using SQL, we can:

• create, delete, and update tables in a database
• access, manipulate, and modify data in a table
• retrieve and summarize the necessary information from a table or several tables
• add or remove certain rows or columns from a table

Question: What types of SQL commands (or SQL subsets) do you know?

Answer: Data Definition Language (DDL): for defining, modifying, and managing database structures.

• Data Manipulation Language (DML): for manipulating data within database tables.
• Data Control Language (DCL): for controlling access permissions and privileges on database objects.
• Transaction Control Language (TCL): for managing transactions within the database.
• Data Query Language (DQL): primarily consists of the SELECT command for retrieving data from the database.

Question: What SQL constraints do you know?

Answer: There are several types of SQL constraints:

• Primary Key Constraint: Ensures uniqueness of a column or combination of columns and enforces entity integrity.
• Foreign Key Constraint: Maintains referential integrity by establishing a relationship between tables based on a key column in one table that references the primary key in another table.
• Unique Constraint: Ensures that all values in a column or combination of columns are unique, similar to a primary key but allow NULL values.
• Check Constraint: Enforces specified conditions on the values allowed in a column, ensuring data integrity.
• Default Constraint: Specifies a default value for a column if no value is provided during an INSERT operation.

Question: What types of joins do you know?

Answer: In SQL, there are several types of joins used to combine data from multiple tables:

• Inner Join: Returns rows that have matching values in both tables based on the specified join condition.
• Left Join (or Left Outer Join): Returns all rows from the left table and matching rows from the right table. If there’s no match, NULL values are returned for columns from the right table.
• Right Join (or Right Outer Join): Returns all rows from the right table and matching rows from the left table. If there’s no match, NULL values are returned for columns from the left table.
• Full Join (or Full Outer Join): Returns all rows from both tables and matches rows where available. If there’s no match, NULL values are returned for the missing side.
• Cross Join (or Cartesian Join): Returns the Cartesian product of the two tables, meaning it combines each row from the first table with every row from the second table.
• Self Join: Joins a table with itself, typically used when comparing rows within the same table.

Question: What is a primary key?

Answer: A primary key is like a unique ID card for each row in a table. It helps keep things organized by making sure each row is different and can be easily found. Think of it as a special tag that says “this is me!” for each item in a list. Having a primary key makes searching for specific items faster and prevents any mix-ups. In simple terms, it’s a crucial part of how databases work, ensuring everything stays in order and is easy to manage.

Question: What is a Unique key?

Answer: A unique key is a special marker in a database table that ensures each row is different, just like having unique serial numbers on items in a store. It prevents duplicate entries, making data tidy and easy to manage. Unique keys are like fingerprints for rows, allowing quick and accurate identification. They’re important for maintaining order in databases and ensuring data quality.

Question: What is a foreign key?

Answer: A foreign key is a special column or set of columns in a database table that establishes a relationship between two tables. It points to the primary key column(s) in another table, creating a link between them. Think of it as a bridge connecting different parts of a database. Foreign keys ensure data integrity by enforcing referential integrity constraints, which means that values in the foreign key column(s) must correspond to values in the primary key column(s) of the referenced table. They’re essential for maintaining the relationships between tables and ensuring consistency in the data.

Question: What is the difference between a WHERE clause and a HAVING clause in SQL?

Answer: WHERE clause filters individual rows before any grouping or aggregation.

• It is applied to raw data based on specified conditions.
• HAVING clause filters aggregated data after grouping and aggregation.
• It is used with GROUP BY and aggregate functions.
• WHERE is used for row-level filtering, while HAVING is used for aggregate-level filtering.

Question: What is a Subquery in SQL?

Answer: A subquery in SQL, also known as a nested query or inner query, is a query nested within another query. It allows you to use the result of one query as a part of another query. Subqueries can appear in various parts of a SQL statement, such as the SELECT, FROM, WHERE, or HAVING clauses. They can be used to retrieve data based on dynamic conditions, perform comparisons, filter data, or even perform aggregate functions. Subqueries offer flexibility and enable complex data manipulation by breaking down tasks into smaller, more manageable parts.

Excel Questions

Question: What is the difference between COUNT, COUNTA, COUNTBLANK, and COUNTIF in Excel?

Answer:

COUNT:

• COUNT counts the number of cells in a range that contain numbers.
• It excludes empty cells, text, logical values, and errors.
• Example: =COUNT(A1:A10) counts the number of numeric values in cells A1 to A10.

COUNTA:

• COUNTA counts the number of non-empty cells in a range.
• It includes cells containing text, numbers, logical values, errors, and empty strings.
• Example: =COUNTA(A1:A10) counts all non-blank cells in cells A1 to A10.

COUNTBLANK:

• COUNTBLANK counts the number of empty cells in a range.
• It only counts cells that are truly empty.
• Example: =COUNTBLANK(A1:A10) counts the number of empty cells in cells A1 to A10.

COUNTIF:

• COUNTIF counts the number of cells in a range that meet a specific condition.
• It allows you to specify a criteria or condition to count cells that match.
• Example: =COUNTIF(A1:A10, “>10”) counts the number of cells in cells A1 to A10 that are greater than 10.

Question: What is a Pivot Table?

Answer: A Pivot Table is a data summarization tool in Microsoft Excel used for analyzing and presenting large datasets. It allows users to dynamically reorganize and manipulate data, enabling easy creation of custom reports and data analysis. With Pivot Tables, users can quickly group, filter, and summarize data by categories, facilitating the identification of trends and patterns. This feature is widely utilized in data analysis, business intelligence, and financial reporting for gaining insights and making informed decisions based on data.

Question: What function would you use to get the current date and time in Excel?

Answer: To obtain the current date and time in Excel, employ the NOW function, which provides both components. Simply input “=NOW()” in a cell to display the current date and time. This function updates automatically upon worksheet recalculations or openings, ensuring real-time data tracking. Utilize NOW for timestamping entries or dynamic calculations requiring the current date and time.

Python Questions

Question: What are built-in data types in Python?

Answer: In Python, built-in data types encompass a range of fundamental structures:

Numeric types include integers (int) and floating-point numbers (float).

Sequence types comprise lists (mutable), tuples (immutable), and ranges.

Mapping types are represented by dictionaries (dict), allowing key-value pairs.

Set types, including sets (mutable) and frozensets (immutable), contain unique elements.

Additionally, there are boolean (bool), string (str), and None types for truth values, text sequences, and null values, respectively. Understanding these types is crucial for effective data handling in Python.

Question: How to find duplicate values in a dataset?

Answer: To identify duplicate values in a dataset in Python, several methods can be employed:

Utilize Python sets to remove duplicates and compare lengths to find duplicates.

Implement the Counter class from the collections module to count occurrences of each value.

Alternatively, Pandas DataFrames offers a built-in duplicated() method to detect duplicate rows efficiently.

These methods provide flexible options for detecting and managing duplicate values based on the dataset’s structure and requirements.

Question: What is list comprehension in Python?

Answer: List comprehension in Python is a concise method for creating lists based on existing tables like lists, tuples, or ranges. It involves applying an expression to each element of the iterable and optionally filtering elements based on a condition. The syntax is straightforward, allowing you to define lists in a single line without the need for explicit loops. List comprehension enhances code readability and efficiency, making it a popular choice for list generation in Python programming.

Question: What are the different parts of a plot in Matplotlib?

Answer: In Matplotlib, a plot typically consists of several key components:

• Figure: The overall window or canvas where the entire plot is drawn. It encompasses all elements of the plot.
• Axes: The area within the figure where data is plotted. It includes the x-axis and y-axis along with ticks, labels, and other components.
• Axis Labels: Labels indicating the variables represented on the x-axis and y-axis, providing context to the data.
• Title: A descriptive title for the plot, summarizing its purpose or content.
• Data Points: The actual data points or lines plotted on the graph, representing the dataset being visualized.

Question: What is the difference between remove(), del(), and pop() in python?

Answer: In Python, remove(), del(), and pop() are methods used to remove elements from lists, but they differ in functionality:

• remove(): Removes the first occurrence of a specified value from a list, modifying it in place without returning the removed element.
• del(): Deletes an item or slice from a list by index or slice range, directly modifying the list in place without returning the removed element.
• pop(): Removes and returns an element from a specific index in the list, allowing you to store or manipulate the removed element.

General Data Analyst Questions

• Define the term ‘Data Wrangling in Data Analytics.
• What are the various steps involved in any analytics project?
• What are the best methods for data cleaning?
• What are the different types of sampling techniques used by data analysts?
• What are your strengths and weaknesses as a data analyst?
• How are data analysis libraries used in Python? What are some of the most common libraries?
• Is Python an object-oriented programming language?
• What is list comprehension in Python? Provide an example.
• How do you make a dropdown list in MS Excel?
• How does the AND() function work in Excel?
• Explain how VLOOKUP works in Excel.
• Explain the difference between modules and packages in Python.
• What are some common data visualization tools you have used?
• How does the graph of a decision tree look like?

Conclusion

Preparing for a data analytics interview at Udaan requires a solid understanding of data analysis concepts, strong technical skills, and the ability to communicate effectively. By familiarizing yourself with common interview questions and practicing your responses, you can confidently demonstrate your expertise and suitability for the role. Remember to showcase your problem-solving abilities, analytical thinking, and passion for leveraging data to drive business success. With thorough preparation and a positive attitude, you’re well on your way to excelling in your data analytics career at Udaan. Good luck!