Data science interview questions 👇

𝗦𝗤𝗟
- How do you write a query to fetch the top 5 highest salaries in each department?
- What’s the difference between the HAVING and WHERE clauses in SQL?
- How do you handle NULL values in SQL, and how do they affect aggregate functions?

𝗣𝘆𝘁𝗵𝗼𝗻
- How do you handle large datasets in Python, and which libraries would you use for performance?
- What are context managers in Python, and how do they help with resource management?
- How do you manage and log errors in Python-based ETL pipelines?

𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
- Explain the difference between bias and variance in a machine learning model. How do you balance them?
- What is cross-validation, and how does it improve the performance of machine learning models?
- How do you deal with class imbalance in classification tasks, and what techniques would you apply?

𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
- What is the vanishing gradient problem in deep learning, and how can it be mitigated?
- Explain how a convolutional neural network (CNN) works and when you would use it.
- What is dropout in neural networks, and how does it help prevent overfitting?

𝗗𝗮𝘁𝗮 𝗪𝗿𝗮𝗻𝗴𝗹𝗶𝗻𝗴
- How would you handle outliers in a dataset, and when is it appropriate to remove or keep them?
- Explain how to merge two datasets in Python, and how would you handle duplicate or missing entries in the merged data?
- What is data normalization, and when should you apply it to your dataset?

𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - 𝗧𝗮𝗯𝗹𝗲𝗮𝘂
- How do you create a dual-axis chart in Tableau, and when would you use it?
- How would you filter data in Tableau to create a dynamic dashboard that updates based on user input?
- What are calculated fields in Tableau, and how would you use them to create a custom metric?

#datascience #interview

𝟱 𝗙𝗿𝗲𝗲 𝗠𝗜𝗧 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗵𝗮𝘁 𝗪𝗶𝗹𝗹 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿😍

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Data Analyst INTERVIEW QUESTIONS AND ANSWERS
👇👇

1.Can you name the wildcards in Excel?

Ans: There are 3 wildcards in Excel that can ve used in formulas.

Asterisk (*) – 0 or more characters. For example, Ex* could mean Excel, Extra, Expertise, etc.

Question mark (?) – Represents any 1 character. For example, R?ain may mean Rain or Ruin.

Tilde (~) – Used to identify a wildcard character (~, *, ?). For example, If you need to find the exact phrase India* in a list. If you use India* as the search string, you may get any word with India at the beginning followed by different characters (such as Indian, Indiana). If you have to look for India” exclusively, use ~.

Hence, the search string will be india~*. ~ is used to ensure that the spreadsheet reads the following character as is, and not as a wildcard.


2.What is cascading filter in tableau?

Ans: Cascading filters can also be understood as giving preference to a particular filter and then applying other filters on previously filtered data source. Right-click on the filter you want to use as a main filter and make sure it is set as all values in dashboard then select the subsequent filter and select only relevant values to cascade the filters. This will improve the performance of the dashboard as you have decreased the time wasted in running all the filters over complete data source.


3.What is the difference between .twb and .twbx extension?

Ans:
A .twb file contains information on all the sheets, dashboards and stories, but it won’t contain any information regarding data source. Whereas .twbx file contains all the sheets, dashboards, stories and also compressed data sources. For saving a .twbx extract needs to be performed on the data source. If we forward .twb file to someone else than they will be able to see the worksheets and dashboards but won’t be able to look into the dataset.


4.What are the various Power BI versions?

Power BI Premium capacity-based license, for example, allows users with a free license to act on content in workspaces with Premium capacity. A user with a free license can only use the Power BI service to connect to data and produce reports and dashboards in My Workspace outside of Premium capacity. They are unable to exchange material or publish it in other workspaces. To process material, a Power BI license with a free or Pro per-user license only uses a shared and restricted capacity. Users with a Power BI Pro license can only work with other Power BI Pro users if the material is stored in that shared capacity. They may consume user-generated information, post material to app workspaces, share dashboards, and subscribe to dashboards and reports. Pro users can share material with users who don’t have a Power BI Pro subnoscription while workspaces are at Premium capacity.

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𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗙𝗿𝗼𝗺 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀😍

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Useful Python for data science cheat sheets 👇

𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 & 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗔𝗜 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗟𝗮𝗻𝗱 𝗧𝗼𝗽 𝗝𝗼𝗯𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱😍

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1.Define RDBMS.

Answer: Relational Database Management System(RDBMS) is based on a relational model of data that is stored in databases in separate tables and they are related to the use of a common column. Data can be accessed easily from the relational database using Structured Query Language (SQL).

2.Define DML Compiler.

Answer: DML compiler translates DML statements in a query language into a low-level instruction and the generated instruction can be understood by Query Evaluation Engine.

3.Explain the terms ‘Record’, ‘Field’ and ‘Table’ in terms of database.

Answer:

Record: Record is a collection of values or fields of a specific entity. For Example, An employee, Salary account, etc.

Field: A field refers to an area within a record that is reserved for specific data. For Example, Employee ID.

Table: Table is the collection of records of specific types. For Example, the Employee table is a collection of records related to all the employees.

4.Define the relationship between ‘View’ and ‘Data Independence’.

Answer: View is a virtual table that does not have its data on its own rather the data is defined from one or more underlying base tables.

Views account for logical data independence as the growth and restructuring of base tables are not reflected in views.

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SQL (Structured Query Language) is a standard programming language used to manage and manipulate relational databases. Here are some key concepts to understand the basics of SQL:

1. Database: A database is a structured collection of data organized in tables, which consist of rows and columns.

2. Table: A table is a collection of related data organized in rows and columns. Each row represents a record, and each column represents a specific attribute or field.

3. Query: A SQL query is a request for data or information from a database. Queries are used to retrieve, insert, update, or delete data in a database.

4. CRUD Operations: CRUD stands for Create, Read, Update, and Delete. These are the basic operations performed on data in a database using SQL:
   - Create (INSERT): Adds new records to a table.
   - Read (SELECT): Retrieves data from one or more tables.
   - Update (UPDATE): Modifies existing records in a table.
   - Delete (DELETE): Removes records from a table.

5. Data Types: SQL supports various data types to define the type of data that can be stored in each column of a table, such as integer, text, date, and decimal.

6. Constraints: Constraints are rules enforced on data columns to ensure data integrity and consistency. Common constraints include:
   - Primary Key: Uniquely identifies each record in a table.
   - Foreign Key: Establishes a relationship between two tables.
   - Unique: Ensures that all values in a column are unique.
   - Not Null: Specifies that a column cannot contain NULL values.

7. Joins: Joins are used to combine rows from two or more tables based on a related column between them. Common types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).

8. Aggregate Functions: SQL provides aggregate functions to perform calculations on sets of values. Common aggregate functions include SUM, AVG, COUNT, MIN, and MAX.

9. Group By: The GROUP BY clause is used to group rows that have the same values into summary rows. It is often used with aggregate functions to perform calculations on grouped data.

10. Order By: The ORDER BY clause is used to sort the result set of a query based on one or more columns in ascending or descending order.

Understanding these basic concepts of SQL will help you write queries to interact with databases effectively. Practice writing SQL queries and experimenting with different commands to become proficient in using SQL for database management and manipulation.

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1. What are the different subsets of SQL?

Data Definition Language (DDL) – It allows you to perform various operations on the database such as CREATE, ALTER, and DELETE objects.
Data Manipulation Language(DML) – It allows you to access and manipulate data. It helps you to insert, update, delete and retrieve data from the database.
Data Control Language(DCL) – It allows you to control access to the database. Example – Grant, Revoke access permissions.

2. List the different types of relationships in SQL.

There are different types of relations in the database:
One-to-One – This is a connection between two tables in which each record in one table corresponds to the maximum of one record in the other.
One-to-Many and Many-to-One – This is the most frequent connection, in which a record in one table is linked to several records in another.
Many-to-Many – This is used when defining a relationship that requires several instances on each sides.
Self-Referencing Relationships – When a table has to declare a connection with itself, this is the method to employ.

3. What is a Stored Procedure?

A stored procedure is a subroutine available to applications that access a relational database management system (RDBMS). Such procedures are stored in the database data dictionary. The sole disadvantage of stored procedure is that it can be executed nowhere except in the database and occupies more memory in the database server.

4. What is Pattern Matching in SQL?

SQL pattern matching provides for pattern search in data if you have no clue as to what that word should be. This kind of SQL query uses wildcards to match a string pattern, rather than writing the exact word. The LIKE operator is used in conjunction with SQL Wildcards to fetch the required information.

𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝘄𝗶𝘁𝗵 𝗧𝗵𝗶𝘀 𝗔𝗜 𝗧𝗼𝗼𝗹 𝗘𝘃𝗲𝗿𝘆 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗡𝗲𝗲𝗱𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱!😍

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Starting your journey as a data analyst is an amazing start for your career. As you progress, you might find new areas that pique your interest:

• Data Science: If you enjoy diving deep into statistics, predictive modeling, and machine learning, this could be your next challenge.

• Data Engineering: If building and optimizing data pipelines excites you, this might be the path for you.

• Business Analysis: If you're passionate about translating data into strategic business insights, consider transitioning to a business analyst role.

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