1. Does SQL support programming language features?
It is true that SQL is a language, but it does not support programming as it is not a programming language, it is a command language. We do not have some programming concepts in SQL like for loops or while loop, we only have commands which we can use to query, update, delete, etc. data in the database. SQL allows us to manipulate data in a database.

2. What is a trigger?
Trigger is a statement that a system executes automatically when there is any modification to the database. In a trigger, we first specify when the trigger is to be executed and then the action to be performed when the trigger executes. Triggers are used to specify certain integrity constraints and referential constraints that cannot be specified using the constraint mechanism of SQL.

3. What are aggregate and scalar functions?
For doing operations on data SQL has many built-in functions, they are categorized into two categories and further sub-categorized into seven different functions under each category. The categories are:
Aggregate functions:
These functions are used to do operations from the values of the column and a single value is returned.
Scalar functions:
These functions are based on user input, these too return a single value.

4. Define SQL Order by the statement?
The ORDER BY statement in SQL is used to sort the fetched data in either ascending or descending according to one or more columns.
By default ORDER BY sorts the data in ascending order.
We can use the keyword DESC to sort the data in descending order and the keyword ASC to sort in ascending order.

5. What is the difference between primary key and unique constraints? 
The primary key cannot have NULL values, the unique constraints can have NULL values. There is only one primary key in a table, but there can be multiple unique constraints. The primary key creates the clustered index automatically but the unique key does not.

matplotlib beginner's code guide 🔥🚀

Data Analytics Interview Preparation Series Part-1
[Questions with Answers]

Why did you want your job?

I was originally studying physics but didn't want to do a PhD. So, after my master’s I decided I would try a job working with data. I noticed that it was quite common for people studying science to go into data after. I had several friends who went on to become data scientists directly after their undergrad.
I noticed that given my background in maths and some noscripting in Python (thanks to computational physics classes), it wouldn't be too hard to make the jump. 
I went into data science because I wanted a more mathematical role with a research component (model design, experimentation, metric design etc.) 
This was instead of a more practical role like data analysis or data engineering. 
It turned out to be a cool choice and I'm enjoying my time as a data scientist right now! 

Why did you choose the industry that you work in?

I work in a music-tech start up. I love it because I make music on the side. Being able to work in 
music and be surrounded by people who are also passionate about music is very cool! 
The company organizes concerts with artists that we work with etc. It's really cool! This makes the job more interesting for me, given that it's so tightly related to what I love to do.

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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If you are trying to transition into the data analytics domain and getting started with SQL, focus on the most useful concept that will help you solve the majority of the problems, and then try to learn the rest of the topics:

👉🏻 Basic Aggregation function:
1️⃣ AVG
2️⃣ COUNT
3️⃣ SUM
4️⃣ MIN
5️⃣ MAX

👉🏻 JOINS
1️⃣ Left
2️⃣ Inner
3️⃣ Self (Important, Practice questions on self join)

👉🏻 Windows Function (Important)
1️⃣ Learn how partitioning works
2️⃣ Learn the different use cases where Ranking/Numbering Functions are used? ( ROW_NUMBER,RANK, DENSE_RANK, NTILE)
3️⃣ Use Cases of LEAD & LAG functions
4️⃣ Use cases of Aggregate window functions

👉🏻 GROUP BY
👉🏻 WHERE vs HAVING
👉🏻 CASE STATEMENT
👉🏻 UNION vs Union ALL
👉🏻 LOGICAL OPERATORS

Other Commonly used functions:
👉🏻 IFNULL
👉🏻 COALESCE
👉🏻 ROUND
👉🏻 Working with Date Functions
1️⃣ EXTRACTING YEAR/MONTH/WEEK/DAY
2️⃣ Calculating date differences

👉🏻CTE
👉🏻Views & Triggers (optional)

Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz

Share with credits: https://news.1rj.ru/str/sqlspecialist

Hope it helps :)

Can you use ChatGPT as a data analyst 👇
https://news.1rj.ru/str/jobinterviewsprep/138

Meesho Data Analyst interview experience (0-3) -


Power BI Questions:

1. Explain the concept of context transition in DAX and provide an example.
2. How would you optimize a complex Power BI report for faster performance?
3. Describe the process of creating and using calculation groups in Power BI.
4. Explain how you would handle large datasets in Power BI without compromising performance.
5. What is a composite model in Power BI, and how can it be used effectively?
6. How does the USERELATIONSHIP function work, and when would you use it?
7. Describe how to use Power Query M language for advanced data transformations.
8. Explain the difference between CROSSFILTER and TREATAS in DAX.

SQL Questions:

1. How would you optimize a slow-running query with multiple joins?
2. What is a recursive CTE, and can you provide an example of when to use it?
3. Explain the difference between clustered and non-clustered indexes and when to use each.
4. Write a query to find the second highest salary in each department.
5. How would you detect and resolve deadlocks in SQL?
6. Explain window functions and provide examples of ROW_NUMBER, RANK, and DENSE_RANK.
7. Describe the ACID properties in database transactions and their significance.
8. Write a query to calculate a running total with partitions based on specific conditions.

1. Define the term 'Data Wrangling.

Data Wrangling is the process wherein raw data is cleaned, structured, and enriched into a desired usable format for better decision making. It involves discovering, structuring, cleaning, enriching, validating, and analyzing data. This process can turn and map out large amounts of data extracted from various sources into a more useful format.

2. What are the best methods for data cleaning?

Create a data cleaning plan by understanding where the common errors take place and keep all the communications open. Before working with the data, identify and remove the duplicates. This will lead to an easy and effective data analysis process.Focus on the accuracy of the data. Set cross-field validation, maintain the value types of data, and provide mandatory constraints.Normalize the data at the entry point so that it is less chaotic. You will be able to ensure that all information is standardized, leading to fewer errors on entry.


3. Explain the Type I and Type II errors in Statistics?

In Hypothesis testing, a Type I error occurs when the null hypothesis is rejected even if it is true. It is also known as a false positive.

A Type II error occurs when the null hypothesis is not rejected, even if it is false. It is also known as a false negative.

4. How do you make a dropdown list in MS Excel?

First, click on the Data tab that is present in the ribbon.Under the Data Tools group, select Data Validation.Then navigate to Settings > Allow > List.Select the source you want to provide as a list array.

5. State some ways to improve the performance of Tableau?

Use an Extract to make workbooks run faster.
Reduce the scope of data to decrease the volume of data.
Reduce the number of marks on the view to avoid information overload.
Hide unused fields.
Use Context filters.
Use indexing in tables and use the same fields for filtering.
Remove unnecessary calculations and sheets.

1. What are Query and Query language?

A query is nothing but a request sent to a database to retrieve data or information. The required data can be retrieved from a table or many tables in the database.

Query languages use various types of queries to retrieve data from databases. SQL, Datalog, and AQL are a few examples of query languages; however, SQL is known to be the widely used query language.



2. What are Superkey and candidate key?

A super key may be a single or a combination of keys that help to identify a record in a table. Know that Super keys can have one or more attributes, even though all the attributes are not necessary to identify the records.

A candidate key is the subset of Superkey, which can have one or more than one attributes to identify records in a table. Unlike Superkey, all the attributes of the candidate key must be helpful to identify the records.


3. What do you mean by buffer pool and mention its benefits?

A buffer pool in SQL is also known as a buffer cache. All the resources can store their cached data pages in a buffer pool. The size of the buffer pool can be defined during the configuration of an instance of SQL Server.
The following are the benefits of a buffer pool:

Increase in I/O performance
Reduction in I/O latency
Increase in transaction throughput
Increase in reading performance


4. What is the difference between Zero and NULL values in SQL?

When a field in a column doesn’t have any value, it is said to be having a NULL value. Simply put, NULL is the blank field in a table. It can cancel be considered as an unassigned, unknown, or unavailable value. On the contrary, zero is a number, and it is an available, assigned, and known value.

Here are some commonly asked SQL interview questions along with brief answers:

1. What is SQL?
   - SQL stands for Structured Query Language, used for managing and manipulating relational databases.

2. What are the types of SQL commands?
   - SQL commands can be broadly categorized into four types: Data Definition Language (DDL), Data Manipulation Language (DML), Data Control Language (DCL), and Transaction Control Language (TCL).

3. What is the difference between CHAR and VARCHAR data types?
   - CHAR is a fixed-length character data type, while VARCHAR is a variable-length character data type. CHAR will always occupy the same amount of storage space, while VARCHAR will only use the necessary space to store the actual data.

4. What is a primary key?
   - A primary key is a column or a set of columns that uniquely identifies each row in a table. It ensures data integrity by enforcing uniqueness and can be used to establish relationships between tables.

5. What is a foreign key?
   - A foreign key is a column or a set of columns in one table that refers to the primary key in another table. It establishes a relationship between two tables and ensures referential integrity.

6. What is a JOIN in SQL?
   - JOIN is used to combine rows from two or more tables based on a related column between them. There are different types of JOINs, including INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

7. What is the difference between INNER JOIN and OUTER JOIN?
   - INNER JOIN returns only the rows that have matching values in both tables, while OUTER JOIN (LEFT, RIGHT, FULL) returns all rows from one or both tables, with NULL values in columns where there is no match.

8. What is the difference between GROUP BY and ORDER BY?
   - GROUP BY is used to group rows that have the same values into summary rows, typically used with aggregate functions like SUM, COUNT, AVG, etc., while ORDER BY is used to sort the result set based on one or more columns.

9. What is a subquery?
   - A subquery is a query nested within another query, used to return data that will be used in the main query. Subqueries can be used in SELECT, INSERT, UPDATE, and DELETE statements.

10. What is normalization in SQL?
    - Normalization is the process of organizing data in a database to reduce redundancy and dependency. It involves dividing large tables into smaller tables and defining relationships between them to improve data integrity and efficiency.

Around 90% questions will be asked from sql in data analytics interview, so please make sure to practice SQL skills using websites like stratascratch. ☺️💪

Planning for Data Science or Data Engineering Interview.

Focus on SQL & Python first. Here are some important questions which you should know.

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬

1- Find out nth Order/Salary from the tables.
2- Find the no of output records in each join from given Table 1 & Table 2
3- YOY,MOM Growth related questions.
4- Find out Employee ,Manager Hierarchy (Self join related question) or
Employees who are earning more than managers.
5- RANK,DENSERANK related questions
6- Some row level scanning medium to complex questions using CTE or recursive CTE, like (Missing no /Missing Item from the list etc.)
7- No of matches played by every team or Source to Destination flight combination using CROSS JOIN.
8-Use window functions to perform advanced analytical tasks, such as calculating moving averages or detecting outliers.
9- Implement logic to handle hierarchical data, such as finding all descendants of a given node in a tree structure.
10-Identify and remove duplicate records from a table.

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐏𝐲𝐭𝐡𝐨𝐧 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬

1- Reversing a String using an Extended Slicing techniques.
2- Count Vowels from Given words .
3- Find the highest occurrences of each word from string and sort them in order.
4- Remove Duplicates from List.
5-Sort a List without using Sort keyword.
6-Find the pair of numbers in this list whose sum is n no.
7-Find the max and min no in the list without using inbuilt functions.
8-Calculate the Intersection of Two Lists without using Built-in Functions
9-Write Python code to make API requests to a public API (e.g., weather API) and process the JSON response.
10-Implement a function to fetch data from a database table, perform data manipulation, and update the database.

Join for more: https://news.1rj.ru/str/datasciencefun

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Here is a list of Important interview questions

SQL INTERVIEW QUESTIONS WITH IMPORTANT TOPICS
👇👇
https://news.1rj.ru/str/sqlspecialist/426

Data Analyst Interview Questions
👇👇
https://news.1rj.ru/str/DataAnalystInterview/69

Python Interview Questions and Answers
👇👇
https://news.1rj.ru/str/dsabooks/96

Data Science Interview Questions
👇👇
https://news.1rj.ru/str/datasciencefun/1058

Advanced Power BI Interview Questions
👇👇
https://news.1rj.ru/str/sqlspecialist/422

DSA INTERVIEW QUESTIONS
👇👇
https://news.1rj.ru/str/crackingthecodinginterview/77

Use Chat GPT to prepare for your next INTERVIEW
👇👇
https://news.1rj.ru/str/getjobss/1483

ENJOY LEARNING 👍👍

✔️📚A beginner's roadmap for learning SQL:

🔺Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.

🔺Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.

🔺Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.

🔺Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.

🔺Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.

🔺Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.

🔺Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.

🔺Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

🔺Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).

🔺Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.

🔺Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.

🔺Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.

🔺Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.

🔺Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.

🔺Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.

👀👍Remember to practice regularly and build real-world projects to reinforce your learning.

Happy Learning 🥳 📚

Q1: How would you analyze data to understand user connection patterns on a professional network?

Ans: I'd use graph databases like Neo4j for social network analysis. By analyzing connection patterns, I can identify influencers or isolated communities.

Q2: Describe a challenging data visualization you created to represent user engagement metrics.

Ans: I visualized multi-dimensional data showing user engagement across features, regions, and time using tools like D3.js, creating an interactive dashboard with drill-down capabilities.

Q3: How would you identify and target passive job seekers on LinkedIn?

Ans: I'd analyze user behavior patterns, like increased profile updates, frequent visits to job postings, or engagement with career-related content, to identify potential passive job seekers.

Q4: How do you measure the effectiveness of a new feature launched on LinkedIn?

Ans: I'd set up A/B tests, comparing user engagement metrics between those who have access to the new feature and a control group. I'd then analyze metrics like time spent, feature usage frequency, and overall platform engagement to measure effectiveness.

Here are 30 most asked SQL questions to clear your next interview -

➤ 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀

1. Calculate the moving average of sales for the past 3 months.
2. Assign a dense rank to employees based on their salary.
3. Retrieve the first and last order date for each customer.
4. Find the Nth highest salary for each department using window functions.
5. Determine the percentage of total sales contributed by each employee.

➤ 𝗖𝗼𝗺𝗺𝗼𝗻 𝗧𝗮𝗯𝗹𝗲 𝗘𝘅𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻𝘀 (𝗖𝗧𝗘)

1. Use a CTE to split a full name into first and last names.
2. Write a CTE to find the longest consecutive streak of sales for an employee.
3. Generate Fibonacci numbers up to a given limit using a recursive CTE.
4. Use a CTE to identify duplicate records in a table.
5. Find the total sales for each category and filter categories with sales greater than a threshold using a CTE.

➤ 𝗝𝗼𝗶𝗻𝘀 (𝗜𝗻𝗻𝗲𝗿, 𝗢𝘂𝘁𝗲𝗿, 𝗖𝗿𝗼𝘀𝘀, 𝗦𝗲𝗹𝗳)

1. Retrieve a list of customers who have placed orders and those who have not placed orders (Full Outer Join).
2. Find employees working on multiple projects using a self join.
3. Match orders with customers and also display unmatched orders (Left Join).
4. Generate a product pair list but exclude pairs with identical products (Cross Join with condition).
5. Retrieve employees and their managers using a self join.

➤ 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀

1. Find customers whose total order amount is greater than the average order amount.
2. Retrieve employees who earn the lowest salary in their department.
3. Identify products that have been ordered more than 10 times using a subquery.
4. Find regions where the maximum sales are below a given threshold.

➤ 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀

1. Calculate the median salary for each department.
2. Find the total sales for each month and rank them in descending order.
3. Count the number of distinct customers for each product.
4. Retrieve the top 5 regions by total sales.
5. Calculate the average order value for each customer.

➤ 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 𝗮𝗻𝗱 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲

1. Write a query to find duplicate values in an indexed column.
2. Analyze the impact of adding a composite index on query performance.
3. Identify columns with high cardinality that could benefit from indexing
4. Compare query execution times before and after adding a clustered index.
5. Write a query that avoids the use of an index to test performance differences.

Many candidates get rejected in interviews due to one of the reasons listed below:

📌Poor Preparation – Walking into an interview without knowing about the company, its culture, or the role is like sitting for an exam without studying. It shows a lack of interest.

📌Weak Communication Skills – Even the best ideas can fail if you can’t communicate them effectively. Clear, confident, and concise answers are key.

📌Inappropriate Attire – First impressions matter, and dressing unprofessionally can send the wrong signal. Always align with the company’s dress code.

📌Overconfidence or Lack of Confidence – Being too arrogant or overly timid can both raise red flags. A balanced, professional attitude is what employers look for.

📌Not Asking Questions – Interviews are a two-way street. Failing to ask thoughtful questions can make you seem uninterested or unengaged.

📌Negative Comments About Previous Employers – Speaking ill of past experiences reflects poorly on your professionalism. Keep the conversation positive.

📌Focusing Only on Salary – While compensation is important, discussing it too soon or too much might make you seem less interested in the job itself.

By recognizing these common pitfalls and addressing them, you can significantly improve your chances of landing that dream job!