Krishnaveni Reddy

Interviewer to candidate: Spark replaced hadoop and Iam habituated to hadoop. What about you ? Candidate: I agree with you but don't worry you can easily adopt to cloud. Interviewer: Thank's a lot we will get back to you. Very short round of interview. Update yourself about cloud technologies by following the right person's. #spark #databricks #mapreduce #hadoop #azure Lalit Rawat Azure MVP-Evangelist,Author,Speaker

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#hiringAlert #DataEngineers #NIQ Hi all, NielsenIQ is actively hiring for Data Engineers. Let me know if anybody is interested, I'll be happy to refer. 1. EXP - 3+ Years Data Engineer (Mid) SKILLS - Azure, Spark Scala, SQL    2. EXP - 3-7 Years Data Engineer (Mid) SKILLS - Apache Spark, Databricks, programming language Python/Scala (scala is preferred), Workflow or Orchestration using Airflow tool -good to have. Azure Fundamental Certificate good to have  3. EXP - 7- 10 Years Senior Data Engineer-Python/Scala  SKILLS - Apache Spark, Databricks, programming language Python/Scala (scala is preferred), Workflow or Orchestration using Airflow tool -good to have. Azure Fundamental Certificate good to have    4. EXP - 7- 10 Years Senior Data Engineer- Python     SKILLS - Python & RESTful APIs, pandas, NumPy, flask, Big Data & RDBMS 5. EXP - 10+ Years  Manager Data Engineering- Python, Snowflake cloud database  SKILLS - Python,Snowflake, Azure cloud, SQL,Pytest #NIQ #NielsenIQ #Openings #Referral #Career #Opportunities #DataEngineers #experiencedprofessionals #spark #python #cloud

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Are you using or learning SQL? This simple function is an absolute life saver... COALESCE( ) This one lets you look at multiple columns, and return the first non-NULL value you find. You can think of it as giving yourself a fallback option... IF there is a value in column A, grab it. But if column A is NULL, then look for a value in column B. This is super useful and there are lots of different applications. We'll walk through it here in this quick video example. Check it out and let me know what you think! #learning #sql #data #analysis #datascience #businessintelligence #careers

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Are you using or learning SQL? This simple function is an absolute life saver... COALESCE( ) This one lets you look at multiple columns, and return the first non-NULL value you find. You can think of it as giving yourself a fallback option... IF there is a value in column A, grab it. But if column A is NULL, then look for a value in column B. This is super useful and there are lots of different applications. We'll walk through it here in this quick video example. Check it out and let me know what you think! #learning #sql #data #analysis #datascience #businessintelligence #careers

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RSVP Movies Case Study:- Leveraged SQL to analyze movie data for RSVP by implementing ERD, DDL, and DML commands. Utilized inner joins to extract valuable insights, and provided recommendations based on the findings to help RSVP produce successful movies for a global audience. problem Statement :- Q1. Find the total number of rows in each table of the schema? Q2. Which columns in the movie table have null values? Q3. Find the total number of movies released each year? How does the trend look month wise?  (Output expected) Q4. How many movies were produced in the USA or India in the year 2019?? Q5. Find the unique list of the genres present in the data set? Q6. Which genre had the highest number of movies produced overall? Q7. How many movies belong to only one genre? Q8. What is the average duration of movies in each genre?  Q9. What is the rank of the ‘thriller’ genre of movies among all the genres in terms of  number of movies produced?  Q10. Find the minimum and maximum values in each column of the ratings table except the movie_id column? Q11. Which are the top 10 movies based on average rating? Q12. Summarise the ratings table based on the movie counts by median ratings. Q13. Which production house has produced the most number of hit movies (average rating > 8)?? Q14. How many movies released in each genre during March 2017 in the USA had more than 1,000 votes? Q15. Find movies of each genre that start with the word ‘The’ and which have an average rating > 8? Q16. Of the movies released between 1 April 2018 and 1 April 2019, how many were given a median rating of 8? Q17. Do German movies get more votes than Italian movies?  Q18. Which columns in the names table have null values?? Q19. Who are the top three directors in the top three genres whose movies have an average rating > 8? Q20. Who are the top two actors whose movies have a median rating >= 8? Q21. Which are the top three production houses based on the number of votes received by their movies? Q22. Rank actors with movies released in India based on their average ratings. Which actor is at the top of the list? Q23.Find out the top five actresses in Hindi movies released in India based on their average ratings?  Note: The actresses should have acted in at least three Indian movies.  Q24. Select thriller movies as per avg rating and classify them in the Q25. What is the genre-wise running total and moving average of the average movie duration?  Q26. Which are the five highest-grossing movies of each year that belong to the top three genres?  Q27. Which are the top two production houses that have produced the highest number of hits  Q28. Who are the top 3 actresses based on number of Super Hit movies (average rating >8) in drama genre? Q29. Get the following details for top 9 directors (based on number of movies) #Mysql #Data Analyst #Data Science #business Analyst

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Interview Readiness Playlist for Aspiring Data Scientists 📌 Ongoing Interviewing Trends: youtu.be/XrZXojl5Zd8 📌 Essential Mathematics for ML: youtu.be/oMY2uKjx_Zc 🎯Complete guide for Linear Regression lnkd.in/gdRsMHbn 🎯Complete playlist for Logistic Regression lnkd.in/gtPfmQUv 📌 Classification Metrics: youtu.be/E2HRSJKU-_4 🎯Data Drift Detection & Model Monitoring youtu.be/tQjRQWfYQ10 📌 Conversational AI: Tech behind Chat-GPT: youtu.be/JKoJ5YIr2O4 📌 Pushing LLM Boundaries Sparse & Flash Attention, Quantisation, Pruning, Distillation, LORA : youtu.be/mF7OM_XU2S4 📌 PySpark Essentials youtu.be/aruptWppgSs #datatrek #datascience #machinelearning #statistics #deeplearning #ai

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Hi, Connections, I have felt Tableau is more flexible than any Visualization Tool 🙃 . Here I am sharing a few questions from my notes on Tableau. 🔍 ✅ What Types of filters do we have in Tableau? ▶ Extract Filter: This filter retrieves a subset of data from the data source. ▶ Dimension Filter: This filter is for non-aggregated data (discrete). ▶ Data Source Filter: This filter refrains users from viewing sensitive information and thus reduces data feeds. ▶ Context Filter: This filter creates datasets by applying presets in Tableau. ▶ Measure Filter: This filter applies various operations like sum, median, average, etc. ▶ Table Calculation Filter: This filter is applied after the view has been created. ✅ Difference between a tree map and a heat map? ▶ Both map helps with data analysis. Heat Map Helps to visualize and  Compare different categories of data. Treemap displays hierarchical data Hope it helps 😊 #keep_learning_keep_growing 📚

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Most asked data warehouse interview question is about SCD Type 2. SCD Type 2: SCD Type 2 is a method used in data warehousing to track historical changes in dimension data by adding new records for changes while retaining previous versions. This approach ensures a complete history of changes over time e.g: If an employee gets promoted, instead of updating the existing record and losing the historical data, SCD Type 2 would close the current record (by setting an end date or marking a flag like 'Current' as 'N') and add a new record for the employee with the new position (marked as 'Current' with 'Y')

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SQL Interview Questions asked In the Data Analyst Interview at Tripadvisor. ➡  Write a query to display the highest salaries in each department. ➡   How would you display the records of the top 15 students in the most recent exam? ➡ Write a query to display each city where the company has customers from two different states and the number of customers in each city. ➡ What does UNION do? What is difference the between between UNION and UNION ALL? ➡ How can you select all the even number records from a table? All the odd-number records? ➡ What is the difference between single-row functions and multiple-row functions? ➡ How do you copy data from one table to another table? ➡What are the benefits of using window functions? ➡How do you join a table to itself? ➡What is the purpose of the LAG and LEAD functions in SQL? #tripadvisor #dataanalyticsmockinterview #sql #LTM

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Common SQL Interview Question: How do you optimize a slow SQL query? While this question might be out-of-scope for Data Analysts and Data Scientists, for roles like Data Engineering or BI, it's absolutely fair game to know how databases work internally, and best practices for troubleshooting a slow query. Answers Include: •SELECT fields instead of using SELECT * •Avoid SELECT DISTINCT •Create joins with INNER JOIN (not WHERE) •Avoid JOINs in general (maybe try de-normalization) •Add indexes to your database •Examine the SQL query execution plan

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Tableau Learning Series Part-2 Today, let's learn about: Connecting to Data. Types of Data Connections 1. File-based Sources: - Excel: Connects to .xlsx and .xls files. - Text Files: Includes CSV, TSV, and other delimited text files. - JSON Files: Connects to .json files for hierarchical data. - PDF Files: Extracts tables from PDF documents. - Spatial Files: Includes .shp, .kml, .geojson, etc. 2. Server-based Sources: - Relational Databases: Such as SQL Server, MySQL, PostgreSQL, Oracle, and more. - Cloud Databases: Such as Amazon Redshift, Google BigQuery, Snowflake, and others. - Web Data Connectors: Allows connection to data available on the web via APIs (e.g., Google Sheets, Salesforce). 3. Extracts: A Tableau Data Extract (.hyper) is a snapshot of your data optimized for performance. #### Connecting to Live Data vs. Extracts 1. Live Connection: Directly connects to the data source and queries it in real-time. This ensures that the data is always up-to-date but can be slower depending on the data source's performance and network latency. 2. Extracts: A static snapshot of the data that is stored locally. Extracts improve performance and allow for offline access. #### Data Source Page and Data Preparation Once you connect to a data source, Tableau takes you to the Data Source page where you can manage and prepare your data before starting your analysis. 1. Data Source Page Layout: - Connections Pane: Lists all the data sources you are connected to. - Canvas: Where you can drag and drop tables to create relationships and joins. - Data Grid: Displays a preview of the data. 2. Data Preparation Tools: - Joins: Combine tables based on common fields. Types of joins include inner, left, right, and full outer joins. - Blends: Combine data from different data sources. This is useful when you cannot join tables directly due to different data sources. - Unions: Stack tables with the same structure on top of each other. - Pivoting: Reshape your data by pivoting columns into rows, useful for transforming wide data sets into long formats. - Splitting: Split a single column into multiple columns based on a delimiter. - Data Interpreter: Helps clean and prepare Excel or CSV data by interpreting the structure and cleaning up the data automatically. Example: Steps for Connecting to an Excel File 1. Open Tableau Desktop. 2. Connect to Data: On the start page, click "Microsoft Excel" under the Connect pane. 3. Select the File: Browse and select an Excel file (e.g., "Sample - Superstore.xlsx"). 4. Data Source Page: - The sheets in the Excel file will be listed on the left side. - Drag a sheet (e.g., "Orders") to the canvas. - Tableau displays a preview of the data in the Data Grid. - Perform any necessary data preparation steps (e.g., pivoting, splitting). 5. Go to Sheet: Click on the "Sheet 1" tab at the bottom to start building your visualization with the connected data. #tableau

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Data normalization is an important aspect of data management and analysis that plays a crucial role in both data storage and data analysis. ▸Fresher’s Guide to Land a Job in Data Analytics: https://lnkd.in/gQsp5uzv ▸SQL Knowledge You Need as a Data Analyst: https://lnkd.in/g-hf2DPw

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**75-Day SQL Challenge: Day # 5** Category: Easy Website: DataLemur 🐒 (Ace the SQL & Data Interview) by Nick Singh 📕🐒 📕🐒 Company: CVS Health 🔶Task: Write a query to calculate the total drug sales for each manufacturer. Round the answer to the nearest million and report your results in descending order of total sales. In case of any duplicates, sort them alphabetically by the manufacturer name. Since this data will be displayed on a dashboard viewed by business stakeholders, please format your results as follows: "$36 million". 🔶Table structure: There is one table named "pharmacy_sales". It consists of following attributes: 1. product_id (int) 2. units_sold (int) 3. total_sales (decimal) 4. cogs (decimal) 5. manufacturer (string) 6. drug (string) 🔶My submission: SELECT manufacturer,  CONCAT('$', CAST((ROUND(totalsale/1000000,0)) AS TEXT), ' million') as sales_mill FROM  (   SELECT manufacturer,        SUM(total_sales) as totalsale   FROM pharmacy_sales   GROUP BY manufacturer   ORDER BY totalsale DESC ) as abc; 🔶Breakdown of the code: ❇️ In the inner query, we are grouping the data at "manufacturer" level and calculating the sum of total_sales made by each manufacturer. The overall output is sorted in the descending order of total sales value. ❇️ In the outer query, we are dividing the total sales value by 1 million, rounding the value to nearest million, casting the value to text from numeric, and finally concatenating with the $ sign. ❇️ Finally, in the overall output, we can see the total sales made by the respective manufacturers in millions. #SQL #DataLemur #75daysofcodechallenge #datanalyst #datascientist

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Tech Nest Academy SQL Interview Question Series Q.Write an SQL query to determine the increment amount each employee will receive based on their base salary. The increment amount is allocated to employees according to the following criteria: 1. If the base salary is less than $5000, the employee will be assigned to Band 'A' and receive the corresponding increment amount. 2. If the base salary is between $5000 and $10000 (inclusive), the employee will be assigned to Band 'B'. 3. For any other salary, the employee will be assigned to Band 'C'. Table Scripts: create table emp(empid int,empname varchar(50),base_salary int); insert into emp values(1,'John',4000); insert into emp values(2,'Tom',7000); insert into emp values(3,'Sara',12000); insert into emp values(4,'Rajesh',20000); insert into emp values(5,'Rohan',0); insert into emp values(6,'Abdul',null); create table bonus(band_name varchar(50),incrementamt int); insert into bonus values('A',500); insert into bonus values('B',1100); insert into bonus values('C',2000); Please share your solution in the comment section. I will create a video on the explanation and will update shortly in this post. #SQL #DataAnalyst #sqltraining #corporatetraining

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SQL interview question#12 You have a Contacts table with columns FirstName and LastName. Write a query to find all contacts whose first name starts with 'J' and last name contains 'son'. 𝐄𝐱𝐩𝐥𝐚𝐧𝐚𝐭𝐢𝐨𝐧: To find contacts with these criteria, we combine two LIKE operators with an AND condition. The first pattern 'J%' matches first names starting with 'J', and the second pattern '%son%' matches last names containing 'son'. 𝐐𝐮𝐞𝐫𝐲: SELECT * FROM Contacts  WHERE FirstName LIKE 'J%' AND LastName LIKE '%son%'; Shashank Singh 🇮🇳 Munna Das Arun R. Vishal Kaushal Thodupunuri Bharath Yusuf Didighar Aniket Kardile Shivan Kumar Ashutosh Kumar Follow Adit Jain for more updates on Data Analyst content and interview questions.

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Its Tough To Get Into Data Analytics and Data Science Career?? #dataanalytics #DataScience #datascience #data #machinelearning #businessanalytics #sql #mysql #sqlserver #statistics #business #hiring #companies #jobs #career #manager #generativeai #artificialintelligence #ai #reels

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