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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A

Smart Cities: 16 Top Job Roles You need to Know

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Why IOT skill you need: There are currently 18.2 billion connections to the internet throughout the world, and this will increase to 50 billion by 2020. The amount of data being transmitted via these connections has grown from 3ZB (3,000,000,000,000,000,000,000 bytes) in 2010 to 10ZB (10,000,000,000,000,000,000,000 bytes) this year, and it is predicted to reach 40ZB (40,000,000,000,000,000,000,000 bytes) by 2020. New Type of Skills Internet of everything has the potential to reach $19 trillion of value by 2022, and it "has the potential to grow global corporate profits by 21% in 2022".It's exponentially increasing. In a smart city, "every single sector has to get technology fluent and it has to get digital fluent to drive long-term prosperity,". This is an issue that both the public and private sectors need to get behind and to transform how they think and how to get people ready for the jobs to solve these problems. "We need new types of skills , ne

Ruby on Rails: How to Create Web Application

You’ve probably already used many of the applications that were built with Ruby on Rails: Basecamp, GitHub,Shopify, Airbnb, Twitch, SoundCloud,Hulu, Zendesk, Square, Highrise. Those are just some of the big names, but there are literally hundreds of thousands of applications built with the framework since its release in 2004.

Computer Science Vs Information Science Top Differences

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Here are the differences between Computer Science and Information Science. Computer Science Computer scientists are, in fact, scientists. They are focused on the theory of computational applications. That means they understand the “why” behind computer programs. Using algorithms and advanced mathematics, computer scientists invent new ways to manipulate and transfer information. Computer scientists are generally concerned with software, operating systems, and implementation. Like Neo in The Matrix, computer scientists can see and make sense of code. Computer science students will learn the fundamentals of different programming languages, linear and discrete mathematics, and software design and development. Computer scientists study the machine itself and understand how and why various computer processes operate the way they do.   Information Science To put it bluntly, computer engineers make computer parts work together. Computer engineers are responsible for the research, de

SPARK is Replacement for MapReduce in Bigdata Real Analytics!

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Apache Spark is among the Hadoop ecosystem technologies acting as catalysts for broader adoption of big data infrastructure. Now, Looker -- a vendor of business intelligence software -- has announced support for Spark and other Hadoop technologies. The goal? To speed up access to the data that fuels business decision making. SPARK Jobs Hadoop's arrival on the scene 10 years ago may have started the big data revolution, but only recently did adoption of this technology begin spreading to a wider audience. Apache Spark is one of the catalysts for the growing adoption rates. Spark can be used as a replacement for MapReduce, a component of Hadoop implementations, to speed up the processing and analytics of big data by 100x in memory, according to the Apache Software Foundation. In today's business environment, in which real-time analytics is the goal and organizations don't want to wait for data warehouses and analysts to provide batch intelligence back to business u