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Top R programming, SQL and Tableau Interview Questions & Answers!

Posted on by Imarticus Learning

Whether you are a fresher or an experienced data professional looking for better opportunities, attending an interview is inevitably the first step towards your dream career. Many of you might already have done a sneak peek into the world of data analytics through self-taught skills.

Data Science Course with Placement in IndiaHaving a good grip on the subject matter will give you an edge over other candidates. Data Science Courses and certifications add more weightage to your profile.

Interviewers might ask situation-based questions to test your knowledge and crisis management skills. So, make sure that you answer these questions wisely and showcase your knowledge wherever possible, without going overboard.

Listed below are some important R programming, SQL, and Tableau interview questions and answers. Check them out!

R Programming Interview Questions

A handy programming language used in data science, R finds application in various use cases from statistical analysis to predictive modeling, data visualization, and data manipulation. Many big names such as Facebook, Twitter, and Google use R to process the huge amount of data they collect.

  1. Which are the R packages used for data imputation?

Answer: Missing data could be a challenging problem to deal with. In such cases, you can impute the lost values with plausible values. imputeR, Amelia, Hmisc, missForest, MICE, and Mi are the data imputation packages used by R.

  1. Define clustering? Explain how hierarchical clustering is different from K-means clustering?

Cluster, just like the literal meaning of the word, is a group of similar objects. During the process, the abstract objects are classified into ‘classes’ based on their similarities. The center of a cluster is called a centroid, which could be either a real location or an imaginary one. K denotes the number of centroids needed in a data set.

While performing data mining, k selects random centroids and then optimizes the positions through iterative calculations. The optimization process stops when the desired number of repetitive calculations have been taken place or when the centroids stabilize after successful clustering.

The hierarchical clustering starts by considering every single observation in the data as a cluster. Then it works to discover two closely placed clusters and merges them. This process continues until all the clusters merge to form just a single cluster. Eventually, it gives a dendrogram that denotes the hierarchical connection between the clusters.

SQL Interview Questions

SQL online Training

If you have completed your SQL training, the following questions would give you a taste of the technical questions you may face during the interview.

  1. Point out the difference between MySQL and SQL?

Answer: Standard Query Language (SQL) is an English-based query language, while MySQL is used for database management.

  1. What is DBMS and How many types of DBMS are there?

Answer: DBMS or the Database Management System is a software set that interacts with the user and the database to analyze the available data. Thus, it allows the user to access the data presented in different forms – image, string, or numbers – modify them, retrieve them and even delete them.

There are two types of DBMS:

  • Relational: The data placed in some relations (tables).
  • Non-Relational: Random data that are not placed in any kind of relations or attributes.

 Tableau Interview Questions

Tableau is becoming popular among the leading business houses. If you have just completed your Tableau training, then the interview questions listed below could be good examples.

  1. Briefly explain Tableau.

Answer: Tableau is a business intelligence software that connects the user to the respective data. It also helps develop and visualize interactive dashboards and facilitates dashboard sharing.

  1. How is Tableau different from the traditional BI tools?

Answer: Traditional BI tools work on an old data architecture, which is supported by complex technologies. Additionally, they do not support in-memory, multi-core, and multi-thread computing. Tableau is fast and dynamic and is supported by advanced technology. It supports in-memory computing.

  1. What are Measures and Dimensions in Tableau?

Answer: ‘Measures’ denote the measurable values of data. These values are stores in specific tables and each dimension is associated with a specific key. This helps to associate one piece of data to multiple keys, allowing easy interpretation and organization of the data. For instance, the data related to sales can be linked to multiple keys such as customer, sales promotion, events, or a sold item.

Dimensions are the attributes that define the characteristics of data. For instance, a dimension table with a product key reference can be associated with different attributes such as product name, color, size, description, etc.

The questions given above are some examples to help you get a feel of the technical questions generally asked during the interviews. Keep them as a reference and prepare with more technically inclined questions.

Remember, your attitude and body language play an important role in making the right impression. So, prepare, and be confident. Most importantly, structure your answers in a way that they demonstrate your knowledge of the subject matter.

Related Article:

https://imarticus.org/20-latest-data-science-jobs-for-freshers/

SQL For Data Science: One-Stop Solution For Beginners!

Posted on by Imarticus Learning

Data science has earned the reputation of being the most promising job of the times, even during this pandemic crisis. With the current changes in the global business and economic background, data science has proven to be a more relevant career opportunity. If you are following the subject and have a keen interest in making a data science career choice, you must have heard about SQL as well.

SQL online trainingSQL is used to access and manipulate data. It helps to store data, access whenever you need it, and retrieve if need be. SQL training will give you a much-required head start in the highly competitive job market.

Why is SQL Important in Data Science?

Today’s business decisions are data-driven. Data is generated all through the day, across the globe. The amount of data generated every day is simply astonishing – about 2.5 quintillion bytes. This underlines the enormity of the subject we are dealing with.

Now that data is available, what is the next thing? How are you going to make sense of this huge amount of data and use it to make a decision? Data science steps in here. You need to collect, organize, and process them to make sense of the data and to derive insights. To do this, you need tools.  This is what SQL does. It is a querying language used to store, access, and retrieve data.

What is Structured Query Language (SQL)

SQL is a language that is primarily concerned with managing relational databases. SQL is the typical API for such data tables. While using SQL, data can be accessed and managed without changing the databases. You can perform a variety of actions including updating, querying, deleting, and inserting data records. Oracle, MySQL etc. are examples of such databases which use SQL.

SQL works based on some simple commands that are associated with different data tasks. These commands can be used to create database and tables, insert, delete, or update data, to alter table and database, drop table and index.

How to Create a Table Using SQL

Let’s see how to create a table using SQL commands. Remember to use UPPERCASE letters for SQL commands, and use semicolons to terminate commands.

data science careerYou may follow the steps given below to create a database.

Step #1 Creating a Database using SQL

CREATE DATABASE: Use this command to create a database “Test”.

USE: This command activates the database.

CREATE test;

USE test;

Your database named test is ready and activated.

Step #2: Creating a Data Table

It is as easy as typing a command to create a table, just like the way you created the database. All you need to do is to decide on the variables you want to include in the table.

SQL online trainingSuppose you want to create a table with the following features:

  1. Serial Number (SL)
  2. Purchase item
  3. Cost
  4. Number of pieces

You can use the command CREATE TABLE to create the table. The four features of the table are SL, purchase item, cost, and number of pieces.

Now, to create the table, use the command as given below:

CREATE TABLE cart (SL NOT NULL PRIMARY KEY AUTO_INCREMENT Purchase_item TEXT, Cost INTEGER, Number_of_pieces INTEGER);

You might have noticed that we have given the value we are going to provide for each feature. The Serial Number is a primary key, which means it represents a unique data. The purchase item will be entered as text, while cost and number of pieces will be entered as numbers.

The table is now ready with the field names and the value to be entered to each cell of the table. To see how the table is executed, type the command “DESCRIBE cart”. This will give you a display of a table with the given features.

Field Type Null Key Default Extra
SL Int(11) NO PRI NULL Auto_increment
Purchase Item Text YES NULL
Cost Int(11) YES NULL
Number of pieces Int(11) YES NULL

Step #3: Data Input

Once you create the table, you need to enter data into the respective fields. To do this. Use the SQL command “INSERT INTO”.

To insert values, follow this pattern:

INSERT INTO cart VALUES (NULL, “Rice”, 75, 10)

The “null” value is assigned to SL, as it will follow the command and auto_increment from 1.

The entered value will look like:

SL Purchase item Cost Number of pieces
1 Rice 75 10

Follow the same pattern to enter more values.

Data Science is trending these days. Getting trained in a skill that is much in demand improves your chances of getting hired manifold.

So, choose a good data science course and give your profile an extra edge while competing for career opportunities.