Check our latest YouTube video in which we have covered a very important topic for Data Analytics.

Learn Complete Matplotlib for Data Analytics in 1.5 Hours. Video link given below.

👉🏻 https://youtu.be/3V8RAsg5GHI

Date: 31st August, 2022
Company name: Netspi
Job role: Data Analyst
Topic: SQL, data cleaning, EDA

1. Explain data cleansing.

Data cleaning, also known as data cleansing or data scrubbing or wrangling, is basically a process of identifying and then modifying, replacing, or deleting the incorrect, incomplete, inaccurate, irrelevant, or missing portions of the data as the need arises. This fundamental element of data science ensures data is correct, consistent, and usable. 

2. What is an Affinity Diagram?

Ans. An Affinity Diagram is an analytical tool used to cluster or organize data into subgroups based on their relationships. These data or ideas are mostly generated from discussions or brainstorming sessions and are used in analyzing complex issues.

3. Which questions should you ask the user/client before you create a dashboard?

Though this depends on the user’s requirements, still some of the common questions that I would ask the client before creating a dashboard are :

What is the purpose of the dashboard?Should the dashboard be retrospective or real-time?How detailed the dashboard should be?How tech and data-savvy is the end-user?Does the data need to be segmented?Should I explain the dashboard design to you?

4. What is an Alias in SQL?

An alias is a feature of SQL that is supported by most, if not all, RDBMSs. It is a temporary name assigned to the table or table column for the purpose of a particular SQL query. In addition, aliasing can be employed as an confusion technique to secure the real names of database fields. A table alias is also called a correlation name.
An alias is represented explicitly by the AS keyword but in some cases, the same can be performed without it as well. 

Decode "CloudyML Data Analytics Combo Course"🤓

Watch our latest video in which we have explained about our Data Analytics Combo Course in depth. We have covered how it gonna help you, how the assignments will be, how you will be connecting with your mentors and how it will make you job ready at best affordable price. Link given below.

➡️ https://youtu.be/AhvqIzkEogw

Date: 01st Sept, 2022
Company name: Walmart
Role: Data Scientist
Topic: Machine Learning, SQL, Deep Learning

1. Which of the following machine learning algorithms can be used for inputting missing values of both categorical and continuous variables?

K-means clustering
Linear regression
K-NN (k-nearest neighbor)
Decision trees

The K nearest neighbor algorithm can be used because it can compute the nearest neighbor and if it doesn't have a value, it just computes the nearest neighbor based on all the other features.

When you're dealing with K-means clustering or linear regression, you need to do that in your pre-processing, otherwise, they'll crash. Decision trees also have the same problem, although there is some variance


2. What is an RNN (recurrent neural network)?

RNN is an algorithm that uses sequential data. RNN is used in language translation, voice recognition, image capturing etc. There are different types of RNN networks such as one-to-one, one-to-many, many-to-one and many-to-many. RNN is used in Google’s Voice search and Apple’s Siri.


3. What is the goal of A/B Testing?

This is statistical hypothesis testing for randomized experiments with two variables, A and B. The objective of A/B testing is to detect any changes to a web page to maximize or increase the outcome of a strategy.


4. What is a star schema?

Star schema is the fundamental schema among the data mart schema and it is simplest. It is said to be star as its physical model resembles to the star shape having a fact table at its center and the dimension tables at its peripheral representing the star’s points.

————————————————————-

🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS WITH CLOUDYML FROM SCRATCH. TRUSTED BY 8000+ HAPPY LEARNERS

This course package, you are getting Python, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Support over Skype chat everyday. Check the course NOW!

Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo

🚨Get Data Science and Analytics related Important Hand Written Notes. Click on "Download Now".


✅Python Notes (Download Now)


✅SQL Notes (Download Now)


✅Statistics Notes (Download Now)


✅DSA Notes (Download Now)


✅Gini Impurity in Decision Trees Notes (Download Now)


✅Linked List Notes (Download Now)


✅ML Algorithms Notes (Download Now)


✅Tableau Notes (Download Now)


✅MS Excel Notes (Download Now)


Stay Safe and Happy Learning💙

If you are a college student then watch our latest YouTube video which will help you in your college placements. Link given below

👉🏻 https://youtu.be/yixOVk_ceUc

Date: 1st September, 2022
Company name: Mindtree
Role: Business analyst
Topic: SQL, Tableau, Agile

1. What is SRS and what are its key elements?

Answer: A System Requirements Specification (SRS) or a Software Requirements Specification is a document or set of documents that describe the features of a system or software application. The key elements of an SRS are:

Scope of Work
Functional Requirements
Non-Functional Requirements
Dependencies
Data Model
Assumptions
Constraints
Acceptance Criteria


2. What do you know about Kanban?

Answer: Kanban is a tool which helps the agile team to visually guide and manage the work as it progresses through the process. Besides, it works as a scheduling system in Agile just-in-time production. The Kanban board is used to describe the current development status.


3. What is clustered index in SQL?

Answer: A clustered index is actually a table where the data for the rows are stored. It determines the order of the table data based on the key values that can sort in only one direction. Each table can have only one clustered index. It is the only index, which has been automatically created when the primary key is generated. If many data modifications needed to be done in the table, then clustered indexes are preferred.


4. What are sets in Tableau?

Answer: Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computed sets update as your data changes. Alternatively, a set can be based on specific data point in your view.

Become Master in Seaborn for Data Analyst role. Watch our Latest YouTube Video. Link given below

👉🏻 https://youtu.be/T5d57ay_dd4

Date: 03-09-2022
Company name: CRED
Role: SQL developer
Topic: SQL

1. What are the differences between OLTP and OLAP?

OLTP stands for online transaction processing, whereas OLAP stands for online analytical processing. OLTP is an online database modification system, whereas OLAP is an online database query response system.



2. What do you understand by query optimization?

The phase that identifies a plan for evaluation query which has the least estimated cost is known as query optimization.

The advantages of query optimization are as follows:

i) The output is provided faster.
ii) A larger number of queries can be executed in less time.
iii) Reduces time and space complexity


3. What is the difference between the RANK() and DENSE_RANK() functions?

The RANK() function in the result set defines the rank of each row within your ordered partition. If both rows have the same rank, the next number in the ranking will be the previous rank plus a number of duplicates. If we have three records at rank 4, for example, the next level indicated is 7.

The DENSE_RANK() function assigns a distinct rank to each row within a partition. This function will assign the same rank to the two rows if they have the same rank, with the next rank being the next consecutive number. If we have three records at rank 4, for example, the next level indicated is 5.


4. What is Normalization and what are the advantages of it?

Normalization in SQL is the process of organizing data to avoid duplication and redundancy. Some of the advantages are:

Better Database organization

More Tables with smaller rows

Efficient data access

Greater Flexibility for Queries

Quickly find the information

Easier to implement Security

Allows easy modification

Reduction of redundant and duplicate data

————————————————————-

🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS WITH CLOUDYML FROM SCRATCH. TRUSTED BY 8000+ HAPPY LEARNERS

This course package, you are getting Python, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Support over Skype chat everyday. Check the course NOW!

Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo

Watch this video to know How Someone Without Data Analytics Degree Can Become A Data Analyst ?

👉🏻 https://youtu.be/g4dXgmo_j24

Date: 4th September, 2022
Company name: Swiggy
Role: Data Analyst
Topic: Python, SQL, PowerBI, Tableau

1. What is the difference between primary key and unique key in SQL?

Both primary and unique keys carry unique values but a primary key cannot have a null value, while a unique key can. In a table, there cannot be more than one primary key, but there can be multiple unique keys.


2. What is a Stacked Column Chart in Tableau?

Stacked Column Chart, composed of multiple bars stacked vertically, one on another. The length of the bar depends on the value in the data point. A stacked column chart is the best one to know the changes in all variables. This type of chart should be checked when the number of series is higher than two.


3. Explain split() and join() functions in Python?

You can use split() function to split a string based on a delimiter to a list of strings.You can use join() function to join a list of strings based on a delimiter to give a single string.


4. Where is the data stored in Power BI?

Ans: Primarily, PowerBI uses two repositories to store its data: Azure Blob Storage and Azure SQL Database. Azure Blob Storage typically stores the data that is uploaded by the users. Azure SQL Database stores all the metadata and artifacts for the system itself.

🚨JOB OPENING UPDATES🚨

Role: Business Analyst Internship (In Office Chennai)
Company: Xobin Technologies Private Limited
Exp: Fresher
Link: https://ai.cloudyml.com/3q8PMjh

Role: Data Analyst
Company: Mymoneymantra
Exp: Fresher
Link: https://ai.cloudyml.com/3QuS33j

Role: Junior Business Analyst
Company: Indus Valley Partners
Exp: Fresher
Link: https://ai.cloudyml.com/3en8wc6

Role: Computer Vision Engineer
Company: Koireader Technologies
Exp: Fresher
Link: https://ai.cloudyml.com/3KSJJsU

ALL THE BEST💙

Date: 05th Sept, 2022
Company: Cloudera
Role: Data Scientist
Topic: machine learning, SQL, python

Q1 What are Loss Function and Cost Functions? Explain the key Difference Between them?

When calculating loss we consider only a single data point, then we use the term loss function.

Whereas, when calculating the sum of error for multiple data then we use the cost function. There is no major difference.

In other words, the loss function is to capture the difference between the actual and predicted values for a single record whereas cost functions aggregate the difference for the entire training dataset.

The Most commonly used loss functions are Mean-squared error and Hinge loss.

Mean-Squared Error(MSE): In simple words, we can say how our model predicted values against the actual values.

MSE = summation(predicted value - actual value)**2/n(no of data points)
Hinge loss: It is used to train the machine learning classifier, which is

L(y) = max(0,1- y_true*y_pred)

Where y = -1 or 1 indicating two classes and y represents the output form of the classifier. The most common cost function represents the total cost as the sum of the fixed costs and the variable costs in the equation y = mx + b


Q2 What is SVM? Can you name some kernels used in SVM?

SVM stands for support vector machine. They are used for classification and prediction tasks. SVM consists of a separating plane that discriminates between the two classes of variables. This separating plane is known as hyperplane. Some of the kernels used in SVM are –

Polynomial Kernel
Gaussian Kernel
Laplace RBF Kernel
Sigmoid Kernel
Hyperbolic Kernel

Q3 What are the subsets of SQL?

Ans. The following are the four significant subsets of the SQL:

Data definition language (DDL): It defines the data structure that consists of commands like CREATE, ALTER, DROP, etc.

Data manipulation language (DML): It is used to manipulate existing data in the database. The commands in this category are SELECT, UPDATE, INSERT, etc.

Data control language (DCL): It controls access to the data stored in the database. The commands in this category include GRANT and REVOKE.

Transaction Control Language (TCL): It is used to deal with the transaction operations in the database. The commands in this category are COMMIT, ROLLBACK, SET TRANSACTION, SAVEPOINT, etc.

Q4 Difference between a shallow and a deep copy?

It's faster to do shallow repetitions. It does, however, handle pointers and references in a "lazy" manner. It just copies over the pointer price rather than producing a current copy of the specific knowledge the pointer links to. As a result, each of the initial and subsequent copies can have pointers that relate to the same underlying knowledge. Deep repetition clones the underlying data completely. It is not shared by the first and, as a result, by the copy.

🚨If you are first time visiting our Telegram Channel then don't forget to JOIN and get Data Science related regular updates.

Check our latest YouTube video in which we have covered SQL interview Round Data Science questions asked by Meta Company. Link given below

👉🏻https://youtu.be/5TxFECLgd5c

Date: 06th Sept, 2022
Company: Datanyze
Role: Data Analyst
Topic: Excel, Tableau, PowerBI

Q1. What are sets and groups in Tableau?

Sets and groups are used group data based on some specific conditions. The main difference between these two is that a group can divide the dataset into multiple groups whereas a set can have only two options which is either in or out. A user should choose to apply group or sets based on the requirements.

Q2. What is Power Pivot & Power Query?

Power Pivot is an add-on provided by Microsoft for Excel since 2010. Power Pivot was designed to extend the analytical capabilities and services of Microsoft Excel.

Power Query is a business intelligence tool designed by Microsoft for Excel. Power Query allows you to import data from various data sources and will enable you to clean, transform and reshape your data as per the requirements. Power Query allows you to write your query once and then run it with a simple refresh.


Q3. 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
Try to use integers or Booleans in calculations as they are much faster than strings
Hide unused fields
Use Context filters
Reduce filter usage and use some alternative way to achieve the same result
Use indexing in tables and use the same fields for filtering
Remove unnecessary calculations and sheets.

Q4. What is macro in excel?

Macro refers to an algorithm or a set of actions that help automate a task in Excel by recording and playing back the steps taken to complete that task. Once the steps are stored, you create a Macro, and it can be edited and played back as many times as the user wants.

Macro is great for repetitive tasks and also eliminates errors. For example, suppose an account manager has to share reports regarding the company employees for non-payment of dues. In that case, it can be automated using a Macro and doing minor changes every month, as needed.

🚨If you are first time visiting our Telegram Channel then don't forget to JOIN and get Data Science related regular updates.

Date: 07th Sept, 2022
Company name: Tiger Analytics
Role: Data Scientist
Topic: Machine learning

1. How is Data modeling different from Database design?

Data Modeling: It can be considered as the first step towards the design of a database. Data modeling creates a conceptual model based on the relationship between various data models. The process involves moving from the conceptual stage to the logical model to the physical schema. It involves the systematic method of applying data modeling techniques.
Database Design: This is the process of designing the database. The database design creates an output which is a detailed data model of the database. Strictly speaking, database design includes the detailed logical model of a database but it can also include physical design choices and storage parameters.


2. What is the benefit of dimensionality reduction?

Dimensionality reduction reduces the dimensions and size of the entire dataset. It drops unnecessary features while retaining the overall information in the data intact. Reduction in dimensions leads to faster processing of the data.
The reason why data with high dimensions is considered so difficult to deal with is that it leads to high time consumption while processing the data and training a model on it. Reducing dimensions speeds up this process, removes noise, and also leads to better model accuracy.


3. Explain stacking in Data Science.

Just like bagging and boosting, stacking is also an ensemble learning method. In bagging and boosting, we could only combine weak models that used the same learning algorithms, e.g., logistic regression. These models are called homogeneous learners.
However, in stacking, we can combine weak models that use different learning algorithms as well. These learners are called heterogeneous learners. Stacking works by training multiple (and different) weak models or learners and then using them together by training another model, called a meta-model, to make predictions based on the multiple outputs of predictions returned by these multiple weak models.

🚨If you are first time visiting our Telegram Channel then don't forget to JOIN and get Data Science related regular updates. Happy Learning 💙

Date: 08th Sept, 2022
Company Name: Fractal Analytics
Role: Data Analyst
Topic: SQL, python, PowerBI

1. What is SQL Injection?

SQL injection is a sort of flaw in website and web app code that allows attackers to take control of back-end processes and access, retrieve, and delete sensitive data stored in databases. In this approach, malicious SQL statements are entered into a database entry field, and the database becomes exposed to an attacker once they are executed. By utilising data-driven apps, this strategy is widely utilised to get access to sensitive data and execute administrative tasks on databases.


2. How do you create a hyperlink in Excel?

Hyperlinks are used to navigate between worksheets and files/websites. To create a hyperlink, the shortcut used is Ctrl+K.
The ‘Insert Hyperlink’ box appears. Enter the address and the text to display.


3. What is DAX in Power BI?

DAX stands for Data Analysis Expressions. It's a collection of functions, operators, and constants used in formulas to calculate and return values. In other words, it helps you create new info from data you already have.


4. What is the difference between deep and shallow copy in python?

Ans: Shallow copy is used when a new instance type gets created and it keeps the values that are copied in the new instance. Shallow copy is used to copy the reference pointers just like it copies the values. Deep copy is used to store the values that are already copied. Deep copy doesn’t copy the reference pointers to the objects. It makes the reference to an object and the new object that is pointed by some other object gets stored.

————————————————————-

🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS WITH CLOUDYML FROM SCRATCH. TRUSTED BY 8000+ HAPPY LEARNERS

This course package, you are getting Python, SQL, Statistics, Machine Learning, Deep Learning, AWS Sagemaker, Model Deployment, Tableau, PowerBi, DSA, Amazon QuickSight, Google Data Studio, Excel, Case studies, Interview QnAs PDF, Capstone End-to-End Projects of ML and DL with 1-1 Live Doubt Clearance Support over Skype chat everyday. Check the course NOW!

Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo

🚨100+ Important Data Science Interview Questions PDF

👉🏻Save It Now