Date: 09th Sept, 2022
Company name: Blinkit
Role: SQL developer
Topic: SQL
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 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.
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Company name: Blinkit
Role: SQL developer
Topic: SQL
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 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.
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Role: Data Analyst
Company: Scouto (Acquired By Spinny)
Exp: 0-4 yr(fresher can apply)
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Company: Meritus Intelytics
Exp: Fresher
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Title: Ohm Analytics
Exp: Fresher
Link: https://ai.cloudyml.com/3BsoQl5
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Company: Fortune Credit Capital Ltd.
Exp: Fresher
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Role: Data Analyst
Company: Scouto (Acquired By Spinny)
Exp: 0-4 yr(fresher can apply)
Link: https://ai.cloudyml.com/3RO3eoD
Role: Business Analyst (Analytics)
Company: Meritus Intelytics
Exp: Fresher
Link: https://ai.cloudyml.com/3xy5PLV
Role: Data Analyst
Title: Ohm Analytics
Exp: Fresher
Link: https://ai.cloudyml.com/3BsoQl5
Role: Business Analyst - NBFC
Company: Fortune Credit Capital Ltd.
Exp: Fresher
Link: https://ai.cloudyml.com/3QwcX1C
ALL THE BEST💙
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Good Technical Skills, Good Projects and a Good Resume can make you ready for the Data Science Interviews and you are getting everything in our course.
Visit our website and Check the course reviews and then Enroll.
👉🏻Course Link - https://ai.cloudyml.com/Mega-Combo
It Covers all the important topics which are required to become interview ready from scratch with 1-1 Live Doubt Clearance Support.
✅Python
✅SQL
✅Maths & Statistics
✅Machine Learning
✅Deep Learning
✅AWS Sagamaker
✅Model Deployment
✅Tableau
✅PowerBi
✅MS Excel
✅DSA
✅AWS QuickSight
✅Google Data Studio
✅Interview QnA PDFs
✅Capstone Projects
Combined Price of all the courses is Rs. 29980/- but you can get all the courses at Mega Combo offer of Rs.7999/- for today.
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Date: 10th Sept, 2022
Company name: Walmart
Role: ML Engineer
Topic: machine learning
1. Explain the difference between L1 and L2 regularization.
Answer: L2 regularization tends to spread error among all the terms, while L1 is more binary/sparse, with many variables either being assigned a 1 or 0 in weighting. L1 corresponds to setting a Laplacean prior on the terms, while L2 corresponds to a Gaussian prior.
2. What cross-validation technique would you use on a time series dataset?
Answer: Instead of using standard k-folds cross-validation, you have to pay attention to the fact that a time series is not randomly distributed data—it is inherently ordered by chronological order. If a pattern emerges in later time periods, for example, your model may still pick up on it even if that effect doesn’t hold in earlier years!
You’ll want to do something like forward chaining where you’ll be able to model on past data then look at forward-facing data.
• Fold 1 : training [1], test [2]
• Fold 2 : training [1 2], test [3]
• Fold 3 : training [1 2 3], test [4]
• Fold 4 : training [1 2 3 4], test [5]
• Fold 5 : training [1 2 3 4 5], test [6]
3. What’s the “kernel trick” and how is it useful?
Answer: The Kernel trick involves kernel functions that can enable in higher-dimension spaces without explicitly calculating the coordinates of points within that dimension: instead, kernel functions compute the inner products between the images of all pairs of data in a feature space. This allows them the very useful attribute of calculating the coordinates of higher dimensions while being computationally cheaper than the explicit calculation of said coordinates.
4. Explain how a ROC curve works.
Answer: The ROC curve is a graphical representation of the contrast between true positive rates and the false positive rate at various thresholds. It’s often used as a proxy for the trade-off between the sensitivity of the model (true positives) vs the fall-out or the probability it will trigger a false alarm (false positives).
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Company name: Walmart
Role: ML Engineer
Topic: machine learning
1. Explain the difference between L1 and L2 regularization.
Answer: L2 regularization tends to spread error among all the terms, while L1 is more binary/sparse, with many variables either being assigned a 1 or 0 in weighting. L1 corresponds to setting a Laplacean prior on the terms, while L2 corresponds to a Gaussian prior.
2. What cross-validation technique would you use on a time series dataset?
Answer: Instead of using standard k-folds cross-validation, you have to pay attention to the fact that a time series is not randomly distributed data—it is inherently ordered by chronological order. If a pattern emerges in later time periods, for example, your model may still pick up on it even if that effect doesn’t hold in earlier years!
You’ll want to do something like forward chaining where you’ll be able to model on past data then look at forward-facing data.
• Fold 1 : training [1], test [2]
• Fold 2 : training [1 2], test [3]
• Fold 3 : training [1 2 3], test [4]
• Fold 4 : training [1 2 3 4], test [5]
• Fold 5 : training [1 2 3 4 5], test [6]
3. What’s the “kernel trick” and how is it useful?
Answer: The Kernel trick involves kernel functions that can enable in higher-dimension spaces without explicitly calculating the coordinates of points within that dimension: instead, kernel functions compute the inner products between the images of all pairs of data in a feature space. This allows them the very useful attribute of calculating the coordinates of higher dimensions while being computationally cheaper than the explicit calculation of said coordinates.
4. Explain how a ROC curve works.
Answer: The ROC curve is a graphical representation of the contrast between true positive rates and the false positive rate at various thresholds. It’s often used as a proxy for the trade-off between the sensitivity of the model (true positives) vs the fall-out or the probability it will trigger a false alarm (false positives).
🚨
🎉1
Important Data Science Interview QnAs by CloudyML.pdf
681.3 KB
📒 Check Some Frequently Asked #Data_Science #Interview QnAs That Will Help You In Your Data Scientist #Job Preparation
Download Now and Save It.
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Find The Output
print('[%x]' % 1729)
print('[%x]' % 1729)
Anonymous Quiz
21%
[x1729]
26%
[1729]
11%
[6c1]
4%
[9c1]
39%
Error
Date: 11th Sept, 2022
Company: CapGemini
Role: Data Analyst
Topic: SQL, Excel, Tableau
1. What is the case when in SQL Server?
The CASE statement is used to construct logic in which one column’s value is determined by the values of other columns.
At least one set of WHEN and THEN commands makes up the SQL Server CASE Statement. The condition to be tested is specified by the WHEN statement. If the WHEN condition returns TRUE, the THEN sentence explains what to do.
When none of the WHEN conditions return true, the ELSE statement is executed. The END keyword brings the CASE statement to a close.
2. What is a relationship in SQL and what are they?
Database Relationship is defined as the connection between the tables in a database. There are various data base relationships, and they are as follows:.
One to One Relationship.
One to Many Relationship.
Many to One Relationship.
Self-Referencing Relationship.
3. What is the use of cycle fields in tableau?
Cycle fields help in switching and trying different colour combinations or views in a cyclic order. It will work only if we have a chart that allows more than one measure such as stacked bar chart and we are unable to finalize the visualizations then we can use cycle fields. To use cycle field, click on analysis menu in the toolbar then select cycle fields to take a quick look at an alternative visualization.
4. What is the difference between a function and a formula in Excel?
A formula is a user-defined expression that calculates a value. A function is pre-defined built-in operation that can take the specified number of arguments. A user can create formulas that can be complex and can have multiple functions in it. For example, =A1+A2 is a formula and =SUM(A1:A10) is a function.
🚨If you are first time visiting our Telegram Channel then don't forget to JOIN and get Data Science related regular updates. Happy Learning 💙
Company: CapGemini
Role: Data Analyst
Topic: SQL, Excel, Tableau
1. What is the case when in SQL Server?
The CASE statement is used to construct logic in which one column’s value is determined by the values of other columns.
At least one set of WHEN and THEN commands makes up the SQL Server CASE Statement. The condition to be tested is specified by the WHEN statement. If the WHEN condition returns TRUE, the THEN sentence explains what to do.
When none of the WHEN conditions return true, the ELSE statement is executed. The END keyword brings the CASE statement to a close.
2. What is a relationship in SQL and what are they?
Database Relationship is defined as the connection between the tables in a database. There are various data base relationships, and they are as follows:.
One to One Relationship.
One to Many Relationship.
Many to One Relationship.
Self-Referencing Relationship.
3. What is the use of cycle fields in tableau?
Cycle fields help in switching and trying different colour combinations or views in a cyclic order. It will work only if we have a chart that allows more than one measure such as stacked bar chart and we are unable to finalize the visualizations then we can use cycle fields. To use cycle field, click on analysis menu in the toolbar then select cycle fields to take a quick look at an alternative visualization.
4. What is the difference between a function and a formula in Excel?
A formula is a user-defined expression that calculates a value. A function is pre-defined built-in operation that can take the specified number of arguments. A user can create formulas that can be complex and can have multiple functions in it. For example, =A1+A2 is a formula and =SUM(A1:A10) is a function.
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Date: 12th September, 2022
Company name: Datanyze
Role: Data Scientist
Topic: SQL, 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.
————————————————————-
🚨MAKE YOUR CAREER IN DATA SCIENCE AND ANALYTICS WITH CLOUDYML FROM SCRATCH. TRUSTED BY 8000+ HAPPY LEARNERS
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Course Link👉🏻 https://ai.cloudyml.com/Mega-Combo
Company name: Datanyze
Role: Data Scientist
Topic: SQL, 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.
————————————————————-
🚨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
Good Technical Skills, Good Projects and a Good Resume can make you ready for the Data Science Interviews and you are getting everything in our course.
It Covers all the important topics which are required to become interview ready from scratch with 1-1 Live Doubt Clearance Support.
✅Python
✅SQL
✅Maths & Statistics
✅Machine Learning
✅Deep Learning
✅AWS Sagamaker
✅Model Deployment
✅Tableau
✅PowerBi
✅MS Excel
✅DSA
✅AWS QuickSight
✅Google Data Studio
✅Interview QnA PDFs
✅Capstone Projects
Combined Price of all the courses is Rs. 29980/- but you can get all the courses at Mega Combo offer of Rs.7999/- for today.
Follow the link below and visit our website and become Interview Ready.
👉🏻Course Link - https://ai.cloudyml.com/Mega-Combo
It Covers all the important topics which are required to become interview ready from scratch with 1-1 Live Doubt Clearance Support.
✅Python
✅SQL
✅Maths & Statistics
✅Machine Learning
✅Deep Learning
✅AWS Sagamaker
✅Model Deployment
✅Tableau
✅PowerBi
✅MS Excel
✅DSA
✅AWS QuickSight
✅Google Data Studio
✅Interview QnA PDFs
✅Capstone Projects
Combined Price of all the courses is Rs. 29980/- but you can get all the courses at Mega Combo offer of Rs.7999/- for today.
Follow the link below and visit our website and become Interview Ready.
👉🏻Course Link - https://ai.cloudyml.com/Mega-Combo
Understand the difference between Normalization and Standardization in Machine Learning. Watch our latest video now. Link below
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Date: 13-09-2022
Company name: IKEA
Role: Data Analyst
Topic: Stats, SQL
1. How can we deal with problems that arise when the data flows in from a variety of sources?
There are many ways to go about dealing with multi-source problems. However, these are done primarily to solve the problems of:
Identifying the presence of similar/same records and merging them into a single recordRe-structuring the schema to ensure there is good schema integration
2. Where is Time Series Analysis used?
Since time series analysis (TSA) has a wide scope of usage, it can be used in multiple domains. Here are some of the places where TSA plays an important role:
Statistics
Signal processing
Econometrics
Weather forecasting
Earthquake prediction
Astronomy
Applied science
3. What are the ideal situations in which t-test or z-test can be used?
It is a standard practice that a t-test is used when there is a sample size less than 30 and the z-test is considered when the sample size exceeds 30 in most cases.
4. What is the usage of the NVL() function?
The NVL() function is used to convert the NULL value to the other value. The function returns the value of the second parameter if the first parameter is NULL. If the first parameter is anything other than NULL, it is left unchanged. This function is used in Oracle, not in SQL and MySQL. Instead of NVL() function, MySQL have IFNULL() and SQL Server have ISNULL() function.
————————————————————-
🚨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
Company name: IKEA
Role: Data Analyst
Topic: Stats, SQL
1. How can we deal with problems that arise when the data flows in from a variety of sources?
There are many ways to go about dealing with multi-source problems. However, these are done primarily to solve the problems of:
Identifying the presence of similar/same records and merging them into a single recordRe-structuring the schema to ensure there is good schema integration
2. Where is Time Series Analysis used?
Since time series analysis (TSA) has a wide scope of usage, it can be used in multiple domains. Here are some of the places where TSA plays an important role:
Statistics
Signal processing
Econometrics
Weather forecasting
Earthquake prediction
Astronomy
Applied science
3. What are the ideal situations in which t-test or z-test can be used?
It is a standard practice that a t-test is used when there is a sample size less than 30 and the z-test is considered when the sample size exceeds 30 in most cases.
4. What is the usage of the NVL() function?
The NVL() function is used to convert the NULL value to the other value. The function returns the value of the second parameter if the first parameter is NULL. If the first parameter is anything other than NULL, it is left unchanged. This function is used in Oracle, not in SQL and MySQL. Instead of NVL() function, MySQL have IFNULL() and SQL Server have ISNULL() function.
————————————————————-
🚨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
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🚨JOB OPENING ALERT🚨
Role: Business Analyst
Company: Mcoxley
Exp: Fresher
Link: https://ai.cloudyml.com/3RDI0dy
Role: Computer Vision Engineer
Company: Sensovision
Exp: Fresher
Link: https://ai.cloudyml.com/3ddGPCn
Role: Data Scientist/AIML Engineer
Company: Upgrad
Exp: Fresher
Link: https://ai.cloudyml.com/3xk0xmY
Role: Analyst - Risk And Compliance
Company: IBM
Exp: Fresher
Link: https://ai.cloudyml.com/3RVCena
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Happy Learning 💙
Role: Business Analyst
Company: Mcoxley
Exp: Fresher
Link: https://ai.cloudyml.com/3RDI0dy
Role: Computer Vision Engineer
Company: Sensovision
Exp: Fresher
Link: https://ai.cloudyml.com/3ddGPCn
Role: Data Scientist/AIML Engineer
Company: Upgrad
Exp: Fresher
Link: https://ai.cloudyml.com/3xk0xmY
Role: Analyst - Risk And Compliance
Company: IBM
Exp: Fresher
Link: https://ai.cloudyml.com/3RVCena
🚨
Company name: Swiggy
Role: SQL Developer
Topic : SQL
1. What is a DEFAULT constraint?
Constraints in SQL are used to specify some sort of rules for processing data and limiting the type of data that can go into a table.
A default constraint is used to define a default value for a column so that it is added to all new records if no other value is specified.
2. What do you mean by data integrity?
Data integrity is the assurance of accuracy and consistency of data over its whole life cycle. It is a critical aspect of the design, implementation, and usage of systems that store, process, or retrieve data.
Data integrity also defines integrity constraints for enforcing business rules on data when it is entered into a database or application.
3. What is AUTO_INCREMENT?
AUTO_INCREMENT is used in SQL to automatically generate a unique number whenever a new record is inserted into a table.
Since the primary key is unique for each record, this primary field is added as the AUTO_INCREMENT field so that it is incremented when a new record is inserted.
4. What is the difference between DROP and TRUNCATE commands?
If a table is dropped, all things associated with that table are dropped as well. This includes the relationships defined on the table with other tables, access privileges, and grants that the table has, as well as the integrity checks and constraints.
However, if a table is truncated, there are no such problems as mentioned above. The table retains its original structure and the data is dropped.
————————————————————-
🚨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
Role: SQL Developer
Topic : SQL
1. What is a DEFAULT constraint?
Constraints in SQL are used to specify some sort of rules for processing data and limiting the type of data that can go into a table.
A default constraint is used to define a default value for a column so that it is added to all new records if no other value is specified.
2. What do you mean by data integrity?
Data integrity is the assurance of accuracy and consistency of data over its whole life cycle. It is a critical aspect of the design, implementation, and usage of systems that store, process, or retrieve data.
Data integrity also defines integrity constraints for enforcing business rules on data when it is entered into a database or application.
3. What is AUTO_INCREMENT?
AUTO_INCREMENT is used in SQL to automatically generate a unique number whenever a new record is inserted into a table.
Since the primary key is unique for each record, this primary field is added as the AUTO_INCREMENT field so that it is incremented when a new record is inserted.
4. What is the difference between DROP and TRUNCATE commands?
If a table is dropped, all things associated with that table are dropped as well. This includes the relationships defined on the table with other tables, access privileges, and grants that the table has, as well as the integrity checks and constraints.
However, if a table is truncated, there are no such problems as mentioned above. The table retains its original structure and the data is dropped.
————————————————————-
🚨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
Check Important Tableau Interview Questions asked in Data Analyst Interview. Watch our latest YouTube Video. Link given below
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Date: 15-09-2022
Company name: TCS
Role: Data Analyst
Topic: Statistics, Excel, Data analysis
1. What is the data analysis process?
Data analysis generally refers to the process of assembling, cleaning, interpreting, transforming, and modeling data to gain insights or conclusions and generate reports to help businesses become more profitable.
• Collect Data: The data is collected from a variety of sources and is then stored to be cleaned and prepared. This step involves removing all missing values and outliers.
• Analyse Data: As soon as the data is prepared, the next step is to analyze it. Improvements are made by running a model repeatedly. Following that, the model is validated to ensure that it is meeting the requirements.
• Create Reports: In the end, the model is implemented, and reports are generated as well as distributed to stakeholders.
2. Explain two different ways to detect outliers.
• Box Plot Method: According to this method, the value is considered an outlier if it exceeds or falls below 1.5*IQR (interquartile range), that is, if it lies above the top quartile (Q3) or below the bottom quartile (Q1).
• Standard Deviation Method: According to this method, an outlier is defined as a value that is greater or lower than the mean ± (3*standard deviation)
3. What is a Pivot table? Write its usage.
One of the basic tools for data analysis is the Pivot Table. With this feature, you can quickly summarize large datasets in Microsoft Excel. Using it, we can turn columns into rows and rows into columns. Furthermore, it permits grouping by any field (column) and applying advanced calculations to them. It is an extremely easy-to-use program since you just drag and drop rows/columns headers to build a report.
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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!
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Company name: TCS
Role: Data Analyst
Topic: Statistics, Excel, Data analysis
1. What is the data analysis process?
Data analysis generally refers to the process of assembling, cleaning, interpreting, transforming, and modeling data to gain insights or conclusions and generate reports to help businesses become more profitable.
• Collect Data: The data is collected from a variety of sources and is then stored to be cleaned and prepared. This step involves removing all missing values and outliers.
• Analyse Data: As soon as the data is prepared, the next step is to analyze it. Improvements are made by running a model repeatedly. Following that, the model is validated to ensure that it is meeting the requirements.
• Create Reports: In the end, the model is implemented, and reports are generated as well as distributed to stakeholders.
2. Explain two different ways to detect outliers.
• Box Plot Method: According to this method, the value is considered an outlier if it exceeds or falls below 1.5*IQR (interquartile range), that is, if it lies above the top quartile (Q3) or below the bottom quartile (Q1).
• Standard Deviation Method: According to this method, an outlier is defined as a value that is greater or lower than the mean ± (3*standard deviation)
3. What is a Pivot table? Write its usage.
One of the basic tools for data analysis is the Pivot Table. With this feature, you can quickly summarize large datasets in Microsoft Excel. Using it, we can turn columns into rows and rows into columns. Furthermore, it permits grouping by any field (column) and applying advanced calculations to them. It is an extremely easy-to-use program since you just drag and drop rows/columns headers to build a report.
————————————————————-
🚨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
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