Data Analysis with Excel
ππ
https://t.me/excel_analyst/2
Power BI DAX Functions
ππ
https://t.me/PowerBI_analyst/2
All about SQL
ππ
https://t.me/sqlanalyst/29
Python for data analysis
ππ
https://t.me/pythonanalyst/26
Statistics Book and other useful resources
ππ
https://t.me/DataAnalystInterview/34
ππ
https://t.me/excel_analyst/2
Power BI DAX Functions
ππ
https://t.me/PowerBI_analyst/2
All about SQL
ππ
https://t.me/sqlanalyst/29
Python for data analysis
ππ
https://t.me/pythonanalyst/26
Statistics Book and other useful resources
ππ
https://t.me/DataAnalystInterview/34
π18π6π2β€1π₯°1π€1π1
Here are top 40 commonly asked pyspark questions that you can prepare for interviews
ππ
https://t.me/sql_engineer/79
ππ
https://t.me/sql_engineer/79
Telegram
Data Engineers
Here are top 40 commonly asked pyspark questions that you can prepare for interviews.
π₯πππ -
1. What is an RDD in Apache Spark? Explain its characteristics.
2. How are RDDs fault-tolerant in Apache Spark?
3. What are the different ways to create RDDs inβ¦
π₯πππ -
1. What is an RDD in Apache Spark? Explain its characteristics.
2. How are RDDs fault-tolerant in Apache Spark?
3. What are the different ways to create RDDs inβ¦
π4
Hi Guys,
Here are some of the telegram channels which may help you in data analytics journey ππ
SQL: https://t.me/sqlanalyst
Power BI & Tableau: https://t.me/PowerBI_analyst
Excel: https://t.me/excel_analyst
Python: https://t.me/dsabooks
Jobs: https://t.me/jobs_SQL
Data Science: https://t.me/datasciencefree
Artificial intelligence: https://t.me/machinelearning_deeplearning
Data Engineering: https://t.me/sql_engineer
Hope it helps :)
Here are some of the telegram channels which may help you in data analytics journey ππ
SQL: https://t.me/sqlanalyst
Power BI & Tableau: https://t.me/PowerBI_analyst
Excel: https://t.me/excel_analyst
Python: https://t.me/dsabooks
Jobs: https://t.me/jobs_SQL
Data Science: https://t.me/datasciencefree
Artificial intelligence: https://t.me/machinelearning_deeplearning
Data Engineering: https://t.me/sql_engineer
Hope it helps :)
π€7π5β€4π₯°2π2
These are the top 5 skills (I think) you need as an entry-level data analyst:
1. Excel. It may not be fancy but it's still one of the most used tools in the business world. I can guarantee you will use it at some point.
2. SQL. You may not actually use SQL but it's worth learning. It's the language of databases and gives you a strong foundation for working with other data analysis tools.
3. A data viz tool. Look, I don't care if you learn Power BI, Tableau, or any other data viz tool. You need to be able to communicate insights in a way that makes sense to non-technical people.
4. Communication. This may actually be the most important skill. It doesn't matter if you can analyze data if you can't communicate why that analysis should matter.
5. Problem solving. You use data to answer business questions and...wait for it... solve problems. It's an absolutely essential skill to have.
The best part of this is that you very likely already have 2, if not 3, of these in a pretty good place.
Focus your efforts on the skills that will make a difference.
1. Excel. It may not be fancy but it's still one of the most used tools in the business world. I can guarantee you will use it at some point.
2. SQL. You may not actually use SQL but it's worth learning. It's the language of databases and gives you a strong foundation for working with other data analysis tools.
3. A data viz tool. Look, I don't care if you learn Power BI, Tableau, or any other data viz tool. You need to be able to communicate insights in a way that makes sense to non-technical people.
4. Communication. This may actually be the most important skill. It doesn't matter if you can analyze data if you can't communicate why that analysis should matter.
5. Problem solving. You use data to answer business questions and...wait for it... solve problems. It's an absolutely essential skill to have.
The best part of this is that you very likely already have 2, if not 3, of these in a pretty good place.
Focus your efforts on the skills that will make a difference.
π14β€4π₯°1
Struggling to stay motivated in your job search?
Try setting input goals first, then shift to output goals once youβre consistent.
Let me explain how this works with a real-life example.
Input Goals vs. Output Goals:
When starting, focus on input goals to build consistency.
For instance, if you're struggling to go to the gym, set a goal to show up every other day rather than aiming to lose 50 pounds.
Once youβre consistent, shift to output goals like losing 5 pounds a month.
Why This Works:
- Focus and Pressure: Output goals create a sense of urgency and focus.
- Efficiency: You find faster and more effective ways to achieve your goals.
- Persistence: Sticking with a strategy until it works builds resilience and problem-solving skills.
Action Time:
1) Start with Input Goals: If you're struggling with consistency, set small, manageable goals to build habits.
2) Shift to Output Goals: Once youβre consistent, set specific, measurable outcomes.
3) Don't Quit: Commit to your goals and find ways to make them work.
Try setting input goals first, then shift to output goals once youβre consistent.
Let me explain how this works with a real-life example.
Input Goals vs. Output Goals:
When starting, focus on input goals to build consistency.
For instance, if you're struggling to go to the gym, set a goal to show up every other day rather than aiming to lose 50 pounds.
Once youβre consistent, shift to output goals like losing 5 pounds a month.
Why This Works:
- Focus and Pressure: Output goals create a sense of urgency and focus.
- Efficiency: You find faster and more effective ways to achieve your goals.
- Persistence: Sticking with a strategy until it works builds resilience and problem-solving skills.
Action Time:
1) Start with Input Goals: If you're struggling with consistency, set small, manageable goals to build habits.
2) Shift to Output Goals: Once youβre consistent, set specific, measurable outcomes.
3) Don't Quit: Commit to your goals and find ways to make them work.
π13β€5π€1π1
Many people ask this common question βCan I get a job with just SQL and Excel?β or βCan I get a job with just Power BI and Python?β.
The answer to all of those questions is yes.
There are jobs that use only SQL, Tableau, Power BI, Excel, Python, or R or some combination of those.
However, the combination of tools you learn impacts the total number of jobs you are qualified for.
For example, letβs say with just SQL and Excel you are qualified for 10 jobs, but if you add Tableau to that, you are qualified for 50 jobs.
If you have a success rate of landing a job youβre qualified for of 4%, having 5 times as many jobs to go for greatly improves your odds of landing a job.
Does this mean you should go out there and learn every single skill any data analyst job requires?
NO!
Itβs about finding the core tools that many jobs want.
And, in my opinion, those tools are SQL, Excel, and a visualization tool.
With these three tools, you are qualified for the majority of entry level data jobs and many higher level jobs.
So, you can land a job with whatever tools youβre comfortable with.
But if you have the three tools above in your toolbelt, you will have many more jobs to apply for and greatly improve your chances of snagging one.
The answer to all of those questions is yes.
There are jobs that use only SQL, Tableau, Power BI, Excel, Python, or R or some combination of those.
However, the combination of tools you learn impacts the total number of jobs you are qualified for.
For example, letβs say with just SQL and Excel you are qualified for 10 jobs, but if you add Tableau to that, you are qualified for 50 jobs.
If you have a success rate of landing a job youβre qualified for of 4%, having 5 times as many jobs to go for greatly improves your odds of landing a job.
Does this mean you should go out there and learn every single skill any data analyst job requires?
NO!
Itβs about finding the core tools that many jobs want.
And, in my opinion, those tools are SQL, Excel, and a visualization tool.
With these three tools, you are qualified for the majority of entry level data jobs and many higher level jobs.
So, you can land a job with whatever tools youβre comfortable with.
But if you have the three tools above in your toolbelt, you will have many more jobs to apply for and greatly improve your chances of snagging one.
π7β€2
ππ’π¬π π¨π ππ¨π¦π©ππ§π’ππ¬ ππ‘ππ π‘π’π«π ππππ ππ§ππ₯π²π¬ππ¬:
TMcKinsey & Company
Boston Consulting Group (BCG)
Bain & Company
Deloitte
PwC
Ernst & Young (EY)
KPMG
Accenture
Google
Amazon
Microsoft
IBM
Oracle
Tiger Analytics
Mu Sigma
Fractal Analytics
EXL Service
ZS Associates
Wells Fargo
Walmart
Target
LTIMindtree
Infosys
TCS (Tata Consultancy Services)
Wipro
HCL Technologies
Capgemini
Cognizant
These companies often hire data analysts to use data for making decisions and planning strategically for their clients.
TMcKinsey & Company
Boston Consulting Group (BCG)
Bain & Company
Deloitte
PwC
Ernst & Young (EY)
KPMG
Accenture
Amazon
Microsoft
IBM
Oracle
Tiger Analytics
Mu Sigma
Fractal Analytics
EXL Service
ZS Associates
Wells Fargo
Walmart
Target
LTIMindtree
Infosys
TCS (Tata Consultancy Services)
Wipro
HCL Technologies
Capgemini
Cognizant
These companies often hire data analysts to use data for making decisions and planning strategically for their clients.
π34
Data Analyst Interview QnA
1. Find avg of salaries department wise from table.
Answer-
2. What does Filter context in DAX mean?
Answer - Filter context in DAX refers to the subset of data that is actively being used in the calculation of a measure or in the evaluation of an expression. This context is determined by filters on the dashboard items like slicers, visuals, and filters pane which restrict the data being processed.
3. Explain how to implement Row-Level Security (RLS) in Power BI.
Answer - Row-Level Security (RLS) in Power BI can be implemented by:
- Creating roles within the Power BI service.
- Defining DAX expressions that specify the data each role can access.
- Assigning users to these roles either in Power BI or dynamically through AD group membership.
4. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
Answer -
5. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
Answer -
1. Find avg of salaries department wise from table.
Answer-
SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id;
2. What does Filter context in DAX mean?
Answer - Filter context in DAX refers to the subset of data that is actively being used in the calculation of a measure or in the evaluation of an expression. This context is determined by filters on the dashboard items like slicers, visuals, and filters pane which restrict the data being processed.
3. Explain how to implement Row-Level Security (RLS) in Power BI.
Answer - Row-Level Security (RLS) in Power BI can be implemented by:
- Creating roles within the Power BI service.
- Defining DAX expressions that specify the data each role can access.
- Assigning users to these roles either in Power BI or dynamically through AD group membership.
4. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
Answer -
d = {'apple': 2, 'banana': 5}
d['orange'] = 3 # Add element
d['apple'] = 4 # Modify element
sorted_d = dict(sorted(d.items())) # Sort dictionary
print(sorted_d)5. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
Answer -
from collections import Counter
numbers = [1, 2, 2, 3, 4, 5, 1, 6, 7, 3, 8, 1]
count = Counter(numbers)
duplicates = {k: v for k, v in count.items() if v > 1}
print(duplicates)
π27β€2π€1
Most asked SQL Interview Questions π―
1.) Explain order of execution of SQL.
2.) What is difference between where and having?
3.) What is the use of group by?
4.) Explain all types of joins in SQL?
5.) What are triggers in SQL?
6.) What is stored procedure in SQL
7.) Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8.) What is difference between Delete and Truncate?
9.) What is difference between DML, DDL and DCL?
10.) What are aggregate function and when do we use them? explain with few example.
11.) Which is faster between CTE and Subquery?
12.) What are constraints and types of Constraints?
13.) Types of Keys?
14.) Different types of Operators ?
15.) Difference between Group By and Where?
16.) What are Views?
17.) What are different types of constraints?
18.) What is difference between varchar and nvarchar?
19.) Similar for char and nchar?
20.) What are index and their types?
21.) What is an index? Explain its different types.
22.) List the different types of relationships in SQL.
23.) Differentiate between UNION and UNION ALL.
24.) How many types of clauses in SQL?
25.) What is the difference between UNION and UNION ALL in SQL?
26.) What are the various types of relationships in SQL?
27.) Difference between Primary Key and Secondary Key?
28.) What is the difference between where and having?
29.) Find the second highest salary of an employee?
30.) Write retention query in SQL?
31.) Write year-on-year growth in SQL?
32.) Write a query for cummulative sum in SQL?
33.) Difference between Function and Store procedure ?
34.) Do we use variable in views?
35.) What are the limitations of views?
Like this post if you need more πβ€οΈ
Hope it helps :)
1.) Explain order of execution of SQL.
2.) What is difference between where and having?
3.) What is the use of group by?
4.) Explain all types of joins in SQL?
5.) What are triggers in SQL?
6.) What is stored procedure in SQL
7.) Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8.) What is difference between Delete and Truncate?
9.) What is difference between DML, DDL and DCL?
10.) What are aggregate function and when do we use them? explain with few example.
11.) Which is faster between CTE and Subquery?
12.) What are constraints and types of Constraints?
13.) Types of Keys?
14.) Different types of Operators ?
15.) Difference between Group By and Where?
16.) What are Views?
17.) What are different types of constraints?
18.) What is difference between varchar and nvarchar?
19.) Similar for char and nchar?
20.) What are index and their types?
21.) What is an index? Explain its different types.
22.) List the different types of relationships in SQL.
23.) Differentiate between UNION and UNION ALL.
24.) How many types of clauses in SQL?
25.) What is the difference between UNION and UNION ALL in SQL?
26.) What are the various types of relationships in SQL?
27.) Difference between Primary Key and Secondary Key?
28.) What is the difference between where and having?
29.) Find the second highest salary of an employee?
30.) Write retention query in SQL?
31.) Write year-on-year growth in SQL?
32.) Write a query for cummulative sum in SQL?
33.) Difference between Function and Store procedure ?
34.) Do we use variable in views?
35.) What are the limitations of views?
Like this post if you need more πβ€οΈ
Hope it helps :)
π57β€7π5π1
Data Analyst Interview Resources
https://youtu.be/1-T-VBjLpJo?si=fo_RhbXC46Hg-FVE
I have kept the language as English so that everyone can understand. Please bear with my voice & video editing skills as I am pretty new to all this π
π7β€5
Youβre not a failure as a data analyst if:
β’ It takes you more than two months to land a job (remove the time expectation!)
β’ Complex concepts donβt immediately sink in
β’ You use Google/YouTube daily on the job (this is a sign youβre successful, actually)
β’ You donβt make as much money as others in the field
β’ You donβt code in 12 different languages (SQL is all you need. Add Python later if you want.)
β’ It takes you more than two months to land a job (remove the time expectation!)
β’ Complex concepts donβt immediately sink in
β’ You use Google/YouTube daily on the job (this is a sign youβre successful, actually)
β’ You donβt make as much money as others in the field
β’ You donβt code in 12 different languages (SQL is all you need. Add Python later if you want.)
π15π1π1
Essential SQL topics & free resources to practice sql.
ππ
https://youtu.be/VCZxODefTIs?si=1XB44uv5DIpcJA4K
Please like this video & subscribe my youtube channel so that I can bring more awesome videos. I would really appreciate any feedback in the comments :)
ππ
https://youtu.be/VCZxODefTIs?si=1XB44uv5DIpcJA4K
Please like this video & subscribe my youtube channel so that I can bring more awesome videos. I would really appreciate any feedback in the comments :)
π4
Data Analyst Interview QnA
1. Find avg of salaries department wise from table.
Answer-
2. What does Filter context in DAX mean?
Answer - Filter context in DAX refers to the subset of data that is actively being used in the calculation of a measure or in the evaluation of an expression. This context is determined by filters on the dashboard items like slicers, visuals, and filters pane which restrict the data being processed.
3. Explain how to implement Row-Level Security (RLS) in Power BI.
Answer - Row-Level Security (RLS) in Power BI can be implemented by:
- Creating roles within the Power BI service.
- Defining DAX expressions that specify the data each role can access.
- Assigning users to these roles either in Power BI or dynamically through AD group membership.
4. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
Answer -
5. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
Answer -
Like β€οΈ & Share the post if you want me to post more similar content. π
1. Find avg of salaries department wise from table.
Answer-
SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id;
2. What does Filter context in DAX mean?
Answer - Filter context in DAX refers to the subset of data that is actively being used in the calculation of a measure or in the evaluation of an expression. This context is determined by filters on the dashboard items like slicers, visuals, and filters pane which restrict the data being processed.
3. Explain how to implement Row-Level Security (RLS) in Power BI.
Answer - Row-Level Security (RLS) in Power BI can be implemented by:
- Creating roles within the Power BI service.
- Defining DAX expressions that specify the data each role can access.
- Assigning users to these roles either in Power BI or dynamically through AD group membership.
4. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys.
Answer -
d = {'apple': 2, 'banana': 5}
d['orange'] = 3 # Add element
d['apple'] = 4 # Modify element
sorted_d = dict(sorted(d.items())) # Sort dictionary
print(sorted_d)5. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated.
Answer -
from collections import Counter
numbers = [1, 2, 2, 3, 4, 5, 1, 6, 7, 3, 8, 1]
count = Counter(numbers)
duplicates = {k: v for k, v in count.items() if v > 1}
print(duplicates)
Like β€οΈ & Share the post if you want me to post more similar content. π
π14β€7π₯°1π1π1
Most Important Python Topics for Data Analyst Interview:
#Basics of Python:
1. Data Types
2. Lists
3. Dictionaries
4. Control Structures:
- if-elif-else
- Loops
5. Functions
6. Practice basic FAQs questions, below mentioned are few examples:
- How to reverse a string in Python?
- How to find the largest/smallest number in a list?
- How to remove duplicates from a list?
- How to count the occurrences of each element in a list?
- How to check if a string is a palindrome?
#Pandas:
1. Pandas Data Structures (Series, DataFrame)
2. Creating and Manipulating DataFrames
3. Filtering and Selecting Data
4. Grouping and Aggregating Data
5. Handling Missing Values
6. Merging and Joining DataFrames
7. Adding and Removing Columns
8. Exploratory Data Analysis (EDA):
- Descriptive Statistics
- Data Visualization with Pandas (Line Plots, Bar Plots, Histograms)
- Correlation and Covariance
- Handling Duplicates
- Data Transformation
#Numpy:
1. NumPy Arrays
2. Array Operations:
- Creating Arrays
- Slicing and Indexing
- Arithmetic Operations
#Integration with Other Libraries:
1. Basic Data Visualization with Pandas (Line Plots, Bar Plots)
#Key Concepts to Revise:
1. Data Manipulation with Pandas and NumPy
2. Data Cleaning Techniques
3. File Handling (reading and writing CSV files, JSON files)
4. Handling Missing and Duplicate Values
5. Data Transformation (scaling, normalization)
6. Data Aggregation and Group Operations
7. Combining and Merging Datasets
#Basics of Python:
1. Data Types
2. Lists
3. Dictionaries
4. Control Structures:
- if-elif-else
- Loops
5. Functions
6. Practice basic FAQs questions, below mentioned are few examples:
- How to reverse a string in Python?
- How to find the largest/smallest number in a list?
- How to remove duplicates from a list?
- How to count the occurrences of each element in a list?
- How to check if a string is a palindrome?
#Pandas:
1. Pandas Data Structures (Series, DataFrame)
2. Creating and Manipulating DataFrames
3. Filtering and Selecting Data
4. Grouping and Aggregating Data
5. Handling Missing Values
6. Merging and Joining DataFrames
7. Adding and Removing Columns
8. Exploratory Data Analysis (EDA):
- Descriptive Statistics
- Data Visualization with Pandas (Line Plots, Bar Plots, Histograms)
- Correlation and Covariance
- Handling Duplicates
- Data Transformation
#Numpy:
1. NumPy Arrays
2. Array Operations:
- Creating Arrays
- Slicing and Indexing
- Arithmetic Operations
#Integration with Other Libraries:
1. Basic Data Visualization with Pandas (Line Plots, Bar Plots)
#Key Concepts to Revise:
1. Data Manipulation with Pandas and NumPy
2. Data Cleaning Techniques
3. File Handling (reading and writing CSV files, JSON files)
4. Handling Missing and Duplicate Values
5. Data Transformation (scaling, normalization)
6. Data Aggregation and Group Operations
7. Combining and Merging Datasets
π25β€7π€2π1π1
The channel that changed the course of the lives of many Data Analysts on Telegram.
https://t.me/sqlspecialist
https://t.me/sqlspecialist
Telegram
Data Analytics
Perfect channel to learn Data Analytics
Learn SQL, Python, Alteryx, Tableau, Power BI and many more
For Promotions: @coderfun @love_data
Learn SQL, Python, Alteryx, Tableau, Power BI and many more
For Promotions: @coderfun @love_data
β€5π2π1π1