39 companies hiring for data analyst role 👇👇
https://www.linkedin.com/posts/sqlspecialist_hi-guys-below-is-the-curated-list-of-39-activity-7242920445069410304-7z_I?utm_source=share&utm_medium=member_android
Like for more ❤️
https://www.linkedin.com/posts/sqlspecialist_hi-guys-below-is-the-curated-list-of-39-activity-7242920445069410304-7z_I?utm_source=share&utm_medium=member_android
Like for more ❤️
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Many people reached out to me saying telegram may get banned in their countries. So I've decided to create WhatsApp channels based on your interests 👇👇
Free Courses with Certificate: https://whatsapp.com/channel/0029Vamhzk5JENy1Zg9KmO2g
Data Analysts: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
MS Excel: https://whatsapp.com/channel/0029VaifY548qIzv0u1AHz3i
Jobs & Internship Opportunities:
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Python Free Books & Projects: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Java Resources: https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s
Coding Interviews: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
SQL: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Power BI: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
Programming Free Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
Data Science Projects: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
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Improve your communication skills: https://whatsapp.com/channel/0029VaiaucV4NVik7Fx6HN2n
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Free Courses with Certificate: https://whatsapp.com/channel/0029Vamhzk5JENy1Zg9KmO2g
Data Analysts: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
MS Excel: https://whatsapp.com/channel/0029VaifY548qIzv0u1AHz3i
Jobs & Internship Opportunities:
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Web Development: https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Python Free Books & Projects: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
Java Resources: https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s
Coding Interviews: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
SQL: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Power BI: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c
Programming Free Resources: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
Data Science Projects: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Learn Data Science & Machine Learning: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
Improve your communication skills: https://whatsapp.com/channel/0029VaiaucV4NVik7Fx6HN2n
Don’t worry Guys your contact number will stay hidden!
ENJOY LEARNING 👍👍
👍4❤2
✔️📚A beginner's roadmap for learning SQL:
🔺Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.
🔺Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.
🔺Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.
🔺Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.
🔺Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.
🔺Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.
🔺Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.
🔺Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
🔺Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).
🔺Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.
🔺Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.
🔺Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.
🔺Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.
🔺Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.
🔺Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.
👀👍Remember to practice regularly and build real-world projects to reinforce your learning.
Happy Learning 🥳 📚
🔺Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.
🔺Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.
🔺Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.
🔺Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.
🔺Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.
🔺Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.
🔺Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.
🔺Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
🔺Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).
🔺Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.
🔺Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.
🔺Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.
🔺Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.
🔺Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.
🔺Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.
👀👍Remember to practice regularly and build real-world projects to reinforce your learning.
Happy Learning 🥳 📚
👍11❤2
Complete checklist to learn SQL, Power BI, Excel, Python & Tableau.
You can access it for FREE here 👇
https://dataanalytics.beehiiv.com/p/data
Like this post if it helps 👍❤️
I'll try bringing more resources like these in the future to help you as much as I can.
You can access it for FREE here 👇
https://dataanalytics.beehiiv.com/p/data
Like this post if it helps 👍❤️
I'll try bringing more resources like these in the future to help you as much as I can.
👍10❤4
This Telegram channel is a true gem for anyone looking to build a career in data analytics 👇👇
https://t.iss.one/jobs_SQL
Generally, I don't go out of my way to appreciate other channels, but this one is really worth it. Whether you're hunting for data analyst jobs, or seeking interview tips, this channel has it all covered.
Hope it helps :)
https://t.iss.one/jobs_SQL
Generally, I don't go out of my way to appreciate other channels, but this one is really worth it. Whether you're hunting for data analyst jobs, or seeking interview tips, this channel has it all covered.
Hope it helps :)
Telegram
Data Analyst Jobs
🏆 Be the first one to know about the latest data analyst, data scientist, data engineer & business analyst job openings.
🏆 Learn everything about data analytics
Ads/ Promotions: @love_data
🏆 Learn everything about data analytics
Ads/ Promotions: @love_data
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🚀👉Data Analytics skills and projects to add in a resume to get shortlisted
1. Technical Skills:
Proficiency in data analysis tools (e.g., Python, R, SQL).
Data visualization skills using tools like Tableau or Power BI.
Experience with statistical analysis and modeling techniques.
2. Data Cleaning and Preprocessing:
Showcase skills in cleaning and preprocessing raw data for analysis.
Highlight expertise in handling missing data and outliers effectively.
3. Database Management:
Mention experience with databases (e.g., MySQL, PostgreSQL) for data retrieval and manipulation.
4. Machine Learning:
If applicable, include knowledge of machine learning algorithms and their application in data analytics projects.
5. Data Storytelling:
Emphasize your ability to communicate insights effectively through data storytelling.
6. Big Data Technologies:
If relevant, mention experience with big data technologies such as Hadoop or Spark.
7. Business Acumen:
Showcase an understanding of the business context and how your analytics work contributes to organizational goals.
8. Problem-Solving:
Highlight instances where you solved business problems through data-driven insights.
9. Collaboration and Communication:
Demonstrate your ability to work in a team and communicate complex findings to non-technical stakeholders.
10. Projects:
List specific data analytics projects you've worked on, detailing the problem, methodology, tools used, and the impact on decision-making.
11. Certifications:
Include relevant certifications such as those from platforms like Coursera, edX, or industry-recognized certifications in data analytics.
12. Continuous Learning:
Showcase any ongoing education, workshops, or courses to display your commitment to staying updated in the field.
💼Tailor your resume to the specific job description, emphasizing the skills and experiences that align with the requirements of the position you're applying for.
1. Technical Skills:
Proficiency in data analysis tools (e.g., Python, R, SQL).
Data visualization skills using tools like Tableau or Power BI.
Experience with statistical analysis and modeling techniques.
2. Data Cleaning and Preprocessing:
Showcase skills in cleaning and preprocessing raw data for analysis.
Highlight expertise in handling missing data and outliers effectively.
3. Database Management:
Mention experience with databases (e.g., MySQL, PostgreSQL) for data retrieval and manipulation.
4. Machine Learning:
If applicable, include knowledge of machine learning algorithms and their application in data analytics projects.
5. Data Storytelling:
Emphasize your ability to communicate insights effectively through data storytelling.
6. Big Data Technologies:
If relevant, mention experience with big data technologies such as Hadoop or Spark.
7. Business Acumen:
Showcase an understanding of the business context and how your analytics work contributes to organizational goals.
8. Problem-Solving:
Highlight instances where you solved business problems through data-driven insights.
9. Collaboration and Communication:
Demonstrate your ability to work in a team and communicate complex findings to non-technical stakeholders.
10. Projects:
List specific data analytics projects you've worked on, detailing the problem, methodology, tools used, and the impact on decision-making.
11. Certifications:
Include relevant certifications such as those from platforms like Coursera, edX, or industry-recognized certifications in data analytics.
12. Continuous Learning:
Showcase any ongoing education, workshops, or courses to display your commitment to staying updated in the field.
💼Tailor your resume to the specific job description, emphasizing the skills and experiences that align with the requirements of the position you're applying for.
👍10❤5
Complete roadmap to learn Python for data analysis
Step 1: Fundamentals of Python
1. Basics of Python Programming
- Introduction to Python
- Data types (integers, floats, strings, booleans)
- Variables and constants
- Basic operators (arithmetic, comparison, logical)
2. Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
- List comprehensions
3. Functions and Modules
- Defining functions
- Function arguments and return values
- Importing modules
- Built-in functions vs. user-defined functions
4. Data Structures
- Lists, tuples, sets, dictionaries
- Manipulating data structures (add, remove, update elements)
Step 2: Advanced Python
1. File Handling
- Reading from and writing to files
- Working with different file formats (txt, csv, json)
2. Error Handling
- Try, except blocks
- Handling exceptions and errors gracefully
3. Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance and polymorphism
- Encapsulation
Step 3: Libraries for Data Analysis
1. NumPy
- Understanding arrays and array operations
- Indexing, slicing, and iterating
- Mathematical functions and statistical operations
2. Pandas
- Series and DataFrames
- Reading and writing data (csv, excel, sql, json)
- Data cleaning and preparation
- Merging, joining, and concatenating data
- Grouping and aggregating data
3. Matplotlib and Seaborn
- Data visualization with Matplotlib
- Plotting different types of graphs (line, bar, scatter, histogram)
- Customizing plots
- Advanced visualizations with Seaborn
Step 4: Data Manipulation and Analysis
1. Data Wrangling
- Handling missing values
- Data transformation
- Feature engineering
2. Exploratory Data Analysis (EDA)
- Descriptive statistics
- Data visualization techniques
- Identifying patterns and outliers
3. Statistical Analysis
- Hypothesis testing
- Correlation and regression analysis
- Probability distributions
Step 5: Advanced Topics
1. Time Series Analysis
- Working with datetime objects
- Time series decomposition
- Forecasting models
2. Machine Learning Basics
- Introduction to machine learning
- Supervised vs. unsupervised learning
- Using Scikit-Learn for machine learning
- Building and evaluating models
3. Big Data and Cloud Computing
- Introduction to big data frameworks (e.g., Hadoop, Spark)
- Using cloud services for data analysis (e.g., AWS, Google Cloud)
Step 6: Practical Projects
1. Hands-on Projects
- Analyzing datasets from Kaggle
- Building interactive dashboards with Plotly or Dash
- Developing end-to-end data analysis projects
2. Collaborative Projects
- Participating in data science competitions
- Contributing to open-source projects
👨💻 FREE Resources to Learn & Practice Python
1. https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course
2. https://www.hackerrank.com/domains/python
3. https://www.hackerearth.com/practice/python/getting-started/numbers/practice-problems/
4. https://t.iss.one/PythonInterviews
5. https://www.w3schools.com/python/python_exercises.asp
6. https://t.iss.one/pythonfreebootcamp/134
7. https://t.iss.one/pythonanalyst
8. https://pythonbasics.org/exercises/
9. https://t.iss.one/pythondevelopersindia/300
10. https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
11. https://t.iss.one/pythonspecialist/33
Join @free4unow_backup for more free resources
ENJOY LEARNING 👍👍
Step 1: Fundamentals of Python
1. Basics of Python Programming
- Introduction to Python
- Data types (integers, floats, strings, booleans)
- Variables and constants
- Basic operators (arithmetic, comparison, logical)
2. Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
- List comprehensions
3. Functions and Modules
- Defining functions
- Function arguments and return values
- Importing modules
- Built-in functions vs. user-defined functions
4. Data Structures
- Lists, tuples, sets, dictionaries
- Manipulating data structures (add, remove, update elements)
Step 2: Advanced Python
1. File Handling
- Reading from and writing to files
- Working with different file formats (txt, csv, json)
2. Error Handling
- Try, except blocks
- Handling exceptions and errors gracefully
3. Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance and polymorphism
- Encapsulation
Step 3: Libraries for Data Analysis
1. NumPy
- Understanding arrays and array operations
- Indexing, slicing, and iterating
- Mathematical functions and statistical operations
2. Pandas
- Series and DataFrames
- Reading and writing data (csv, excel, sql, json)
- Data cleaning and preparation
- Merging, joining, and concatenating data
- Grouping and aggregating data
3. Matplotlib and Seaborn
- Data visualization with Matplotlib
- Plotting different types of graphs (line, bar, scatter, histogram)
- Customizing plots
- Advanced visualizations with Seaborn
Step 4: Data Manipulation and Analysis
1. Data Wrangling
- Handling missing values
- Data transformation
- Feature engineering
2. Exploratory Data Analysis (EDA)
- Descriptive statistics
- Data visualization techniques
- Identifying patterns and outliers
3. Statistical Analysis
- Hypothesis testing
- Correlation and regression analysis
- Probability distributions
Step 5: Advanced Topics
1. Time Series Analysis
- Working with datetime objects
- Time series decomposition
- Forecasting models
2. Machine Learning Basics
- Introduction to machine learning
- Supervised vs. unsupervised learning
- Using Scikit-Learn for machine learning
- Building and evaluating models
3. Big Data and Cloud Computing
- Introduction to big data frameworks (e.g., Hadoop, Spark)
- Using cloud services for data analysis (e.g., AWS, Google Cloud)
Step 6: Practical Projects
1. Hands-on Projects
- Analyzing datasets from Kaggle
- Building interactive dashboards with Plotly or Dash
- Developing end-to-end data analysis projects
2. Collaborative Projects
- Participating in data science competitions
- Contributing to open-source projects
👨💻 FREE Resources to Learn & Practice Python
1. https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course
2. https://www.hackerrank.com/domains/python
3. https://www.hackerearth.com/practice/python/getting-started/numbers/practice-problems/
4. https://t.iss.one/PythonInterviews
5. https://www.w3schools.com/python/python_exercises.asp
6. https://t.iss.one/pythonfreebootcamp/134
7. https://t.iss.one/pythonanalyst
8. https://pythonbasics.org/exercises/
9. https://t.iss.one/pythondevelopersindia/300
10. https://www.geeksforgeeks.org/python-programming-language/learn-python-tutorial
11. https://t.iss.one/pythonspecialist/33
Join @free4unow_backup for more free resources
ENJOY LEARNING 👍👍
👍15❤5
SQL Interview Ques & ANS 💥
👍19❤4🔥2