Essential tools and skills required to become a data analyst ππ
### Data Analysis and Visualization:
1. Microsoft Excel: Essential for data manipulation, analysis, and basic modeling.
2. SQL (Structured Query Language): Crucial for querying databases and extracting data for analysis.
3. Tableau or Power BI: Powerful tools for creating interactive dashboards and visualizing data.
### Programming and Data Manipulation:(Optional)
4. Python: Used for data manipulation, scripting, and automation.
5. R: Useful for statistical computing, data visualization, and basic analytics.
### Statistical Analysis:
6. Statistical Software (SPSS, SAS): Tools for advanced statistical analysis and modeling.(Optional)
7. Advanced Excel Functions: Proficiency in pivot tables, VLOOKUP, statistical functions, and data cleaning techniques.
### Project Management and Collaboration:(Optional)
8. Jira or Trello: Tools for project management, task tracking, and collaboration.
9. Confluence or SharePoint: Platforms for documentation, collaboration, and knowledge sharing.
### Business Process Management:(Optional)
10. Business Process Modeling Tools (Visio, Lucidchart): Used for modeling, analyzing, and optimizing business processes.
### Additional Skills:
11. Google Analytics: Important for understanding website traffic and user behavior. (Optional)
12. CRM Systems (Salesforce, HubSpot): Knowledge of these systems aids in analyzing sales data and customer interactions.(Optional)
13. Version Control (Git): Helps manage changes in analytical projects and ensures versioning control. (Optional)
### Data Warehousing and Database Management:
14. Data Warehousing (Amazon Redshift, Google BigQuery): Knowledge of these platforms for handling large-scale datasets and optimizing queries. (Optional)
### Soft Skills:
15. Communication: Clear and concise communication of findings and recommendations.
16. Problem-Solving & Critical Thinking: Ability to analyze complex problems and derive actionable insights.
I know this list might seem extensive, so it's best to begin with mastering Excel, Power BI, and SQL. As you progress, you can gradually add other tools from the list based on specific project needs and requirements.
Here are some essential telegram channels with important resources:
β― SQL β t.iss.one/sqlanalyst
β― Power BI β @PowerBI_analyst
β― Resources β @learndataanalysis
β― Excel β t.iss.one/excel_analyst
β― Data Portfolio β @DataPortfolio
Also, try building projects & data portfolio while learning these skills. Creating data analytics projects will help you in showcasing the skills while giving job interviews.
Join @free4unow_backup for more resources
ENJOY LEARNINGππ
### Data Analysis and Visualization:
1. Microsoft Excel: Essential for data manipulation, analysis, and basic modeling.
2. SQL (Structured Query Language): Crucial for querying databases and extracting data for analysis.
3. Tableau or Power BI: Powerful tools for creating interactive dashboards and visualizing data.
### Programming and Data Manipulation:(Optional)
4. Python: Used for data manipulation, scripting, and automation.
5. R: Useful for statistical computing, data visualization, and basic analytics.
### Statistical Analysis:
6. Statistical Software (SPSS, SAS): Tools for advanced statistical analysis and modeling.(Optional)
7. Advanced Excel Functions: Proficiency in pivot tables, VLOOKUP, statistical functions, and data cleaning techniques.
### Project Management and Collaboration:(Optional)
8. Jira or Trello: Tools for project management, task tracking, and collaboration.
9. Confluence or SharePoint: Platforms for documentation, collaboration, and knowledge sharing.
### Business Process Management:(Optional)
10. Business Process Modeling Tools (Visio, Lucidchart): Used for modeling, analyzing, and optimizing business processes.
### Additional Skills:
11. Google Analytics: Important for understanding website traffic and user behavior. (Optional)
12. CRM Systems (Salesforce, HubSpot): Knowledge of these systems aids in analyzing sales data and customer interactions.(Optional)
13. Version Control (Git): Helps manage changes in analytical projects and ensures versioning control. (Optional)
### Data Warehousing and Database Management:
14. Data Warehousing (Amazon Redshift, Google BigQuery): Knowledge of these platforms for handling large-scale datasets and optimizing queries. (Optional)
### Soft Skills:
15. Communication: Clear and concise communication of findings and recommendations.
16. Problem-Solving & Critical Thinking: Ability to analyze complex problems and derive actionable insights.
I know this list might seem extensive, so it's best to begin with mastering Excel, Power BI, and SQL. As you progress, you can gradually add other tools from the list based on specific project needs and requirements.
Here are some essential telegram channels with important resources:
β― SQL β t.iss.one/sqlanalyst
β― Power BI β @PowerBI_analyst
β― Resources β @learndataanalysis
β― Excel β t.iss.one/excel_analyst
β― Data Portfolio β @DataPortfolio
Also, try building projects & data portfolio while learning these skills. Creating data analytics projects will help you in showcasing the skills while giving job interviews.
Join @free4unow_backup for more resources
ENJOY LEARNINGππ
π2
introducing-data-science-machine-learning-python.pdf
14.6 MB
Introducing Data Science Machine Learning
Machine_Learning_With_Python_For_Everyone_Addison_Wesley_Professional.pdf
9 MB
Machine Learning with Python for Everyone
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1.6 MB
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GitHub For Dummies.pdf
45.5 MB
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Sarah Guthals, 2023
Sarah Guthals, 2023
π6β€4
Data Science Fundamentals for Python and MongoDB.pdf
7.2 MB
Data Science Fundamentals for Python and MongoDB
David Paper, 2018
David Paper, 2018
π9π1π1
Best YouTube Playlists for Data Science
βΆοΈ Python
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βΆοΈ Linear Algebra
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βΆοΈ Calculus
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βΆοΈ Ruby
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FREE RESOURCES TO LEARN MACHINE LEARNING
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Intro to ML by MIT Free Course
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
Machine Learning for Everyone FREE BOOK
https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
Advanced Machine Learning with Python Github
https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python
Practical Machine Learning Tools and Techniques Free Book
https://vk.com/doc10903696_437487078?hash=674d2f82c486ac525b&dl=ed6dd98cd9d60a642b
Python Machine Learning for beginners
https://t.iss.one/datasciencefun/1177?single
ENJOY LEARNING ππ
ππ
Intro to ML by MIT Free Course
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
Machine Learning for Everyone FREE BOOK
https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
Advanced Machine Learning with Python Github
https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python
Practical Machine Learning Tools and Techniques Free Book
https://vk.com/doc10903696_437487078?hash=674d2f82c486ac525b&dl=ed6dd98cd9d60a642b
Python Machine Learning for beginners
https://t.iss.one/datasciencefun/1177?single
ENJOY LEARNING ππ
π4β€1
Python.Machine.Learning.Projects.pdf
6.4 MB
Python Machine Learning Projects
ΠΠ²ΡΠΎΡ: Dr. Deepali R Vora
ΠΠ²ΡΠΎΡ: Dr. Deepali R Vora
β€11π4
βοΈ 25 Javascript Path Files Used To Store Sensitive Information In Web Application:-
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π7π2β€1
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4.5 MB
LEARNING VUE
Core Concepts and Practical Patterns for Reusable, Composable, and Scalable User Interfaces
(2024)
Core Concepts and Practical Patterns for Reusable, Composable, and Scalable User Interfaces
(2024)
π3β€2
Forwarded from SQL Programming Resources
SQL Complete .pdf
12.4 MB
SQL complete Guide β
By Marcin Blaszczyk
By Marcin Blaszczyk
π5β€4