Best practices to follow while creating Tableau dashboards
ππ
https://www.linkedin.com/posts/sql-analysts_learn-tableau-activity-7195275749245784064-9TNf?utm_source=share&utm_medium=member_android
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https://www.linkedin.com/posts/sql-analysts_learn-tableau-activity-7195275749245784064-9TNf?utm_source=share&utm_medium=member_android
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This post is for freshers who get confused with the interview questions for the data roles.
Best tip from my side would be to start focusing on your SQL skills. Most of the data roles ask SQL questions based on joins & aggregate functions. Some interviewers may also ask questions based on window function. But, make your basics solid and practice it well.
If you are from non-coding background focus on your excel and bi skills. Learn vlookups, hlookups, pivot table, pivot charts and questions based on basic formulas.
But whatever the case is, stay resilient and believe on yourself. If unsure, start applying for jobs & give interviews. Even if you don't know the answers, don't worry. Even you don't crack the interview, don't worry. It's all part of this journey and you'll become better version of yourself with every small improvement.
Some resources I already shared on this channel: https://t.iss.one/learndataanalysis/911
Some you'll find here as well: https://t.iss.one/sqlspecialist
Hope it helps :)
Best tip from my side would be to start focusing on your SQL skills. Most of the data roles ask SQL questions based on joins & aggregate functions. Some interviewers may also ask questions based on window function. But, make your basics solid and practice it well.
If you are from non-coding background focus on your excel and bi skills. Learn vlookups, hlookups, pivot table, pivot charts and questions based on basic formulas.
But whatever the case is, stay resilient and believe on yourself. If unsure, start applying for jobs & give interviews. Even if you don't know the answers, don't worry. Even you don't crack the interview, don't worry. It's all part of this journey and you'll become better version of yourself with every small improvement.
Some resources I already shared on this channel: https://t.iss.one/learndataanalysis/911
Some you'll find here as well: https://t.iss.one/sqlspecialist
Hope it helps :)
π6β€2π1
Complete Python Topics for Data Analytics ππ
https://www.linkedin.com/posts/sql-analysts_python-cheatsheet-activity-7196728645044834307-BYgX?utm_source=share&utm_medium=member_android
Like for more β€οΈ
https://www.linkedin.com/posts/sql-analysts_python-cheatsheet-activity-7196728645044834307-BYgX?utm_source=share&utm_medium=member_android
Like for more β€οΈ
π4β€2
We are now a community of 50000+ members on LinkedIn
https://www.linkedin.com/company/sql-analysts/
Thanks for the support β€οΈ
https://www.linkedin.com/company/sql-analysts/
Thanks for the support β€οΈ
π6β€5
SAMPLE RESUME TEMPLATE FOR A DATA ANALYST(FRESHER)
Creating a resume as a fresher data analyst involves highlighting your education, skills, projects, and any relevant experience you have gained through internships, coursework, or personal projects.
Hereβs a structured resume template tailored for a fresher in data analysis:
[Your Name] [Your Address] [City, State, Zip Code] [Your Email Address] [Your Phone Number] [LinkedIn Profile] [GitHub Profile (if applicable)]
Objective:-
A motivated and detail-oriented data analyst with a strong foundation in statistics, data manipulation, and visualization. Seeking to leverage technical and analytical skills to solve complex problems and drive business insights in an entry-level data analyst role.
Education:-
Bachelor of Science in [Your Major] [Your University], [City, State]
Graduation Date: [Month, Year]
β Relevant Coursework: Data Structures, Statistics, Data Mining, Machine Learning, Database Management, Business Analytics
Technical Skills:-
β Programming Languages: Python, R, SQL
β Data Manipulation: pandas, NumPy
β Data Visualization: matplotlib, seaborn, ggplot2, Tableau, Power BI
β Databases: MySQL, PostgreSQL
β Tools: Excel, Jupyter Notebook, RStudio
β Other Skills: Data Cleaning, Data Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, Machine Learning Basics
Projects:-
Project Title 1
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 2
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 3
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Internships and Experience:-
Data Analyst Intern [Company Name], [City, State]
[Month, Year] β [Month, Year]
β Assisted in collecting, cleaning, and analyzing large datasets to support business decision-making.
β Developed dashboards and visualizations to present data insights to stakeholders.
β Conducted statistical analyses to identify trends and patterns in data.
Research Assistant [University Department or Lab], [City, State]
[Month, Year] β [Month, Year]
β Collaborated on research projects involving data collection, data entry, and preliminary data analysis.
β Used statistical software to analyze research data and prepare reports.
Certifications:-
β Google Data Analytics Professional Certificate
β Microsoft Certified: Data Analyst Associate
β [Any other relevant certification]
Extracurricular Activities:-
Member, Data Science Club, [Your University]
β Participated in data analysis competitions and hackathons.
β Attended workshops and seminars on data science and analytics.
Volunteer, [Organization Name]
β Contributed to data-driven projects that helped the organization improve its operations and outreach.
Additional Information:-
β Languages: [Any languages you speak other than English, if applicable]
β Interests: [Relevant interests that can show your passion for data and analysis, e.g., participating in Kaggle competitions, blogging about data science, etc.]
Data Analyst Jobs -> t.iss.one/jobs_SQL
Creating a resume as a fresher data analyst involves highlighting your education, skills, projects, and any relevant experience you have gained through internships, coursework, or personal projects.
Hereβs a structured resume template tailored for a fresher in data analysis:
[Your Name] [Your Address] [City, State, Zip Code] [Your Email Address] [Your Phone Number] [LinkedIn Profile] [GitHub Profile (if applicable)]
Objective:-
A motivated and detail-oriented data analyst with a strong foundation in statistics, data manipulation, and visualization. Seeking to leverage technical and analytical skills to solve complex problems and drive business insights in an entry-level data analyst role.
Education:-
Bachelor of Science in [Your Major] [Your University], [City, State]
Graduation Date: [Month, Year]
β Relevant Coursework: Data Structures, Statistics, Data Mining, Machine Learning, Database Management, Business Analytics
Technical Skills:-
β Programming Languages: Python, R, SQL
β Data Manipulation: pandas, NumPy
β Data Visualization: matplotlib, seaborn, ggplot2, Tableau, Power BI
β Databases: MySQL, PostgreSQL
β Tools: Excel, Jupyter Notebook, RStudio
β Other Skills: Data Cleaning, Data Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, Machine Learning Basics
Projects:-
Project Title 1
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 2
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 3
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Internships and Experience:-
Data Analyst Intern [Company Name], [City, State]
[Month, Year] β [Month, Year]
β Assisted in collecting, cleaning, and analyzing large datasets to support business decision-making.
β Developed dashboards and visualizations to present data insights to stakeholders.
β Conducted statistical analyses to identify trends and patterns in data.
Research Assistant [University Department or Lab], [City, State]
[Month, Year] β [Month, Year]
β Collaborated on research projects involving data collection, data entry, and preliminary data analysis.
β Used statistical software to analyze research data and prepare reports.
Certifications:-
β Google Data Analytics Professional Certificate
β Microsoft Certified: Data Analyst Associate
β [Any other relevant certification]
Extracurricular Activities:-
Member, Data Science Club, [Your University]
β Participated in data analysis competitions and hackathons.
β Attended workshops and seminars on data science and analytics.
Volunteer, [Organization Name]
β Contributed to data-driven projects that helped the organization improve its operations and outreach.
Additional Information:-
β Languages: [Any languages you speak other than English, if applicable]
β Interests: [Relevant interests that can show your passion for data and analysis, e.g., participating in Kaggle competitions, blogging about data science, etc.]
Data Analyst Jobs -> t.iss.one/jobs_SQL
π16π₯4β€1
If you're looking to build a career in Data Analytics but feel unsure about where to start, this post is for you.
It's important to know that you don't need to spend money on expensive courses to succeed in this field.
Many posts you see on LinkedIn promoting paid courses are often shared by individuals who are either trying to sell their own products or are being compensated to endorse these courses.
Through this post, I will share with you everything you need to start your data journey absolutely free.
π Source
Hope it helps :)
It's important to know that you don't need to spend money on expensive courses to succeed in this field.
Many posts you see on LinkedIn promoting paid courses are often shared by individuals who are either trying to sell their own products or are being compensated to endorse these courses.
Through this post, I will share with you everything you need to start your data journey absolutely free.
π Source
Hope it helps :)
π7β€3π₯°1
Step-by-step guide to master data analytics
ππ
https://www.linkedin.com/posts/sql-analysts_step-by-step-guide-to-master-data-analytics-activity-7200748815463649281-zPT2
ππ
https://www.linkedin.com/posts/sql-analysts_step-by-step-guide-to-master-data-analytics-activity-7200748815463649281-zPT2
Top 5 skills for DataAnalytics
1. Proficiency in programming languages like Python, R, or SQL.
2. Strong analytical and problem-solving skills.
3. Ability to work with data manipulation and visualization tools like Pandas, NumPy, Matplotlib, and Seaborn.
4. Knowledge of statistical analysis and machine learning techniques.
5. Effective communication and storytelling skills to convey insights from data to stakeholders.
1. Proficiency in programming languages like Python, R, or SQL.
2. Strong analytical and problem-solving skills.
3. Ability to work with data manipulation and visualization tools like Pandas, NumPy, Matplotlib, and Seaborn.
4. Knowledge of statistical analysis and machine learning techniques.
5. Effective communication and storytelling skills to convey insights from data to stakeholders.
π12π₯2
Want to become a data analyst?
Stage 1 β Excel
Stage 2 β SQL + Project
Stage 3 β Python (Pandas, NumPy) + Project
Stage 4 β Data Visualization (Matplotlib, Seaborn) + Project
Stage 5 β Statistics + Project
Stage 6 β Machine Learning (Scikit-learn) + Project
Stage 7 β Big Data Tools (Hadoop, Spark) + Project
π β DataAnalytics
Stage 1 β Excel
Stage 2 β SQL + Project
Stage 3 β Python (Pandas, NumPy) + Project
Stage 4 β Data Visualization (Matplotlib, Seaborn) + Project
Stage 5 β Statistics + Project
Stage 6 β Machine Learning (Scikit-learn) + Project
Stage 7 β Big Data Tools (Hadoop, Spark) + Project
π β DataAnalytics
π20β€13π€1
Important Interview Questions for SQL ππ
https://www.linkedin.com/posts/sql-analysts_preparing-for-an-sql-interview-here-are-activity-7201945469835476994-lI_m
https://www.linkedin.com/posts/sql-analysts_preparing-for-an-sql-interview-here-are-activity-7201945469835476994-lI_m
π6β€1
Python for everything
ππ
https://www.linkedin.com/posts/sql-analysts_many-people-charge-too-much-to-teach-python-activity-7204810034940153857-2Rlh
Like for more β€οΈ
ππ
https://www.linkedin.com/posts/sql-analysts_many-people-charge-too-much-to-teach-python-activity-7204810034940153857-2Rlh
Like for more β€οΈ
β€2π₯2
Excel Useful Shortcuts
ππ
https://www.linkedin.com/posts/sql-analysts_excel-activity-7205903255766282240-HH5D
ππ
https://www.linkedin.com/posts/sql-analysts_excel-activity-7205903255766282240-HH5D
π3
Thinking about becoming a Data Engineer? Here's the roadmap to avoid pitfalls & master the essential skills for a successful career.
ππ
https://t.iss.one/sql_engineer/62
ππ
https://t.iss.one/sql_engineer/62
π₯3
SAMPLE RESUME TEMPLATE FOR A DATA ANALYST(FRESHER)
Creating a resume as a fresher data analyst involves highlighting your education, skills, projects, and any relevant experience you have gained through internships, coursework, or personal projects.
Hereβs a structured resume template tailored for a fresher in data analysis:
[Your Name] [Your Address] [City, State, Zip Code] [Your Email Address] [Your Phone Number] [LinkedIn Profile] [GitHub Profile (if applicable)]
Objective:-
A motivated and detail-oriented data analyst with a strong foundation in statistics, data manipulation, and visualization. Seeking to leverage technical and analytical skills to solve complex problems and drive business insights in an entry-level data analyst role.
Education:-
Bachelor of Science in [Your Major] [Your University], [City, State]
Graduation Date: [Month, Year]
β Relevant Coursework: Data Structures, Statistics, Data Mining, Machine Learning, Database Management, Business Analytics
Technical Skills:-
β Programming Languages: Python, R, SQL
β Data Manipulation: pandas, NumPy
β Data Visualization: matplotlib, seaborn, ggplot2, Tableau, Power BI
β Databases: MySQL, PostgreSQL
β Tools: Excel, Jupyter Notebook, RStudio
β Other Skills: Data Cleaning, Data Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, Machine Learning Basics
Projects:-
Project Title 1
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 2
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 3
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Internships and Experience:-
Data Analyst Intern [Company Name], [City, State]
[Month, Year] β [Month, Year]
β Assisted in collecting, cleaning, and analyzing large datasets to support business decision-making.
β Developed dashboards and visualizations to present data insights to stakeholders.
β Conducted statistical analyses to identify trends and patterns in data.
Research Assistant [University Department or Lab], [City, State]
[Month, Year] β [Month, Year]
β Collaborated on research projects involving data collection, data entry, and preliminary data analysis.
β Used statistical software to analyze research data and prepare reports.
Certifications:-
β Google Data Analytics Professional Certificate
β Microsoft Certified: Data Analyst Associate
β [Any other relevant certification]
Extracurricular Activities:-
Member, Data Science Club, [Your University]
β Participated in data analysis competitions and hackathons.
β Attended workshops and seminars on data science and analytics.
Volunteer, [Organization Name]
β Contributed to data-driven projects that helped the organization improve its operations and outreach.
Additional Information:-
β Languages: [Any languages you speak other than English, if applicable]
β Interests: [Relevant interests that can show your passion for data and analysis, e.g., participating in Kaggle competitions, blogging about data science, etc.]
Data Analyst Jobs -> t.iss.one/jobs_SQL
Creating a resume as a fresher data analyst involves highlighting your education, skills, projects, and any relevant experience you have gained through internships, coursework, or personal projects.
Hereβs a structured resume template tailored for a fresher in data analysis:
[Your Name] [Your Address] [City, State, Zip Code] [Your Email Address] [Your Phone Number] [LinkedIn Profile] [GitHub Profile (if applicable)]
Objective:-
A motivated and detail-oriented data analyst with a strong foundation in statistics, data manipulation, and visualization. Seeking to leverage technical and analytical skills to solve complex problems and drive business insights in an entry-level data analyst role.
Education:-
Bachelor of Science in [Your Major] [Your University], [City, State]
Graduation Date: [Month, Year]
β Relevant Coursework: Data Structures, Statistics, Data Mining, Machine Learning, Database Management, Business Analytics
Technical Skills:-
β Programming Languages: Python, R, SQL
β Data Manipulation: pandas, NumPy
β Data Visualization: matplotlib, seaborn, ggplot2, Tableau, Power BI
β Databases: MySQL, PostgreSQL
β Tools: Excel, Jupyter Notebook, RStudio
β Other Skills: Data Cleaning, Data Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, Machine Learning Basics
Projects:-
Project Title 1
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 2
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Project Title 3
β Description: [Brief description of the project, the problem you solved, and the tools/technologies you used.]
β Key Achievements: [Highlight specific outcomes, insights derived, or skills applied.]
Internships and Experience:-
Data Analyst Intern [Company Name], [City, State]
[Month, Year] β [Month, Year]
β Assisted in collecting, cleaning, and analyzing large datasets to support business decision-making.
β Developed dashboards and visualizations to present data insights to stakeholders.
β Conducted statistical analyses to identify trends and patterns in data.
Research Assistant [University Department or Lab], [City, State]
[Month, Year] β [Month, Year]
β Collaborated on research projects involving data collection, data entry, and preliminary data analysis.
β Used statistical software to analyze research data and prepare reports.
Certifications:-
β Google Data Analytics Professional Certificate
β Microsoft Certified: Data Analyst Associate
β [Any other relevant certification]
Extracurricular Activities:-
Member, Data Science Club, [Your University]
β Participated in data analysis competitions and hackathons.
β Attended workshops and seminars on data science and analytics.
Volunteer, [Organization Name]
β Contributed to data-driven projects that helped the organization improve its operations and outreach.
Additional Information:-
β Languages: [Any languages you speak other than English, if applicable]
β Interests: [Relevant interests that can show your passion for data and analysis, e.g., participating in Kaggle competitions, blogging about data science, etc.]
Data Analyst Jobs -> t.iss.one/jobs_SQL
π14β€5