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Data Analyst

Overview, Education, Careers Types, Skills, Career Path, Resources

Data Analysts interpret data to improve business decisions. They gather, clean, and analyze data, identifying trends and providing insights to stakeholders.

Average Salary

₹6,00,000

Growth

high

Satisfaction

medium

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Functional Skills

Functional Skills are essential skills that help individuals perform tasks effectively in everyday life, work, and education.

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    Data Visualization
    -
    Statistical Analysis
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    SQL Database Management
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    Data Cleaning and Preprocessing
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    Programming Languages (Python, R)
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    Communication and Presentation Skills
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    Machine Learning Fundamentals
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    Critical Thinking and Problem-Solving
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    Business Acumen
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    Data Warehousing Concepts
Soft Skills

Communication, teamwork, and critical thinking to ensure seamless project execution.

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    Communication Skills
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    Problem-Solving
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    Critical Thinking
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    Attention to Detail
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    Teamwork and Collaboration
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    Adaptability and Flexibility
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    Time Management
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    Presentation Skills
Technical Skills

Technical Skills are specialized abilities and knowledge needed to perform specific tasks or functions.

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    SQL
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    Excel
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    Python
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    Data Visualization
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    Statistical Analysis
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    Data Cleaning and Preprocessing
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    R Programming
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    Tableau
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    Power BI
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    Machine Learning Basics
Duties and Responsiblities

Task

Work Activities

95%

Analyze data to identify trends, patterns, and insights for informed decisions.

92%

Apply statistical techniques to datasets, ensuring accuracy and relevance.

90%

Create detailed reports summarizing findings for stakeholders.

88%

Design charts and graphs to present data in an understandable format.

85%

Maintain and update databases to ensure data integrity and accessibility.

82%

Extract useful information from large datasets using advanced techniques.

80%

Develop models to forecast future trends and outcomes.

78%

Design and implement ETL processes to transform raw data.

75%

Ensure data accuracy and reliability through rigorous testing.

72%

Work with teams to understand data needs and provide solutions.

70%

Create and maintain documentation for data processes and models.

Detailed Work Profile

Collect and clean data from various sources, ensuring accuracy and consistency for analysis.

Analyze data using statistical techniques and tools to identify trends and patterns.

Develop and maintain databases and data systems to organize and store data effectively.

Create data visualizations, such as charts and graphs, to communicate findings to stakeholders.

Write reports summarizing data analysis results and providing actionable recommendations.

Collaborate with cross-functional teams to understand business needs and provide data-driven insights.

Design and implement data models and data pipelines to support data analysis efforts.

Perform data validation and quality checks to ensure data integrity.

Use programming languages like Python or R to automate data analysis tasks.

Apply machine learning techniques to build predictive models and improve business outcomes.

Present data analysis findings to clients or management in a clear and concise manner.

Stay up-to-date with industry trends and best practices in data analysis and visualization.

Develop and maintain documentation for data analysis processes and procedures.

Work with big data technologies like Hadoop and Spark to process large datasets.

Conduct A/B testing and analyze results to optimize marketing campaigns and product features.

Interests