Fresher Data Analyst Data Science
Posted on :
13-10-2023
Employer Active
1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
13-10-2023
Job Description
Essential Data Analyst Skills:
Data analysts need a mix of technical, analytical, and soft skills to effectively analyze data and communicate their findings. Here are some essential skills for data analysts:
1. Data Cleaning and Preparation
Data analysts should know how to clean and prepare data for analysis. This includes removing errors, identifying outliers, and transforming data into a format that can be analyzed.
2. Data Analysis and Exploration
Data analysts need to be able to analyze data and explore it for insights. This includes using statistical methods to test hypotheses, identify trends, and make predictions.
3. Statistical Analysis
Understanding statistical tests and tools is crucial. Familiarity with mean, median, variance, standard deviation, correlation, regression, and hypothesis testing can be fundamental.
4. Programming
Knowledge of programming languages, especially:
Python: Libraries like pandas, numpy, and scikit-learn are essential for data manipulation and analysis.
R: Another powerful language for statistical analysis and data visualization.
5. Database Management
The ability to query databases using SQL is essential for extracting data.
Knowledge of database systems like MySQL, PostgreSQL, Oracle, or MS SQL.
6. Creating Dashboards and Reports
Data analysts need to be able to create dashboards and reports that communicate insights to stakeholders. This includes using tools like Tableau, Power BI, and Microsoft Word to create interactive dashboards and reports.
7. Data Visualization
Using tools and libraries like Tableau, Power BI, Matplotlib, Seaborn, or ggplot2 to represent data in a visual format that's easy to understand.
8. Machine Learning
Machine learning is a growing field that is becoming increasingly important for data analysts. Data analysts who are proficient in machine learning can use it to automate tasks, identify patterns, and make predictions.
9. Excel
Often overlooked, but it's still widely used for data analysis and visualization, especially in smaller datasets or in business settings.
10. Critical Thinking
The ability to approach problems logically and make informed decisions based on the data.
11. Attention to Detail
Ensuring accuracy in data analysis and recognizing anomalies or errors in data.
12. Communication
Clearly conveying findings, both written and orally, to non-technical stakeholders. This includes creating reports and presentations that gives the insights from the data.
13. Problem-Solving
Coming up with solutions to business problems using data-driven approaches.
14. Teamwork
Collaborating with other departments or teams, understanding their needs, and providing them with relevant data insights.
15. Ethical Judgement
Recognizing the ethical implications of data usage, storage, and analysis, especially in terms of privacy and security.
r,data ethics,python,sql,data modelling,database management,excel,data cleaning,tableau,business intelligence,cloud computing,power bi,data wrangling,spss,machine learning,big data technologies,data warehousing,critical thinking,data cleaning and preparation,data mining,data storytelling,data management,communication,attention to detail,problem-solving,programming,data quality,statistical analysis,creating dashboards and reports,sas,data governance,ethical judgement,data visualization,data analysis and exploration,data architecture,teamwork,statistics
Employment Type
Full Time
Company Industry
Key Skills
- Data Analytics
- Microsoft Access
- SQL
- Power BI
- R
- Data Visualization
- Tableau
- Data Management
- Data Mining
- SAS
- Data Analysis Skills
- Analytics
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