A career in Data Analytics has become one of the most desirable amongst the graduates. The demand is greater than the availability of trained professionals which makes this field less competition and higher pay among the other tech fields.

 

Data Analysis is analyzing data, identifying patterns, and generating useful insights. The Data Analysts further use their Data Analyst skills and visualization techniques to transform data into a readable format.

often data analysts spend their time analyzing the data and generating useful insights but their role also includes some part of Visualization and presenting data in a readable manner.

Top 20 skill a data analyst must know

 

 

 

Let’s Explore the Top 20 Skills a Data Analyst Must know:

1. Data Cleaning

Raw data extracted from databases may contain irrelevant information. Data Cleaning is the process through which data analysts prepare data for the analysis. 

2. Statistics

Knowledge of statistics aids logical thinking and identifying patterns, which is critical for analyzing data to generate useful insights.

 3. Programming

Programming knowledge is essential for extracting and manipulating data from databases, automation of tasks, and analyzing data to generate insights.

4. Database management

Ensuring proper collection, storage, and extraction of the right data as and when required is a must-have skill for a data analyst it includes knowledge of SQL and NoSQL.

5. Exploration 

Data exploration skills are a must-have skill for data analysts, a data analyst extracts analyzes, and explores the data to find correlations between different attributes to generate insights.

6. Interactive Dashboards 

Millions of petabytes of data enter databases every day and it is impossible for a human to process it and extract any useful information from it, Interactive Dashboards make it easy to understand the data.

7. Excel

This is one of the most famous and widely used Data analysis tools. Its ability to process huge data using formulas and functions makes it popular and easy to use.

8. Python

As a famous general-purpose programming language, Python should be the priority among the data analyst skills to master first before becoming a data analyst.

9. Machine learning

Machine learning techniques help Data Analyst Course make accurate predictions based on the patterns identified from the data and make data-driven decisions.

10. Data visualization

Data visualization is presenting complex data in a more easy-to-understand manner through visuals.

11. Critical thinking

Critical thinking is one of the most important soft skills that a Data Analyst should have, critical thinking is very important to ask the right questions and analysis of various attributes in a database.

12. Teamwork

Extracting large organizational data and generating useful insights based on that is not an easy task and it often requires different perspectives and checks for accuracy. Teamwork is a skill that enables you to collaborate with others and perform your tasks.

13. Problem-solving

Solving real-time problems is critical for a Data scientist, the ability to identify the real problem and put in place the right solution is very important for a data analyst. 

14. Data modeling 

Data models are the Diagrams of software and data elements that represent data flow. It can use symbols and text.

 

15. Query language 

Doing the right query is very important for data analysts to extract useful data that can help analyze. SQL is one of the most used query language used by data analysts across the globe.

16. SQL and NoSQL

It is the most famous query language across the globe. every organization dealing with data uses SQL. SQL is used for a structured database and NoSQL for a non structured database is used.

17. Communication

Communicating vital information extracted from the data is an integral part of the data analysis process, Having good communication skills helps data analysts to do it.

18. Domain Knowledge

Having good knowledge of the domain of your organization is always a plus. It enables you to understand better and draw correlations between the different attributes.

19. Research

Thorough research keeps a data analyst updated with the latest trends in the market. An analyst should always consider the latest trends in the market before making any reports.

20. Functions and Formulas

A data analyst should have a strong command over formulas and functions, they are vital for any calculations and analysis of data through analysis tools like Excel.

 

Learn more

If the Data Analyst profile interests you, please check out the Data Analytics Course facilitated by Henry Harvin Education, the largest E-learning Platform, with 1200+ courses across 37 categories.

 

Since 2013, it has had more than 600+ employees and offices in 13+ cities across the globe. It has the vision  To reshape the growth of its students globally by delivering excellent training & services through benchmarked content and resources.

 

Conclusion

A professional who extracts and generates useful insights from data using data analyst skills and techniques is a Data Analyst. In this ever-expanding world of technology, it has become difficult to learn all at once. I would rather recommend learning in a structured way. 

Also, Read

Most Asked Questions

Q. 1 What is Data modeling?

Ans. It is a simplified Diagram of software and data elements representing data flow. It can use symbols and text.

Q. 2 Who is a Data Analyst?

Ans. A professional who extracts and generates useful insights from data using skills and techniques is a Data Analyst.

Q. 3 What is data cleaning?

Ans. Raw data extracted from databases may contain irrelevant information. Data Cleaning is how data analysts prepare data for analysis. 

Q. 4 What is Data Analysis?

Ans. Data Analysis is extracting and analyzing raw data to identify patterns between attributes and generate useful insights.

Q. 5 What are SQL and NoSQL?

Ans. It is the most famous query language across the globe. every organization dealing with data uses SQL. SQL is used for a structured database and NoSQL for a nonstructured database is used.

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