Data Scientist Vs Data Analyst

BySachin Pandey

Both data analysts and data scientists are very important assets of an organization. They help an organization in analyzing their data and developing business strategies on the basis of facts and rather than on the basis of intuition and gut feeling. However, most people believe that the role and responsibilities of a data analyst and data scientist are the same. But that’s not true. The roles and responsibilities of a data scientist and data analyst are very different from each other and require different skills and knowledge. So, today we are going to learn what is the main difference between a data scientist and a data analyst.

What Does a Data Analyst Do?

The main responsibility of a data analyst is to evaluate data sets to obtain insights and draw conclusions. The job of a data analyst revolves around collecting large volumes of data from different sources, organizing it, and analyzing it for identifying hidden insight/trends in it. Once the analysis is done their next responsibility is to summarize their findings and present them to top management with the help of charts and graphs. In simple terms, the job of a data analyst is to discover insights/patterns and present those insights/patterns in such a way that anyone can understand them. Following are some of the most important responsibilities of a data analyst:

  1. Collect large volumes of data and interpret it.

  2. Discover hidden trends from large volumes of data.

  3. Manipulate and analyze data with the help of SQL. 

  4. Perform predictive analytics, prescriptive analytics, descriptive analytics, etc.

  5. Present insights with the help of visualization software like IBM Cognos Analytics, Power BI, Excel, Tableau, etc. To learn more about these visualization tools, feel free to join Data Analytics Online Training in Bahrain.

Core Skills of a Good Data Analyst

A good data analyst must be proficient in data mining, data modeling, and data warehousing. Besides this, he must have strong data analysis, statistical analysis, and data visualization skills. Additionally, a good data scientist must be:

  1. Expert in Manipulating and analyzing data.

  2. Proficient in using Microsoft Excel and Microsoft SQL Server.

  3. Expert in various tools and software like SAS, Tableau, etc.

  4. Proficient in solving complex business problems.

What Does a Data Scientist Do?

Data scientists use various techniques like mathematical techniques and machine learning techniques for the purpose of cleaning, processing, analyzing, and interpreting data to discover insights from it. Additionally, they develop various data modeling processes for an organization with the help of algorithms, predictive models, prototypes, etc. Here are some of the major responsibilities of a data scientist:

  1. Cleaning, processing, analyzing, and validating the data.

  2. Conduct data analysis on large volumes of data.

  3. Perform data mining.

  4. Conduct statistical analysis with the help of machine learning algorithms

  5. Develop useful machine learning libraries and develop automation codes.

  6. Obtain insights with the help of machine learning tools and algorithms.

  7. Identify new data trends and forecast future trends.

Core Skills of a Good Data Scientist

A good data scientist must be an expert in Mathematics and Statistics. Besides this, he must have knowledge about various programming languages, predictive modeling, and machine learning algorithms. Additionally, a good data scientist must be:

  1. Proficient in probability and statistics

  2. Expert in multivariate calculus and linear algebra.

  3. Proficient in database management and data wrangling.

  4. Expert in popular programming languages like R, Python, Java, Scala, etc.

  5. Proficient in using Apache Spark and Hadoop.

What Is the Main Difference Between a Data Scientist and Data Analyst?

Following are the main difference between a data scientist and a data analyst:

  1. A data scientist must have a mathematical mindset whereas a data analyst must have a statistical and analytical mindset.

  2. A good data scientist must have knowledge about machine learning and various mathematical techniques. While a good data analyst must have good knowledge about statistics, predictive analytics, prescriptive analytics, descriptive analytics, etc. To learn more about these analytics techniques enroll yourself in the Data Analytics Online Training in Kuwait.

  3. In terms of the job, getting a job as a data scientist is not easy. To get a job as a data scientist you must have knowledge about various mathematical and machine learning techniques, multivariate calculus, etc. While it is very easy to get a job as a data analyst even if you have limited skills.

Conclusion

The job of a data scientist and data analyst is not easy. Both data scientists and data analysts help an organization in analyzing their data and finding useful patterns and trends from it. But the role and responsibilities of a data scientist and data analyst are not the same. So, make sure you don’t get confused and believe that there is no difference between a data scientist and a data analyst.