The Difference Between a Data Analyst and a Data Scientist

Introduction

With so much analytics done these days, it is easy for a data analyst to be confused as a data scientist or vice versa. Although some businesses want their data analysts to handle everything themselves, there are apparent differences between the two roles. 

A critical point to note is that a data analyst can not perform all the functions of a data scientist. Still, a data scientist might be able to do everything or somewhat is expected to do everything a data analyst does. Another critical point is that you will grow from a data analyst role to a data scientist in data-centric careers and never the other way round. Let’s have a look at each of the roles and then look at their fundamental differences. While you go through these, please remember that the actual ground realities might shift depending on the way businesses see each of these roles.

Who is a Data Scientist?

A role of a data scientist involves designing data, statistical and mathematical models around business problems using available data from the business ecosystem. A data scientist is someone who is an exponent of scientific methods designed to work with data systems. This includes statistics, mathematics, theoretical computer science, programming, database management, and big data. The data scientists can put every theory in statistics and mathematics into practice using the large data sets they have at their disposal. 

Who is a Data Analyst?

A data analyst role is a smaller subset of a data scientist with some more responsibilities added, if you will. A data analyst is someone you would expect to know how data is stored in data warehouses, SQL databases, NoSQL databases, big data, and any other popular form of data storage. 

The analyst is also expected to know the most efficient ways to extract data from these data storage systems using any convenient database-friendly language. In most cases, it is SQL. Beyond these capabilities, a data analyst is expected to know about data mining, data munging, and data cleansing. These tasks require a data analyst to work with popular data visualization tools in the market.

Key differences between Data Scientist and Data Analyst

As you can make out, there are some significant similarities between the two roles, but we shall focus on their differences.

Data Analyst Skills	Data Scientist Skills
A data analyst is expected to be adept at statistical and mathematical practices.	A data scientist is expected to be an expert at statistics, mathematics, theoretical computer science, data modelling, programming, and big data.
A data analyst may use tools that are more like data marts or small and relevant subsets of the entire data. Tools like Excel, Tableau, Power BI are popular with data analysts.	A data scientist uses tools that can work with massive data sets, usually staged on big data systems. These are generally already mined and cleaned for data modelling and application of Machine Learning and Deep Learning algorithms.
Scripting, SQL, and Python are some of the more advanced tools that a data analyst is expected to know and work with.	A data scientist might be asked to pick up skills in programming in any of the languages among Python, R, Ruby, Pig, Scala, Java, SQL, NoSQL, MATLAB, etc.
Data analysts typically deal with the shorter horizon of intelligence, dealing with immediate or tactical results.	Data scientists usually are employed to build long-term and sustainable plans around available data. The pans are more strategic in nature.

Conclusion

As you might have already made out, a data scientist is a more niche role involving deep knowledge and expertise in the science behind data. Data scientists are involved in designing and modelling new or even business models, usually resulting in long-term projects. Data analyst is a role which is more to do with handling and shaping data into reports and visualizations, presenting short day-to-day or week to week stories centred around these reports and visuals.

If you are looking at ways to become a data scientist or a data analyst, you can choose the data science and analytics course available online at Great Learning. You can even opt for programs that lead to industry-recognized data science certificates online.

References

https://www.mastersindatascience.org/careers/data-analyst-vs-data-scientist/