People have different opinions about the job responsibilities and skill sets driving the data science field, which creates much confusion. The question remains, what distinguishes a data scientist from a data analyst?
Many people have the perception that a data scientist is just an exaggerated term for a data analyst. The fact that different companies define roles in different ways is a significant reason for this confusion. Actually, a title does not always reflect one’s job activities and responsibilities accurately. Moreover, data science is a relatively new field, and not everyone is familiar with the workings of the industry.
One can find plenty of data analyst job vacancies in Bangalore, Pune, Hyderabad, and many other cities.
Life of a Data Analyst
On a daily basis, a data analyst gathers data, organizes it, and uses it to reach insightful conclusions. Data analysts develop new processes and systems for the collection of data and compile their conclusions for business improvements.
Data Analyst Job Description
- Delivery of reports.
- Examining the patterns.
- Collaborate with Stakeholders: Data analyst roles and responsibilities include collaborating with different departments in the organization including marketers, and salespeople.
- Consolidating data: The most technical aspect of an analyst’s job is the collection of data. They develop routines to be automated and easily modified for the purpose of reusing it in other areas.
Life of a Data Scientist
A data scientist is someone who is an expert in statistics, Big Data, R programming, Python as well as SAS. And a career as a data scientist gives plenty of opportunities and high-paying salaries. Data scientists are basically problem solvers. They seek to determine the questions that need to be answered and then come up with alternate approaches to solve the problem.
Data Scientist Job Description
- Pull, merge and analyze data.
- Look for patterns/trends.
- Develop and test new algorithms using a wide variety of tools like Tableau, Python, Hive, Impala, PySpark, Excel, Hadoop, etc.
- Simplification of data problems and developing predictive models.
- Build data visualizations.
Data Scientist vs. Data Analyst – Skills Comparison
A data analyst deals with similar activities as that of a data scientist, but the leadership component is a tad different.
Generally, a data scientist is expected to formulate the questions for helping businesses and then look forward to solving them. On the other hand, a data analyst is given questions by the business team to look for a solution with that guidance.
Expectations from both the roles are to write queries, work with multiple teams to source the correct data, perform data munging, and derive insights from the data. Building statistical models or being hands-on in machine learning and advanced programming is not expected from a data analyst. Instead, they typically work on simpler SQLs or similar databases.
The data scientist job demands for strong data visualization skills and they must be able to convert data into a story for their business. Data analyst’s jobs usually do not require professionals to transform data and analyze it into a business scenario and roadmap.
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