At first glance, these two jobs seem similar because they both deal with data and analyze it. However a Data Scientist has more senior responsibilities than a Data Analyst. As a simple example, Data Analyst works with structured data with a more tangible goal, while Data Science solves intangibles with raw data that is not necessarily structured.
You can see the difference in definition and scope of work between Data Analyst and Data Science here.
Difference Definition of Data Science and Data Analyst
- Data Science
Data Scientist is a professional in analyzing, processing, designing data models and algorithms to be interpreted into company plans or actions. Data scientists often deal with unstructured raw data or even intangible business problems, so their work requires tools and methods from Statistics and machine learning to streamline data. Data scientists must be able to automate their own machine learning models and algorithms that can handle unstructured data.
- Data Analyst
Data Analyst is a professional who collects and interprets data, to solve specific problems through the process of data cleaning, transformation, and data modeling. Data Analysts typically work with structured data to solve tangible business problems using tools such as SQL, R or Python programming languages, data visualization software, and statistical analysis.
Differences in Scope of Work of Data Science and Data Analyst
- Collaborate with manager / leader to identify the information needed
- Take data from primary and secondary sources
- Data cleaning and rearrangement for the analysis process
- Analyze data sets to see trends and patterns that can be translated into insights or future company plans
- Present findings in an easy-to-understand way to inform data-driven decisions
- Collect, clean, and process raw data
- Design machine learning models and algorithms to extract big data sets
- Develop tools and processes to monitor and analyze data accuracy
- Create visualization tools data, dashboards, and reports
- Create programs to automate data collection and processing
- Present data findings into actionable insights to help companies make decisions
If you want to know the scope of work of a Data Scientist y More specifically, here’s an overview:
- Identifying data-analytics problems that offer the company the greatest opportunity in making decisions
- Determine correct data sets and variables
- Collect structured and unstructured data sets chunks from various sources
- Data cleaning and data validation to ensure accuracy, completeness , and data uniformity
- Design and implement models and algorithms to extract big data storage
- Analyze data to identify patterns and trends
- Interpret data to find solutions and opportunities
- Communicate findings to stakeholders with data visualization
Now that we know the difference between Data Scientist and Data Analyst we can conclude that Data Scientist is a more advanced job and requires more skillset than Data Analyst. Because of this complex expertise, many companies need a Data Scientist to provide actionable insights for the sustainability of their business.
Are you interested in becoming a Data Scientist?