What data analysts do with the data is one of the key distinctions between data analysts and scientists.
Data analysts
Data analysts typically use tools like SQL, R or Python programming languages, data visualization software, and statistical analysis to work with structured data to address real-world business issues. Typical tasks for a data analyst could be:
- identifying information needs in collaboration with organizational leaders
- using primary and secondary sources to gather information
- Rearranging and cleaning up data for analysis
- Analyzing data sets to spot trends and patterns that can be translated into actionable insights
- Easy-to-understand findings presentation to guide data-driven decisions
Obtaining a Data Analyst Course is vital for upskilling and staying current in the workplace.
Data scientists
When dealing with the unknown, data scientists frequently use more sophisticated data techniques to make future predictions. They might develop processes for predictive modeling that can handle both structured and unstructured data, or they might automate their own machine learning algorithms. This position is typically viewed as an improved version of a data analyst. Typical daily tasks might include:
- gathering, purifying, and processing unprocessed data
- developing machine learning algorithms and predictive models to mine large data sets
- Creating instruments and procedures to track and evaluate data accuracy
- creating dashboards, reports, and tools for data visualization
- Programming the collection and processing of data in an automated manner
