What is the difference between a data analyst and a data scientist?
While data analyst and data scientist roles attract similar types of creative and logical people, their roles do have stark differences. Here’s our breakdown of the lines between these often mixed up roles.
While these positions have different responsibilities, which we cover below, the people that fill them often have similarities that lead them to excel in these roles.
Data analysts and data scientists tend to be people with investigative minds, are very curious, and enjoy solving puzzles. They blend logic and creativity to look for pieces of data that fit together to tell a compelling story. Ultimately, they are storytellers through data.
The roles of data analysts and data scientists are often used interchangeably in conversation, but in practicality, they have very different responsibilities.
A data analyst’s primary role is to scan and analyze data, where a data scientist collects, cleans, and explains the data. An easy way to think of it is that an analyst is often more of a beginner-level role, and a data scientist may have more experience or more advanced education.
What Does A Data Analyst Do?
Data analysts do exactly what their title says – they analyze data sets to identify trends and draw conclusions.
Analysts provide explanations and reports and show visualizations to illustrate insights to decision-makers. Data analysts are proficient in SQL and business intelligence software. They use these software to interpret structured data and analyze trends and patterns.
However, data analysts do not need to have any extensive programming abilities. Their expertise is more in the realm of analytics and data management. For instance, they can generate marketing reports and future sales projections and show the success of ad campaigns.
To become a data analyst, you need to learn how to interpret trends from historical data, prepare summary reports, information management, data cleansing, data mining, and develop data pipelines.
What Does A Data Scientist Do?
A Data Scientist collects, cleans, and explains data. Their primary role is to adjust statistical and mathematical models and apply them to the data. Due to the higher reasoning and programming skills used to extrapolate findings from complex data sets, Data Scientists are often considered to be more senior than Data Analysts.
Data Scientists are responsible for translating formal business problems into workable data questions. They build predictive models for upcoming data and can theorize, implement, and acquire data effectively.
These professionals are often creative and must work to display their findings to tell a transparent, understandable, and compelling story.
In short, a Data Scientist interprets data in a similar way to a Data Analyst. But, Data Scientists also code models and algorithms to gain more insight into the data. Data Analysts act like “translators” while Data Scientists act in a hybrid capacity, helping companies turn data into practical and actionable information.
Breaking Into The Field
No matter which position you would like to pursue in Data Science, it is critical to learn the skills required for your target role to be a competitive candidate.
This can be achieved in several methods – including with university classes or self-teaching. But by far the most time-conscious and cost-effective way is to enroll in a technical training course.
These courses are completed in months, not years. They also just cost a fraction of traditional university tuition and provide practical, real-world applicable training.
Most importantly, short-term, intensive courses teach you up-to-date skills that won’t be obsolete when you graduate.
Related Reading: See the programming languages and skills Flatiron School will teach you.
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Disclaimer: The information in this blog is current as of September 28, 2022. Current policies, offerings, procedures, and programs may differ.