Through data analytics, companies are able to understand and improve their business and processes.
This helps them to reduce their expenses and save more of their precious time. But before we delve deeper into data analytics, it is important that we know the significance of data analyst vs data scientist.
As a business owner, this will help you determine which profession you need for your business.
As you can see, data analytics is now playing a very significant role in today’s business world. Because organizations have the capacity to collect various types of data as they go on their operations, it has become one of their competitive edge in the marketplace.
Data analyst vs data scientist – a quick overview
Data-driven skills like machine learning, analytics, and artificial intelligence are becoming on demand these days. Industries become more and more reliant on data in terms of research, the economy, as well as in different aspects of businesses. Thus, data analyst and data scientist are two job roles that will continuously be a prominent career track among other IT professions.
What does a data analyst do?
A data analyst analyses volumes of data sets and extracts valuable insights to help businesses with their growth and development. Data analysts perform statistical analyses from collected sets of information to provide organizations with answers to certain questions and help them solve problems.
Data analysts are also able to determine trends and guide business leaders to make informed decisions.
What does a data scientist do?
A data scientist is more focused on designing and developing data modelling processes. With tools and methods that typically consist of algorithms and predictive models. This will help companies to draw out accurate results in terms of big data and help them solve complicated problems.
Data analyst vs data scientist: Main role differences
Both data analysts and data scientists require a bachelor’s degree in fields such as mathematics, statistics, or computer science to qualify for the job. In terms of job roles, although both professions deal with data and statistics, they are quite different from each other:
Roles of data analysts
- Perform different types of data analysis such as predictive, prescriptive, diagnostic, and descriptive analytics.
- Making use of SQL for data querying.
- Data analysis and forecasting through Microsoft Excel.
- Making reports, visuals, and dashboards through a business intelligence software.
Roles of data scientist
- Data scrubbing and cleaning by using programming languages like Python or R.
- Data mining.
- Statistical analysis via machine learning algorithms.
- Develop big data infrastructure.
- Creating automation and programming techniques that will simplify daily processes.
What we have discussed above are general roles and responsibilities that these two professions typically work on. However, their job will also depend on the type of requirements every company needs, as well as their kind of industry.
