Over the past years big data has increasingly shaping our systems we interact with every day, from Siri, to google assistant, google, Facebook and so forth. This led to an increase in data-related jobs such as data scientist, analysts and engineers. Since these roles are very similar, it might be confusing. Therefore, we will talk about these three roles and the differences between them.
A data analyst is a scientist that delivers value to their companies by taking data in order to answer questions, and communicate the results to help better business decisions. Common task for a data analyst are data cleaning, performing analyses, and creating data visualisations.
In contrary to a data analyst, a data scientist is a specialist that applies their expertise in statistics in building machine learning models in order to make predictions and answer key business questions. A data scientist will have more depth and expertise in the skills of a data analyst and will be able to train and optimize the machine learning models.
A data engineer will build and optimize systems that allow the data scientist and analysist to perform their work. The engineer will ensure that any data is properly received, transformed and stored, and made accessible for the other data analyst and scientist. Basically, a data engineer is someone who retrieves the data.
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