Data scientists mainly find out hidden patterns and useful insights from the data. They mainly analyze the raw data and handle them very well. In order to extract useful insights, they use various statistical procedures. Both structured and unstructured information are handled very well by skilled data scientists.
Data scientists need big data pipelines and models to work upon. Data engineers are the ones who will help data scientists to build data pipelines and models. Managing, maintaining, and testing data models are also done by a data engineer.Essential requirements for a data engineer 1. Knowledge of database models 2. Knowledge of ETL
They will organize and manage both macro and microdata. The blueprints of a company’s data platform are implemented by a data architect.Tools used by a data architect XML SQL Hive Spark Pig
Data science projects are handled and managed by a data science manager. They are responsible for executing all of their plans and submitting the outcome before the deadline. In order to guide the teammates, a data science manager should have good communication skills and very good leadership qualities.
In order to extract meaningful information from the large amount of data that is given, the Ml engineers will write programs and develop Algorithms. They should be very familiar with machine learning algorithms.
With the help of artificial intelligence and machine learning, a decision scientist helps the company to make appropriate business decisions.
They will identify various trends in the market using a statistical model. Tools used by a statistician R, python, SQL SAS ,SPSS Matlab Statsa
They are the people who collect as well as interpret data to solve a particular problem.