Data Science has been trending in the world of computer science for numerous years now. Numerous universities are running data science courses in 2022.
As the data that's being collected by colorful services and apps are added, the demand for data science and big data professionals is skyrocketing. Data science has surfaced as a great career path for software professionals and people who are obsessed with data.
Data Science comprises skills. You can't be a data scientist if you're just good at programming or have a good knowledge of Statistics.
The place where data science skills like Statistics, data mining, programming, and domain expertise match, data science happens.
It doesn't mean you need to be an expert at all these skills. Collaboration is the key. You might have good expertise in your domain and data mining, you can collaborate with a team member with great programming skills to set up an automated process to retrieve decision-making data for your business.
There are different kinds of data wisdom places —
Data Scientist — Data scientist knows nearly everything under the umbrella of data wisdom like data collection, processing, analysis, data presentation, and the birth of decision-making information.
Data Analyst — The term has come to a synonym for Data Scientist but there's a lot of difference between them. Data analysts analyze the data present in the data warehouse, produce queries, produce data visualizations, and communicate with the business side to produce reports to find insights.
Data Engineer — Data Engineers handle the most specialized part of the system. They design, make, and maintain the data channels. They design the system that gathers the data from colorful signals and stores it in the best possible way. It also involves data processing.
**Machine Learning Engineer — **ML Engineers use their statistical, programming skills, and ML algorithms to find perceptivity and predictions that aren't easy to find else.
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