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Have you ever wondered how Self-driving cars work, or what the science behind Siri and Google assistant is? Have you ever heard of Speech and Image Recognition and wanted to know more? These are all elements of Data Science!
In this three minute article, I will provide a brief overview of what Data Science is and the job opportunities that come with it. Words like Data Science, Artificial Intelligence, Big Data and Deep Learning are becoming increasingly more common in the world of technology, so let’s dive in and understand what data science is all about.
What’s Data?
Data is a collection of facts such as numbers, words, measurements, observations, or descriptions about something. It exists in structured and unstructured forms and can be measured, reported, visualized, and analyzed.
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What Exactly is Data Science?
Data Science is a blend of principles and practices from Mathematics, Statistics, and Artificial Intelligence that take data and turn it into meaningful information to solve problems. In other words, it is like a tree with many different branches.
Data Science is a broad term that encompasses numerous job roles. Each role is incredibly different and requires a different set of skills and knowledge.
There are numerous job opportunities within the field of Data Science. The term “Data Science” is often used to refer to a variety of different positions, each with its own distinct roles and responsibilities. Examples of some Data Science positions include Data Analysts, Data Engineers, Machine Learning Specialists, and Business Intelligence Analysts e.t.c.
ROLES IN DATA SCIENCE
The roles in the Data science field aren’t limited to the ones listed below
- Data Scientist: A data scientist is a professional responsible for collecting, organizing, analyzing, and interpreting large sets of data. They use their expertise to uncover patterns and correlations in data that could lead to insights that could help a company develop better products, processes, and services.
Image : Huawei
- Data Analyst: A data analyst is a professional responsible for taking data sets, mining them for meaningful patterns, and making actionable recommendations. They must have a strong understanding of computer programming, data mining, and analytics.
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3. Machine Learning Engineer: A machine learning engineer is a professional that designs and implements algorithms that allow computers to improve their performance. They must have a strong understanding of mathematics, statistics, artificial intelligence, and computer science.
Image : AltexSoft
4. Business Intelligence Analyst: A business intelligence analyst is a professional responsible for analyzing business data to create actionable insights. They must have a strong understanding of data analytics and be able to identify areas of improvement in a company’s operations.
Image: TechTarget
- Data Visualizer: A data visualizer is a professional that uses data sets to create visual representations of the data. They must have a strong understanding of data visualization techniques, as well as the ability to interpret the visuals.
Image: Venngage
- Data Architect: A data architect is a professional responsible for designing and implementing an organization's data architecture. They must have a strong understanding of data architecture principles and be able to create a data model that is adaptable and scalable.
Image: Freelancermap
Data Science is an exciting and ever-evolving field that is revolutionizing the way we interact with data. By leveraging the power of analytics and machine learning, Data Scientists are discovering insights that are transforming our world. As the amount of data continues to increase, the importance of Data Science will only become more pronounced. The future of data-driven decision making is now, so don’t be left behind — start taking advantage of the power of data science today!
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