Data science is a broad field that includes data analysis, predictive analytics, data mining, machine intelligence and deep learning; amongst many other sub-units. Data is quickly becoming a huge resource for governments and companies, and as such; data scientists are needed to apply statistical methods to interpret this data. Numerous companies require a team of data scientists to leverage this data within their organization to gain a competitive advantage.
Becoming a data scientist requires one to have a solid foundation in math, and having a knowledge and understanding of basic quantitative and qualitative mathematical principles.
One is also advised to have a good grasp of programs such as Python, R and SQL which would assist you as a data scientist in data analysis and ones such as Tableau and Power BI which would assist in organizing and visualizing the data.
You are not limited in having a formal education to learn the above, as you can attend a bootcamp online or be self-taught. This opens up the career to many wishing to pursue data science and who may not have a university degree due to one reason or other. It also enables people in other careers such as economics or finance to switch over or to build on to their existing skills using data science.
Therefore what you need to build a successful career in data science is patience, drive and a willingess to learn. The learning curve for this particular path is not linear either, as there are ups and downs which would require you to keep practicing until you have grasped all the concepts enabling you to receive raw data and be able to fully analyze, process it and visualize it into information that can be clearly understood.
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