10 Facts About Data Science You Should Know Introduction The advancement of internet connectivity has increased the flow of data immensely. It has given rise to the need for data science professionals who can analyze vast amounts of data. Billions of devices are connected to the internet every second. Further, millions of terabytes of data are being generated every day. It culminates in almost 30 million terabytes of data in a single day. The field of data science attracts professionals from all areas, such as mathematicians, engineers, statisticians, and computer scientists. It is a multi-faceted approach for successful execution. There is hardly any branch of science that is not touched by the data analytics industry. 10 Interesting Facts About Data Science \tData science is considered one of the most sought-after fields in the market right now. A recent Harvard Business Review article praised data science as a field that covers several business insights. The demand for data science experts is increasing every day, with the United States leading the market and India following closely after. \tFully automated data science do not exist. In most cases, data is not clean and needs significant processing. Rogue data can be incomplete, duplicate, irrelevant, incorrect, or misspelled. The issue with data science is that there is no fixed model for this as all data is different and has varying problems. One needs to explore the data, test models, and validate the business sense, and there is no shortcut for this. \tMost of the data science-related problems do not require highly advanced analytical capabilities. Linear regression, K-means clustering, and logistic regressions are the simple models generally used for all well-formulated problems. Even complex models sometimes provide marginal gains compared to simple models. \tA common myth among people is that data scientists and data analysts are the same. However, the reality is that the work of these two professionals is wholly different. Data analysts analyze data and find trends, whereas data scientists try to find the cause of these trends and predict the future ones. \tData science mostly sounds like a field for technical professionals. It is a common belief that one needs to have a degree or be extremely intelligent to learn data science. However, with adequate training in data science, a person with average intelligence can also learn the nuances of the field and be a successful professional. \tData Science is another order of hypothesis testing. One needs to have the conviction to go for it before being proved right or wrong based on observations. It is also known as the Bayesian approach. However, establishing that the alternative hypothesis is incorrect is as essential as proving your hypothesis is correct. \tJust like in any other field, academics and business in data science are different. In academics, you can discover new methods and new theorems. However, in business, it is about solving the problem and making money. Not everyone is concerned about the analytics behind the solution. Data science certificate courses are excellent opportunities to gain academic knowledge and prepare for business-related aspects as well. \tPeople in data science should remember that presentation is critical. Selling an analytical solution is not that different from others. You need to explain your method in simple terms, and it should align with the end user’s interests. Using PowerPoint for storytelling is crucial. \tAnother surprising fact about data science professionals is that in most cases, data science professionals are paid a way higher salary than other tech professionals. In the future, this salary gap is expected to rise even further. \tAnd finally, it is estimated that by 2025 around 75 billion IoT (Internet of things) devices will be connected, which would be a three times increase since 2019. This only firmly justifies the hype around data science. Conclusion Not all the data generated online is essential. Dark data generally is a useless form of data, and it does not offer any meaningful insight. Data generated in call centers or on social media also does not have much use. These facts state the significance of data science in today and the near future. Considering that the importance will increase in the coming years, the data science field will remain lucrative for a long time. There are several universities offering data science certification courses to open the world of data science to professionals. The Certificate in Data Science and Analytics for Business - Shiv Nadar University (SNU) program is specially designed to guide data-driven intelligence. Enroll in the Certificate in Data Science and Analytics for Business - Shiv Nadar University (SNU) to expedite your career! Subscribe to our Jaro Education’s blog and stay updated with the latest information.