08 Dec 2022
Debunking Common Myths Of Data Science
Ekeeda Moderator
Works at Ekeeda
The data science field has gained immense popularity in the last couple of years and now companies heavily rely on data-driven decisions that are foolproof and concrete. Data Science has incredible power and it has helped companies to crack massive data volumes and gain valuable business insights. It’s like the harmonious union of technology, mathematics, and business that will make customers’ lives easier and more efficient. People feel the transition in data science is complex, and you'll have to study rocket science level of math, statistics, or programming to make a mark in the data science field. But that’s not the case. One such thing that hovers around in the market, you should learn to combat the myths about data science you will hear from others in the industry.
Data science is a field of study that deals with voluminous data and the use of cutting-edge tools & procedures to real hidden patterns, generate useful data, and make efficient business decisions. It's the most potent thing on the earth that will help business changes their perceptions and attain new zeniths in their lifecycles. Before companies hire skilled data scientists it will be a fact check whether the person is clear with the fundamentals or not. This field has helped various companies generate meaningful insights on massive volumes of data. Many thoughts & perceptions of data science also circulate along with popularity but some of these are not factual.
But, along with the growth, there have been a lot of myths surrounding the data science field. For this very fact, Ekeeda has brought together a panel of Data Science experts to debunk the common myths to help companies and data science professionals gain clear visibility and a focused approach.
Watch Video:
Sources: Krish Naik, Co-Founder, iNeuron
Let’s start debunking common myths about Data Science one by one:
People are frightened that data science is rocket science. It’s meant only Ph.D. holders or mathematics genius. However, it’s a myth. The truth is anybody can dwell in the field with industry-oriented training or learning. You will need a fair understanding of statistics and probability since most of the predictive modelling techniques will be based on these concepts. Also, with the availability of sophisticated tools & software, Data Scientists won’t have to use complex formulae and equations. You will need to figure out the interpretation of these techniques of when & how to use them, rather than the mechanics of the application. There are a lot of data science courses online that will teach you basic to advanced data science concepts. Ekeeda is the place where you will find an industry-focused curriculum and learn with industry experts. 1:1 mentorship will help you clear all your doubts and capstones will give a sneak peek into the professional world. So, by now you may have understood that data science is not about Ph.D. holders or maths wizards. Logical ability, common sense, and good practice for analysis are all it takes to secure jobs under the data science spectrum.
Just tools will help us crack data science interviews. NO! For instance, if you learn SAS, then you’re a SAS programmer and not a data scientist. A data scientist will think out of the box to get solutions not merely with the help of tools. They should go beyond using tools to derive solutions, instead, they will need to master important skills like the application of various predictive modelling techniques. We don’t say that learning tool will help, but it is the only thing that will make you good data scientist. Although, learning tools will create make your job easier in the data analytics world companies will look for skilled data professionals who have mastered the combination of mathematical, programming, and business skills. To focus only on a particular tool is good, but it’s better to pick a data science course that will help you acquire the required skills with the right exposure and real-world examples.
AI Will Take Over Data Science
Yeah! AI is the talk of the town and it's great. But there is a likely chance that machines will do some form of data science activities. And, if you think that it will completely replace the kind of data scientist work, the answer would be ‘NO’. Although machines and automation are reducing our work, data scientists are must professionals who will sort, feed data, and interpret it to develop commands and other working principles. Data science is going through ground-breaking technologies and the industry is building sophisticated algorithms to automate it. But we still require people with strong analytical and judgment skills, with domain expertise who will give the right command to the machine to do it.
Read more: Why Is Data Science A Good Career Option
Many mediums to small-size businesses are now openly embracing the skills of data scientists, especially when they have piles of unwrapped data. Similarly, data scientists also think that they work if there is a voluminous amount of data that won’t fit in a basic excel sheet. But it is not as such. It is indeed true that data in bulk will be the goal, but you don’t have voluminous data to derive meaningful and valuable data insights. They say four important ‘V’s are implied by IBM – Volume, Velocity, Variety, and Veracity. So, if it’s possible to structure data in any of the ‘V’s, then you can imply Data Science.
Many individuals think that data scientist primary skill is to understand programming languages and know how to develop efficient code. In fact, it’s an assumption a good coder is a good data scientist. Most men and women are turning to the data science industry and it’s like a resurgence of the tech industry. But again, as we said earlier, focusing on one skill won’t help you swim across the troubled waters. Because not all data scientists are going to code in Java or Python, the relevant skills related to predictive modelling, data mining, or data visualization will also count in the overall efficiency. The data science roles will change from company to company, business to business, and learning new findings in the field.
Data Science & BI Is ONE
A common myth prevailing, especially amongst those who are unfamiliar with the industry is that Data Science and Business Intelligence are the same. We need to understand that they are not identical. Although business intelligence involves working on big data sets but it’s more about operational and context to an organization such as you will learn more about the company’s customers and audience. On the other hand, Data scientists will do more perspective and predictive analytics, and their end goal will be to collect proper information to build distinct patterns and valuable insights. So don’t get confused between the two. Data Science is more towards data mining and statistical or quantitative analysis that helps find trends & patterns. Data Science is more into data mining, data processing, deriving patterns, and visualization, and it's different from business intelligence.
Experts predict a 10% increase in data accessibility will help acquire $50 million in additional revenue for Fortune 500 companies. When you apply data science to the collective data with the right strategy from the marketing channels, one can easily derive the best sources for increased profits and revenue. You will have to decide the one that you need to invest in so that you reap benefits. The insights derived from the potential data by skilled data professionals may not directly, but surely obtain monetary gain for the company.
Data Science is one of the most crucial elements to lay out your business strategies and make a remarkable change to business practices. Today, data science is regarded as a top-ranking profession in any analytics company. The demand for data scientists is already skyrocketing, and the aspirants have to make the right career move by equipping themselves with in-demand data science skills. In fact, Glassdoor ranked Data Scientists as one of the top 10 jobs in the industry for 2022-23.
Companies and aspiring data scientists need to learn data science, the trends, and patterns & understand how it helps the business or rather gives value to it. You should strive to get clarity about the myths floating in the industry. If you’re an aspiring professional who look for a data science career, then here’s an opportunity for you.
Ekeeda is one of the leading edtech platforms and leading professional training providers in Data Science. They train aspiring candidates with a data-driven approach to work on BIG but highly complex data and apply valuable insights towards the benefit of companies and processes. Those candidates who join the Ekeeda Data Science course will get hands-on training that will prepare them to visualize and analyze the extensive data sets and interpret them. You will gain the required skills to work at big companies and leverage vast amounts of data to gain meaningful insights and make critical data-driven decisions. Equip yourself with the right knowledge and skills without sacrificing your passion to learn new things for a rocketing data science career!
Now is the time to broaden your knowledge horizons with the Ekeeda data science course and see your career take a leap ahead.
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