Data Science is one of the fastest-growing fields nowadays. It is gaining attention from everyone. Whether you are a techie or non-techie there is a significant role played by data science in your day-to-day life, and maybe you are not aware of it. This really pushed the growth of data science to a different from other trending technology. And, of course, this will the reason behind everyone wants to learn more and more about Data Science popularity of Data Science. This really gives Data Science a kind of celebrity status among all trending technology.
Now, if someone asks you what is Data Science? Based on your working area you may have a different answer. If You are a non-techie who doesn’t hear this word you maybe skip the conversation at that moment only and will start speaking about how pleasant whether we have today. But if you know this term and got your head hurt by some time from this trending tech’s 11 letters long name then you may simply tell that Data Science is the field of computer science which deals with data. So is that enough? Maybe it is.
But, If you are Data Scientist then you should explain it in a more specific way. Like dealing with data can be done using different kinds of files also. What makes it different from normal data handling procedures?
Here is the answer-
Data Science is a mixture of various algorithms, tools, principles of statics, and machine learning which help us to deal with data by getting useful and meaningful insights and knowledge from it.
These insights and knowledge can be used for a large range of applications and problems to make business decisions. Ah, That was such a good definition, isn’t it? But, how this makes it different from normal statics? Because statics also deals with data and provides insights from it.
How Data Science is Different form Normal Statistics?
This can be answered with a very simple analogy. And that analogy is the difference between explaining and predicting. Maybe you got it. Let’s try to understand together.
Consider your company has a dataset of petrol price during last 5 years. And your boss wants to make the best use of this data so it gives some best results to save money for each office employee. Oh, that really looks like an amazing project. So your boss gives this task to you because you are the best who can deal with data like a pro. Come on, you have to save thousands of rupees now. Let’s do it.
Now if we think it is a statistical manner, you may calculate mean, median, mode, variance, maximum, minimum values, etc. to get some useful results that can really save your colleagues money. Don’t forget it will save you money also. But those values can just explain the data. You may get that the average price of petrol was around 72 rupees, the maximum was 94 rupees. But how it can save your colleague’s money? No, it can’t you can’t save their money by just explaining the dataset feature. You need to do something different. So, that means your statistical analysis which gives you a detailed explanation about data failed to fulfill your requirements.
Time to move ahead because you have to save money. So, we will try to solve this in a data science manner. So you have data and if you want to find insights and explanations about that you can get it in the same way like you did for a statistical manner because data science can use statistical principles to explain data before carried out further operations on it. That may be considered as Exploratory Data Analysis. I can bet if you have even beginners level experience with data science you already know this term.
After EDA you are fully familiar with the dataset and its feature, now data science will make the whole game different from normal statistics. Data science can use advanced machine learning algorithms which can be accessed from including various libraries. These ML algorithms can be used to train your data to train a model which can make predictions of petrol price for next one month BOOM! You can verify your model with testing before applying it to the real world. So with few lines of code and intelligence of ML algorithms and your supervisor and smart work all together invented a model which can predict the price of petrol for future. Congratulations! you did such a good job.
Show your project to your boss (I can bet he will be happy with your work) Give access to your final product to all your colleagues and all will appreciate your work because you are saving their money with this amazing project.
Hope this little imaginary project helps you to understand the difference between statics and data science. Always remember, statics is all about explaining the data, and data science is all about explaining and then predicting or making use of ML algorithms.
Keep learning and eating data to increase your knowledge!