“What’s trending in the IT industry?”, “What’s a promising domain for me in IT?”, “How do I make a difference?” If you’ve had any one of these questions cross your mind, you’ve probably had ‘Data Science’ in the answers. Data Science is one such domain that’s created a new trend on how people look at data, well, Big Data to be specific. But why is that? Why is Data Science being heard of so often? Let’s find the answer to that as we keep exploring this blog. To give you a heads up, we’ll go through what Data Science is, what are its objectives, the state of Data Science in the industry, and how you can start by taking up courses in Data Science.

Let’s start with understanding what Data Science is.

What is Data Science?

Science is the study of something. In Data Science, that ‘something’ is data. What kind of data? For now, it’s limited to digital data either structured or unstructured. Data Science is a field whose sole purpose is to make meaning out of raw data. It achieves this by using various tools, technologies, algorithms, and frameworks, to identify and extract patterns that are hidden in raw data.

Almost everything is digitalized today. From ordering food, booking a travel service, social media, there’s an involvement of computers and networks everywhere. And wherever there are such systems, you can see data flooding. Think of the number of videos you’ve watched last week, activities on your social media accounts, visits to various online applications. The world is generating tons of data every second without realizing it.

Some of this data is of direct value to businesses. For example, your credit card number, email id, etc. This data is a meaningful form right from the point when it is generated. And it can be directly used whenever necessary.

But there is other data that is in raw form. For example, your product review, the kind of videos you watch on Youtube, the products that you look for on an e-commerce website. Although, this data contains information regarding your activity, your requirement, it can’t be directly used.

Let’s try to understand how Data Science deals with raw data with the help of an example.

How Does Data Science Help? – Facebook Use Case

Data Science has helped Facebook to really understand its users. Let’s look at a few examples of how Facebook uses Data Science.

Users generate a lot of text data on Facebook through posts and comments. Facebook uses Data Science to analyze and understand this data. One of the outcomes of this is that Facebook gives you the translation of native-language written posts in English.

If you’re a regular Facebook user and keep posting pictures, you might have seen how Facebook suggests you to tag people in your pictures. Facebook uses Data Science to analyze users’ pictures and understand their facial characters. It stores this information in a database. Whenever a picture is uploaded, it analyzes the picture to detect faces and identify the person in the picture. If the characteristics of a person in the picture match any entry in the database, then it suggests you tag that person.

Have you ever searched for a product on an e-commerce application and got an advertisement for the same product on Facebook? That happens with the help of Data Science. When you use an e-commerce application, your activity is recorded to show better suggestions. Facebook uses this data to show you advertisements for similar products.

Not everybody likes videos of all genres. You will have different interests. Facebook uses Data Science to display the videos of your interest on your wall. If you’re a technology enthusiast and usually watch only technical videos, Facebook records this activity. And based on this information, it suggests technical videos for you to watch.

We’ve explored only one application: Facebook, on a high level. But it is a great example to learn how Data Science is used in different ways.

Objectives of Data Science

You can use Data Science to solve various problems based on your requirements. But what are problems that Data Science mainly focusses on solving?

Better Use of Raw Data

Raw data is like a gold mine. A gold mine has layers and layers of soil and waste but what is underneath is worth a lot of money. That applies to raw data as well. But mining valuable data is not easy. Data Science changes this by providing tools, technologies, and algorithms to extract valuable data. So instead of all the raw data going to waste or stored away somewhere, Data science puts it at work and helps utilize it.

Understanding Your Users

It’s obvious that your business runs from your users. No users, no business. Every business wants to impress their customers by fulfilling their needs. I’m sure you’d want to hear positive feedback from your customers. And you’d obviously want your business to generate more revenue from your customers. To make this happen, you need to provide what your customers want or expect from you. But with a diverse set of audiences, it is difficult to understand who likes what. Data Science helps in solving this problem. You can monitor your users’ activity and analyze it to understand what they are expecting. This is the 1st ingredient to make your business successful.

For example, if you own an e-commerce application, you can monitor what category of products a user is interested in. Based on this, you can display suggestions and send an email when there’s a price drop. This would increase the chances of a user shopping from your application. By doing this, you’re focusing on giving the user what they were looking for. And that, in return, would increase your revenue. You can also use Data Science to optimize your product, add features, and provide user-specific services based on your understanding of the user.

Understanding Your Business

The 2nd ingredient to run a successful business is to bring change within. A lot of businesses run unoptimized. They know what end product they need, and they work on building it. But what they miss is understanding how to do it in an efficient way. Data Science can give you insights on how your business is running. By integrating Data Science with practices like Value Stream Management, you can understand what processes in your business add how much value to your product and eliminate waste.

Business Decisions and Predictions

The difference between a business and a money-making business is taking the right decisions at the right time. Be it prioritizing your tasks, choosing what features to add to a product, when to campaign, or what to invest your resources in. Each of your decision determines your success. Data Science can be used to analyze market trends and business needs to help you decide what decisions would help your business.

Using Artificial Intelligence algorithms on past and current data, you can get predictions for the decisions you’re planning to take. This is very helpful when you have different ideas and don’t have enough resources to go ahead with all the ideas. In such cases, you will be forced to pick one or a few ideas to implement. Predicting the outcome of each of these ideas would help you prioritize your action plans.


Data Science is all about finding hidden patterns in data. While you’re at it, there’s also a chance of innovation. With so much data at hand, you can find out something new for your business based on the feedback, the activity, etc.

One good example of this is the application of Data Science in the field of Medicine. Suppose you are using Data Science to find a new cure by looking at data and finding the patterns that might cure a disease. You might find another pattern that could end up being a cure for another medical condition.

Data Science is amazing!

Where Does Data Science Stand in the Industry?

Data is getting piled up day by day and so, the demand for Data Science professionals is rapidly increasing. Because businesses need to handle data properly and use it to their advantage, the need for Data Science is never-ending.

Information Science is ever evolving. There’s something new every day. And Data Science has been consistent in staying at the top of the list. Data Science has been in demand for many years now and the word is, it’s not going down anytime soon.

Although there’s so much demand and competition for Data Science jobs, the positions remain vacant. Recruiters say that people lack data science skills. And if you’re one of those people who’s looking to make a career in Data Science, you should consider taking up courses in Data Science.

How can Courses in Data Science help You?

Taking up courses in Data Science has two main benefits. One, you learn what’s the latest in the market, be it theoretical or practical. And two, you get a certification of value that will help you score a worthy job. But with so many courses in Data Science out there, which one should you choose? You have to make sure that the course teaches the latest industry trends, there’s hands-on training, assessments, projects, and a subject matter expert. These are the basic checkboxes that qualify a course as a good course.

If you’re looking for such courses, you should take a look at Springboard’s Data Science Career Program. It checks all the basic requirements a good course should have, and offers 1:1 mentoring, project-driven approach, career coaching and comes along with a job guarantee. Once you complete this course and get a job in Data Science, you would never look back. Good luck!

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