Data's importance is known by everyone now. If it had been even 10 years back, nobody would have thought of this gigantic shift of power. The data is all around us just like any other gas. It's invisible but present. But actually there's no value to data as it is. Here's where data science and all its algorithms come in that actually give some value to it. Data Science is, after all, using data in creative and different ways so that it gets some business value. It actually makes data more of a product that is ready to be sold. The whole Data Science is based on utilizing data as an input and then processing the data with the help of complex data algorithms to get the necessary results. There are so many applications related to data science. Let us see what they are.
Applications of Data Science around us
One important application used is the recommender systems that are used in so many websites. Be it any E-commerce sites or any video sites like YouTube. Recommender systems use the input data and then generate the recommended results using the algorithms. Another example can be seen in your social media sites. The image recognition part where we can actually tag people is actually based on data science. It gives suggestions as to who the person is and even tells their name.
One of the biggest applications in the gaming industry. Big gaming giants are trying to take the gaming experience to the next level. They are using complex machine learning and data algorithms which continually improve the user experience. Motion gaming which is particularly still in its new stage uses these algorithms to learn about user's tracks to improve the levels or the UI.
The field of data science is actually very lucrative and is actually a mine of prospects. But there are still lots of challenges that have to be faced by data scientists around the world. One of the biggest challenges there is the fact that most of the companies are actually looking out for specialists rather than generalists. They want people to actually master the basics and then choose in on platforms, tools, and areas that you want to specialize in to get an edge over others. Another challenge is actually understanding the purpose of the process that is used by them in terms of business factors. Understanding what the client needs and also why he needs it is as important as the algorithms that are being used. This helps in gaining a different perspective to the work and leads to better understanding and in turn enhanced output. Also, a challenge that is regularly faced is to actually explain technical concepts to non-technical audiences. Getting the client to actually understand all the complications of the work is actually too much to ask. A data scientist has to communicate in such a way so that it makes both sides comfortable to an extent which is good for all.
In this information age, a lot of data about everyone and everything is generated. The companies are developing upon this big data to analyze the needs of the customer and deliver to them what they want. It is a mixture of algorithms, technology, and inference.
Job Prospects after the course:
Several courses are offered in this field. A person is eligible to pursue any career within this field. However, one can specifically choose the data science segment. It can be:
Data Analyst: The person who analyses the already collected data and derives useful insights that help the companies in further processing the data and streamlining it.
Data Architect: The one who builds the data. It generally includes the collection of data and put into the database for further analysis.
Data engineer: The one who looks at the data and thinks of ways in which it can be presented in an even better way. Developing on the mechanisms and new algorithms is what they are good at. The development of new languages in their work.
Statistician: A person who draws insights with the help of developed mathematical and statistical ways and predicts the situations that might occur.
Future of Data Science:
Data science is seen as the most revolutionary and futuristic field that is promising not only in the aspects of providing jobs to the youth but also in growth prospects in the field. The speed of growth in the field is really good. Websites like Glassdoor represent a true and fair view of the compensation that companies provide and the opportunities that a person can get.
With the advent of Artificial intelligence, the importance of big data analytics is going to grow as the machines would not be able to draw inferences and that is something that would stay with the humans to decide. Therefore, the field is considered to be a bright one.