Data Scientist, an IT Sector.

Greetings! I hope you all are doing well. So, this is going to be my first post in this community. And I joined #steemit because of @vvarishay who had guided me and not only me but also many others.

So now, let's get into what I am going to post right now. I am going to cover different sectors of IT to let you guys know what they are, and what do they do and stuff like this. So for this post, I have decided to tell you about Data Scientist.

INTRODUCTION
First of all, to know about a data scientist, you have to know about Data Science.

Now what is data science?
Data Science is obviously the study of data, it deals with how data is received, where do we get it from, what does it represent and how we can transform or convert it into valuable knowledge which is called information. As data is raw, it needs to be processed in order to use it, previously there were issues of storing large amounts of data but now due to such advancement in technology, they have been overcame and the real focus is now on processing it. Here's a picture showing different places where data is used:

What is the need for it?
Well, we all know that data is increasing every minute! So how can we handle this huge and enormous amounts of unprocessed data coming from many different sources? How can we separate the useful data from the useless one? We surely can't do it using normal tools and techniques, and that's the reason why we need data science, because it provides certain tools, techniques, skills which are sufficient for handling this data and processing it in such a useful way that it can be beneficial. A few examples can be:

• Weather forecast. With the help of data science, it has become easy to predict weather based on previous information and it is actually pretty precise.

• Product Recommendations or Suggestions. Ever wondered how we are recommended stuff? Different algorithms observe our history or search results and based on that, it fetches similar things from a massive pool of data and presents it to us.

• Effective decision making. You can take intelligent vehicles as an example here, with the help of different tools including Machine Learning, the systems are trained on data to act accordingly and efficiently.

DATA SCIENTIST
Up till now, you might have a good idea about what data science is, so let's jump into the position of a data scientist.
A data scientist collects data from many different sources, and then stores it, organizes it in a way that is easily understood. These guys then convert it into useful information which is used in making important and useful decisions for the company or a business. They use the data to make near future insights which can also let the company know about their net profit or net loss, many things similar to this. You might think that such individuals just only need to work on devices, well no. They also need to have good communication skills and not to forget leadership skills because they are required to communicate very frequently to their employer, to the client and also to their team. Here are just a few skills that will definitely help progress the business and also the individuals themselves.

WHAT IS THEIR DEMAND?
As I've mentioned earlier that the amount of data is just increasing without limit, there wasn't this much data before, but now it has increased to an amount that has made people realise it's importance. And yes, you guessed it right, the demand of these individuals is also increasing as they have the ability to handle and transform this ocean of data into something important that is useful for the company. They help the company solve many complex problems, and not only this, they also help find the best solution from the data which they just processed.

SKILLS THEY HAVE
Here's a small list of what the data science individuals are required to have, or must have to improve better in their domain:

• The first is definitely going to be the ability to collect data from relevant places.
• Then, to convert it into a useful and important form.
• To know a certain range of languages such as SQL, R, Python, etc. Also, some tools such as Microsoft Excel, Power-BI, Tableau which are used for data visualization and modelling. The knowledge of Amazon Web Services (AWS) is also an important requirement.
• Should know how to solve and tackle problems. And not to forget that, the individual should have a good way of conveying things and communicating with the team.
• The knowledge of statistics which is used for modelling data and mathematics go hand in hand while dealing with data.
• They are required to have a profound knowledge of analytical techniques and skills which includes different domains of Artificial Intelligence (AI) such as Machine Learning, Deep Learning, etc.
• They must keep a track of everything going on, and also have an eye on new incoming data which might be useful for the company.

Apart from all these skills, there are many more things which can be learned and improved to make yourself recognised as a data scientist. They are an important part of companies that deal with tons of data.

CONCLUSION
Finally, I would like to conclude that data science is an interesting domain and it will keep growing. Data scientists are also important members of any company as they provide the company with useful information and insights which will help them grow. They use their techniques and different skills to manipulate this data and play an effective role in the development of a business, and the demand for data science and data scientists will keep on increasing with time.