What is Data Science?
Ever wondered how people are predicting Next Stocks to buy? Or how Netflix just knows what you like? Or even Google showing you the exact product you need? Or what's behind self-driving cars?
Yes, all with help of Data Science!!! Amazing isn't it?
How do we do Data Science Work?
Problem Statement
First, We need a problem that needs to be solved.
Like for example. Can I identify apples and oranges?
Data Mining
And if we are going to separate apples and oranges, what kind of data can we get or do we get? Images, their chemical configurations, etc.
Now that we know this (Let's go with Images, I don't know the chemical configurations and my boss wasn't giving me access to apple phones)
Data Cleaning
In real life what would you do if you had oranges and apples to separate?
- See if you really had oranges and apples to separate else it's just one thing you have and that is just stupid.
- If any of them is less in number then just take them out and you are done faster.
- If there is anything else with them?
These come involuntarily to us in real-time but hell computers don't know that so we check all these and more.
Data Exploration
Didn't it become easier when you could feel oranges and apples? But what happens when you get a bunch of numbers ( Like the pixel values of these images also I can't tell colours in RGB values), which makes no sense or maybe sense to some geniuses out there?
But for others. It would be so much easier to see things graphically or as we call it using various Visualization methods.
Feature Engineering
Now that I have this visualization I know I can separate using the colour and size didn't make much effect on how I should classify both of them.
Predictive Modeling
Now I see the colour orange and the rough texture I know it's orange, the red colour and smooth texture it is Apple.
Data Science Life Cycle
Data Science Application ranges in various Industries such as:
- Social Media Marketing
- Consumer goods
- Stock markets
- Industry
- Politics
- Logistic companies
- E-commerce
Let us discuss the application of data science:
The application can vary based on different sectors.
Internet:
Speech Recognition:
- When you googling something with your voice. How Google recognizes your voice and gives the exact thing that you want.
- It's all by data science. Data scientists will train the model that will recognize all the voices in the world and convert them to Google Search.
- Solved the business problem.
Target advertisement:
- Whenever you are searching for something on Amazon, that product will appear like an ad on your internet browser on the same day or the next day. How?
- It's all by data science. Your browser will store the data (cache). Based on your cache, the ad will appear on your browser or device.
Image Search:
- If you want to search the related images by the existing image you have, you get that easily by googling. Google also provides the services like this. How?
- It's all about data science. Data scientists build a model that will recognize the pixel pattern of your image and convert them to Google Search.
Virtual assistant:
- A virtual assistant helps customers, patients, and be friends with humans. The perfect example: Alexa, google assistant, and robots.
Who is Going to win in the Olympics?
- It can also be possible when you have a good amount of data. We can predict who will win in particular sports in the Olympics.
- Data scientists build a model that will predict the player depending upon sports.
Recommendation System:
- YouTube uses the recommendation system. It will help to recommend the new videos you may like, based on the history of your YouTube videos.
- Not only YouTube Spotify, Netflix, Facebook, and Instagram, all the social media are also using the recommendation system, which will help to get more users.
Chat Bot:
- A chatbot is also virtual assistance and it will help to clarify your questions based on a particular domain.
- ChatBot also comes under data science because it will recognize you and it will predict what you will ask in the future based on that it will retrieve the answers from the domain.
Fraud Detection:
Banking and financial institutions make use of data science and related algorithms to prevent and detect fraudulent transactions.
Why Data Science?
Data plays a major role in this world, by use of data, we can predict future, solve complex problems, build more customers, and more solutions. We have an enormous amount of data with us, but we don't have enormous data scientist to solve enormous data problems. To build a better future. In 2019 alone, Glassdoor named it the number one job in the United States. By 2026, the U.S. Bureau of Labor Statistics that there will be at least 11.5 million job vacancies related to data science.
- The Field of data science is growing high and all the company wants to solve business problems to earn a lot. The data scientist can solve problems easily and accurately!
- So, Company hires data scientists more to solve problems.
- And salary-wise, compare to some technical fields, the salary is high!
- The company that follows data science they likely to get more profit compare to non-follow data science companies.
Because of this phenomenon, data scientists are increasingly in demand, and a team of data scientists can make or break a company.
Different Types of roles available in Data Science:
1. Data Scientist
2. Data Analyst
3. Data Engineer
4. Data Architect
5. Data Storyteller
6. Machine Learning Scientist
7. Business Intelligence Developer
9. Technology Specialized Roles
9. Deep Learning Engineer
10. Business analyst
and more... Based on what you like, you can take the interested domain.
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Name: R.Aravindan
Company: Artificial Neurons.AI
Position: Content Writer