What is Data Science?

Data Science

Data Science is the field to extract, to mine the knowledge or to dig the information from the data across various platforms, which can be later used by the experts or the analysts to present some valuable information out of it. 

Now you must be thinking how to extract the information?

Well their are tools and techniques which are applied in the data sets to extract the information out of it.

But these tools and techniques are not easy as it sounds to be, one must gain an adequate knowledge, the process or the steps which are going behind the application to gain the information.

What are techniques?

Technique can be termed as the algorithms which are applied over the dataset to get the desired outcome.

Their are numerous algorithm(s) which can be applied over the dataset, but the real question is which algorithm should be applied when ?

Well the answer to this question is you must have enough knowledge to those algorithms.

Example - 

K-Nearest Neighbor (KNN)

• This algorithm is most commonly used algorithm in the classification problems.
•  It is one of the simplest algorithm in Machine Learning.
• The nearest neighbor algorithm is well suited for classification task where the relationship among the features and the target class are numerous, complicated or extremely difficult to understand.

For the time I won't be going much deep into the algorithm and will be covering up later.

What are tools?

Tools can be referred as the software which are directly used instead of implementing or the use of the algorithm but in the backend we are still using the algorithm.

Its basically a Graphical User Interface(GUI) based software where one just has to drag and drop the parameters or the functions that are going to be used in the dataset, and again you must acquire the knowledge to use the functions.

Some of the tools used I have used are - 

• MS Excel
• Tableau Prep
• Tableau 
• RStudio
• Rapid Miner Studio

What is the role of a Data Scientist?

• A data scientist be able to acquire the data from the various sources across various platforms.
• Must be able to present the extracted information.
• Organize the information.
• Find the solutions to the specific problems.
• Must be able to give a solution for the problem. 

Why you should learn Data Science?

Well, it's completely up to you to learn Data Science or not, but one who is really excited to explore the data, to learn new technology, apply them into the real world should definitely learn this.

As it is one of the most emerging technology and the demand for a data scientist is high in many organizations so one can at least give it a try to learn Data Science.

As it is said Data is the new oil. It is valuable, costly and effective but if remain unrefined it is of no use. 

Finally I will conclude with, Data Science is something which involves cleaning the data, integration of the data, data transformation and finally preparing the data for the analysis purpose to get the value information from the raw data.