Hello all, this read on what is data science is going to be the simplest of anything available on the internet world. You can easily grasp the content and you will be clear with this widespread topic. I thank padhAI for making me write my first blog. You can also gain more knowledge by visiting padhAI( https://padhai.onefourthlabs.in/).
Data science is the science of collecting, storing, processing, describing and modeling data. The one who practices data science is called a data scientist. The role of a data scientist is to find solutions for problems by analyzing big or small data with the help of appropriate tools and telling stories to communicate his/her findings to the problem holder.
Data collection
As the name suggests data collection is the process of collection of a large amount of data in the system. This is the first process involved in data science, data is collected to reveal the unknown hidden patterns inside which itself a solution for the problem.
Storing Data
The collected data is stored here and it is of various types. It is stored in the form of a relational database which is structured data(name, date, address, ph-number), multiple structured data is stored and analyzed in a place called the data warehouse. Text, image, video, audio are unstructured data which comprises big data. A large structured or unstructured data related to an organization that is dumped into it is called a data lake.
Processing Data
The stored data is now said to process and it follows a certain mechanism. When raw data is converted into meaningful data is called data wrangling. The missing values are filled and errors are rectified by the data cleaning process. And data scaling is done with normalization and standardization.
Describing Data
Describing data is known as visualizing it, Data visualization is known as a graphical representation of data. The so-far processed data cannot be directly viewed, the graph gives us a clear idea of the data.
Modeling Data
Building data models is called as modeling data. A model is built to reflect the output of the data. Statistical modeling includes mathematical concepts(statistics) to give appropriate results. The algorithmic modeling is a result of complex modeling which is done by machine learning concepts and deep learning is used to when we have a large amount of high dimensional data.
Coming to this line means you are now clear with the basic idea of data science. I hope you enjoyed the original content. Thank you
