Open AccessData Science Techniques, Tools and Predictions
Author(s) -
Mr.Mujthaba Gulam Muqeeth*,
Dr.Manjur Kolhar,
Dr.Aballa AlAmeen,
Dr.Mohammed Rahmath
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f9887.038620
Subject(s) - data science , computer science , business intelligence , relevance (law) , field (mathematics) , big data , data visualization , visualization , management science , artificial intelligence , knowledge management , data mining , engineering , mathematics , political science , pure mathematics , law
Almighty created human being with numerous wants and needs which makes them associated with their own data, choices and preferences. To grow and develop any business or organizations it is very obligatory to know their clients requests or customer needs based on their data. The evolving role of data makes it very vital element in any organization and carried with convinced operations. In this paper we are going to present a study of Data Science and its relevance with Artificial Intelligence, machine learning and deep learning. The incorporation of these intellectual sciences in data science is useful for perming numerous operations in our research we tried to demonstrate the data science operations like data cleaning, data processing, data modeling, data visualization and data presentations techniques. To grow any business it is mandatory to know their customer needs and satisfy their future expectations by smart decision makings. The intellectual algorithms or data operations in the data science make the data to be more effective in decision making and decision polices. We also focus on how data science incorporates mathematical & statistical methods, logical reasoning with applications of Artificial Intelligence techniques. We also focus on various data operations tools which exists in the market like python, SAS, R and many others. At last we focusses on how data science field going to meet the future expectations of many businesses. This research paper may become as successful reference for the people to carry out their research and meet the expectations of data science field with business growing decisions.