Data science is an integrative field that employs scientific methods and algorithms to extract knowledge from data, encompassing a variety of techniques such as machine learning and analytics. It follows a non-linear workflow for data exploration and modeling, with a lifecycle that structures data science projects. The importance of data science lies in its ability to enhance decision-making, optimize processes, and uncover insights from large datasets.

1. What is Data Science
What is Data Science ?
Data science is an integrative field that uses scientific methods,
processes,algorithms and systems to extract, knowledge and
awareness from data in various forms,both structured and unstructured,
similar to data mining
Data science is a “conceptto unify statistics, data analysis, machine
learning and their related methods in order to “understand and analyse
actual phenomena” With data
Differentkinds of Data Science :-
 Python
 Artificial intelligence
 R programming

2.  Deep learning
 Machine learning
 Text mining and Analytics
 Data analytics
How to work on Data Science ?
Data science work flow is a non-linear, iterative process that involves
asking questions,getting Data ,exploring data, modelling data, and
communication Data. Their work through implementation and then test.
The team Data science process provides alife cycle to structure the
developmentof your data science projects.The lifecycle outlines the
steps , from start to finish ,that projects usually follow when they are
executed.
Why do we need Data Science :-
Data science helps humans make better decisions;either quicker
decisions or better decisions .it can do more than that. Data science is
not a new role, but the creation of a chief data scientist represents the
enhance of executive capability for big data solutions. Data scientists
are big data wranglers.

3. Purpose of Data Science :-
In simple word is the purpose of data analytics is make bestout of
waste. It is very important to first clearly understand for what purpose
you are conducting the analysis. Data analysis is a processof applying
statistical practice to organize, represent, describe,evaluate and
interpret data.
Importance of Data Science :-
Data science is an combining field , it deals with processes and systems,
that are used to extract knowledge or understanding from large amounts
of data

4. It is an “idea to bind together measurements , information , examination ,
machine learning and their related strategies “ keeping in mind the end
goal to “comprehend& break real miracle with data. It uses systems &
hypothesis drawn from numerous fields inside the setting of arithmetic,
insights, data science and software engineer.
Benefits of Data Science :-
 Data science deals with process & systems
 It is used extract knowledge & insights, from large amounts of data
 Data science is a tool that can be used to help reduce costs
 It can find new markets & make better decisions
 Data science techniques are great at spotting abnormalities.
Optimization , constraint problems,predic and targeting.

5. “ withoutbig Data analytics, companiesare blind and deaf,
Wandering outonto the web like deer on a free way”