What is data science

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and
systems to extract knowledge and insights from structured and unstructured data.

 Let's see how data scientist goes through in his/her work !!!😱
 1.Identifying Business Problem
a data scientist initial job will be identifying the business problem the
should selected under important of the topic selecting the most
problem that will influence the business growth and when the problem is
identified & selected he/she thinking about why this problem has arisen so
many questions has to be answered to tackle the current scenario tough the
data scientist needs to collect the data from the various sources hence, next
phase will be collecting information relevant to solve the business problem

 2. Data Acquisition
 this step can be also described data mining due to the nature of this process. data can be
collected from multiple sources according to the availability & similarly the data are
from the various like web servers, logs, databases, API's and online repositories this seem's
takes both times and effort taking the process to complete and collected the data need to
filtered so the phase will be data preparation.
 3.Data Preparation
 The next job will be data preparation where he has to organize the data which includes two
phases of the process which data cleaning and data preparation this is the most time-
consuming process where the data scientist needs to work on the data .data cleaning
activity due to the data collected from various sources might include inconsistent data,
misspelled attributes and missed or duplicate values. in spite of data cleaning the other part
of preparation could be a data transformation. here the data scientist's objective will be to
modify the data according to the defined mapping rules. moreover for minimizing the
complexity of the data formation project team will use the e-tail tools like TALENT,
INFORMATICA.


4. Exploratory Data Analysis After the preparation of the data, the next stage
is to what you can do the data very crucial, with the help of EDA
(EXPLORATORY DATA ANALYSIS ) the data is defined and refined the
selection feature variables that will be used in the model construction
5.Data Modelling
In the process of the prospect is to identify the model that give optimum
fits to the business requirements by trialing the data set's and the test them
to select the best acting model the are a few programs are used to do this like
python, R and SAS6. Visualization and Communication

6. Visualization and Communication this is the most complex part of the work where
needed to meet the clients again continue to communicate the business findings simple
and effective manner to convince the stakeholder for this tool TABLEAU, POWER BI and
QLICK VIEW which will help in creating power repots and dashboard's
7. Deploy and Maintaining In this process, the data scientist test the
selected models in the pre-production environment before deploying it in a
production environment which is the best practice and after successfully
deploying it then reports and dashboards are used for acquiring real-
time analytics apart from that scientist also monitor and maintenance project
performance this will end up data scientist project

now you got data scientist work in his/her project
let's take how a data science changes the world
data science provide understanding genetic issue in a deeper sense in reaction to particular drugs and
disease. logistics companies like DHK, FEDEX have discovered the best time, routes, transportation
mode, and delivery does leading to cost of efficiency
in another case of this data science not help predict employee attrition but also the variables that
affected in employee turn over also the airline's companies can easily predict the flight delay
communicate it with passengers before and to enhance the travel experience
There are various roles offered to a data scientist like :
1 Data Analyst
2 Machine Learning Engineer
3 Deep Learning Engineer
4 Data Engineer
5 Data Scientist
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