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2. INTRODUCTIONTO DATA SCIENCE
Data Science is one amongst the fastest-growing, difficult and high paying jobs of this
decade. So, the question is what is data science? data science is an interdisciplinary
field (it consists of more than one branch of study) that uses statistics, computer
science and machine learning algorithms to gain insights from both structured and
unstructured data. According to ‘Economic Times’ India has seen more than 400
percent rise in demand for data science professionals across varied industry sectors
at a time when the supply of such talent witness slow growth.
4. APPLICATIONS
1. Marketing
There is a huge scope in marketing, for example, Improved Pricing strategy Companies like Uber, e-commerce
companies can use data science-driven pricing which allows them to increase their profits.
2. Healthcare
Using wearable data to prevent and monitor health problems.The data generated from the body can be used in
healthcare to prevent future emergencies.
3. Banking and Finance
As we discussed the introduction to data science now we will go ahead with the application of data science uses in
the banking sector for fraud detection which can be helpful in reducing the Non-Performing Assets of banks.
4. Government Policies
The Government can use data science to prepare better policies to cater better to the needs of the people and what
they want using the data they can get by conducting surveys and others from other official sources.
5. ADVANTAGES
In this topic of IntroductionTo Data Science, we also show you the advantages of Data Science. Some of them are as
follows:
It helps America to induce insights from the historical information with its powerful tools.
It helps to optimize the business, hire the right persons and generate more revenue as using data science helps
you to make better future decisions for the business.
Companies can develop and market their products better as they can better select their target customers.
Introduction to Data Science also helps consumers search for better goods, especially in e-commerce sites based
on the data-driven recommendation system.
6. DISADVANTAGES
As we studied about the introduction to data science now we are going ahead with
the disadvantages of data science:
The disadvantages are generally when data science is used for customer profiling and
infringement of customer privacy, as their information, such as transactions,
purchases, and subscriptions, is visible their parent companies.The information
obtained mistreatment knowledge science is used against a precise cluster,
individual, country or community.
7. OUTCOMES
On fortunate completion of this unit a student ought to be ready to:
analyze the role of data in organizations, including curation and management issues;
apply basic tools for performing exploratory data analysis and visualization;
apply basic tools for managing and processing big data;
apply basic predictive modeling and data analysis methods;
determine data storage and processing requirements for a data science project;
identify data resources and standards.
8. THANKYOU
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