This document discusses how data science can help solve problems in business. It begins by defining data science as the process of building, cleaning, and structuring datasets to analyze and extract meaning from data. Data scientists employ data analysis to help businesses make better decisions, measure performance, optimize finances, develop better products, and improve customer experiences. Some ways data science can help businesses include enabling innovative upgrades and improvements by understanding customer motivations, developing new products and services, and identifying new value within existing company data.

1. A P P L I CAT I O N
O F DATA
S C I E N C E I N
B U S I N E S S
SUBMITTED BY
MARIA KURIAN
2237045
2MAECO

2. W H AT I S
B U S I N E S S ?
The term business refers to an organization or
enterprising entity engaged in commercial, industrial,
or professional activities. The purpose of a business is
to organize some sort of economic production (of
goods or services). Businesses can be for-profit entities
or non-profit organizations fulfilling a charitable
mission or furthering a social cause. Businesses range in
scale and scope from sole proprietorships to large,
international corporations.
Business also refers to the efforts and activities
undertaken by individuals to produce and sell goods
and services for profit.

3. M A J O R P R O B L E M S
F A C E D I N T H E
F I E L D O F
B U S I N E S S
➢ 1. Uncertainty
Uncertainty in the global economy, uncertainty in the credit markets, uncertainty in
how new regulations will affect business, uncertainty about what competitors are doing,
and uncertainty about how new technology will affect the business—these are just the
start of a never-ending list. The bottom line is that uncertainty leads to a short-term
focus.
➢ 2. Globalization
Understanding foreign cultures is essential to everything from the ability to penetrate
new markets with existing products and services, to designing new products and
services for new customers, to recognizing emergent, disruptive competitors that only
months earlier weren’t even known. The problem to be solved is to better understand
international markets and cultures through better information gathering and
analysis of what it all means.Similarly, the incredible degree of government
intervention in nearly all major economies of the world is leading to much greater
uncertainty in the global marketplace, making international operations ever harder to
manage.

4. 3. Innovation
It is found that many companies are trying to create more innovative cultures.
This innovation came as a big surprise when people have changed quite a bit
since then. It seems that big companies are struggling with innovation, and for
many, a good innovation process is at the top of the list, but the idea of a more
innovative culture is frightening for too many. The problem to be solved is
how to be more creative while maintaining tight control over the organization.
4. Problem-solving
Lack of sophisticated approaches to data acquisition, analysis, and
development of specialized insights puts many companies at a disadvantage;
they have no long-term strategic needs and should instead jump from one
strategy to another for the year. The ability to solve everyday problems in
today’s business leaders also limits the ability to adequately deal with the first
nine problems.
5. Diversity
Diversity brings many challenges because people are more likely to disagree,
and a lack of agreement makes it much harder to run a business.
Simultaneously, the lack of diversity in many large company leadership groups
leads to a continually changing and narrow perspective of a different world.
The problem to be solved is first defining what difference is in your company
then isolated to ensure a harmonious environment.

5. DATA S C I E N C E
Data science is the process of building,
cleaning, and structuring datasets to analyze
and extract meaning. It’s not to be
confused with data analytics, which is the act
of analyzing and interpreting data. These
processes share many similarities and are
both valuable in the workplace.
This Photo by Unknown author is licensed under CC BY-ND.

6. DAT A S C I E N C E
• Data science requires you to:
• Form hypotheses
• Run experiments to gather data
• Assess data’s quality
• Clean and streamline datasets
• Organize and structure data for analysis
Data scientists often write algorithms—in coding languages like SQL and R—to
collect and analyze big data. When designed correctly and tested thoroughly,
algorithms can catch information or trends that humans miss. They can also
significantly speed up the processes of gathering and analyzing data.

7. • Businesses employ data scientists, who collect,
clean, organize, and analyze large data sets, in order
to solve a business problem and develop actionable
insights. In their daily work, consequently, data
scientists plunder big data to determine trends and
predictions and form conjectures that companies use
to make decisions about their operations, target
audiences, or products.
DATA S C I E N C E I N
B U S I N E S S

8. I M P O R T A N C E O F
DA T A S C I E N C E
I N B U S I N E S S
➢ Managing better business decisions.
Companies can use data and risk analysis practices to make
informed business decisions. The collection and analysis of data
collected within the company can assist higher-ups by providing
objective evidence to direct difficult business choices.
➢ Measuring performance
Data science allows businesses to measure performance through
data collection to make more educated decisions across the
organization by using trends and empirical evidence to help them
come up with solutions.

9. ➢ Providing information to internal finances
Your company can also use data science to make predictions, generate
financial reports, and analyze economic trends so you can make informed
decisions on budget, finances, and expenses. This will allow for a
fully optimized revenue generation with an accurate picture of what is going
on with internal finances.
➢ Developing better products
Data analysis can use a data-driven approach to provide verifiable and
evidence-based numbers that allow a company to reach its target audiences,
find what its audiences enjoy, and then cater its products to that audience.
➢ Improving customer experiences
Data collection on customers can be valuable in attracting a target market and
tailoring the customer experience and need toward the data collected. By
demonstrating their likes and dislikes, the results can increase sales and allow
companies to build a brand on which their customer base relies.

10. W A Y S D A T A
S C I E N C E C A N S O L V E
P R O B L E M S I N T H E
B U S I N E S S
1. Innovative Upgrades And Improvements
• Understanding what drives and motivates your purchasing
public is a secret businesses have longed to know ever since
commerce began. It is often driven by gut feelings or broad
and rough analysis of glaringly obvious data. Innovating your
existing product or service through upgrades and
improvements is one way to use data at your disposal to boost
revenue-deepening customer relations. Customers love their
familiar devices, but they may love them more when they are
given a new look, feel, or function which makes them better
and more relevant.
• Data science solutions can show developers opportunities
where increased interest and sales are simply hidden within
the product or service itself. Discovering this is a direct result
of a focused effort to use analytics to understand customer
motivations.

11. 2. Developing New Products And Services
There are times when the need arises for an entirely new product or service, often one
which is interrelated with your existing business goals and operations. A prime example of
this new development may be found in the company Netflix. It began its service as a
convenient and affordable alternative to renting movies. As demands and technology
evolved, their service gradually evolved too. First, by offering streaming services as a
secondary viewing option. Quickly, customers recognized its convenience and streaming
service grew to become the most popular viewing model.
3. Data-Value Identification
One of the best outcomes of using data science to solve business problems is that you often
end up inspiring and motivating data scientists on your team. They can feel like more than
simply analysts of information. Rather, they're part of a team imagining elegant solutions
that add value to customers, communities and business culture. By using the data your
business already collects, data science has the potential to help solve various problems in
new ways. It's another tool in your toolbox to build up your business by tackling obstacles
head-on.