Data Science And How To Use Data To Make Better Business Decisions
                     Data Science And How To Use Data To 
Make Better Business Decisions
Introduction : 
To extract useful insights and knowledge from 
data, data science is an interdisciplinary field that 
combines methods from computer science, 
statistics, and domain expertise.  
To solve complicated issues, come to wise 
decisions, and identify trends and patterns, it 
entails gathering, processing, analyzing, and 
interpreting data. By providing evidence-based 
information, data science plays a critical role in 
assisting businesses in making more informed 
decisions. 
The following are some essential actions and ideas 
for leveraging data to improve business decisions:
2
Source: manavrachnauniversity.com
Establish the Business Problem:  
To begin, precisely identify the issue or choice 
that data science is intended to help you with. 
Recognize the underlying objectives, targets, 
and limitations.
Data gathering: 
Compile pertinent information from a variety of 
sources, including internal databases, external 
sources, and third-party data providers. 
Make sure the data is accurate and complete.
3
Source:projectpro.io
Feature engineering: 
Enhance the quality and applicability of the 
data for analysis by adding new features or 
changing already-existing ones. 
It might also be required to reduce 
dimensionality and select features.
Model Selection: 
Pick data science models and algorithms 
that make sense for the particular issue at 
hand. 
Regression, classification, clustering, and 
time series analysis are examples of 
common techniques.
4
Source:bernardmarr.com
Model Training and Evaluation:
 Split the data into training and testing 
sets, and train the chosen models on the 
training data.
 Evaluate model performance using 
metrics such as accuracy, precision, recall, 
or others relevant to the problem.
Predictive Modeling:
 Apply the trained model to make 
predictions or classifications on new or 
unseen data.
Interpretation and Visualization: 
To convey insights to stakeholders, 
interpret the results and visualize the 
findings. 
To comprehend the analysis's implications, 
you must complete this step.
5
Source:udacity.com
Making Decisions: 
Make well-informed business decisions by 
applying the knowledge gleaned from data 
analysis. 
These choices could have an impact on 
product development, marketing tweaks, 
resource allocation, strategy 
modifications, or any other area of the 
company.
Implementation and Monitoring:
 Carry out the decisions and keep an eye 
on their long-term effects.
 Continue gathering and analyzing data in 
order to evaluate the decisions' efficacy 
and make any necessary corrections.
6
Source:datascience-pm.com
Feedback Loop: 
The study of data science involves 
iterations. Constantly refine models and 
decision-making procedures by 
incorporating new information and user 
feedback.
Ethical Considerations: 
Make sure that the gathering and analysis 
of data is done in an ethical manner, 
adhering to all applicable laws, and taking 
privacy concerns into account.
Data Governance: 
Set up procedures for data governance 
inside the company to ensure data 
security, compliance, and quality.
7
Source:analyticsinsight.com
Data Governance: 
Set up procedures for data governance 
inside the company to ensure data 
security, compliance, and quality.
Effective communication :
It is essential for successful decision-
making when it comes to conveying data-
driven insights and their implications to 
non-technical stakeholders.
8
Source:simplilearn.com
Conclusion: 
Businesses can find new opportunities, 
cut expenses, optimize operations, and 
enhance customer experiences with the 
help of data science.
It is an effective tool for obtaining a 
competitive edge and making more 
informed decisions across a range of 
industries.
9
Source:iindianAI.com
THANK YOU
10