I am Neel Hetalkumar Shah (18IT124) a final year student of CSPIT CHRUSAT University of Btech(I.T). As my 7th semester project I have taken up a research project on how different countries are stressed and calculate the stress index of those countries based on multiple factors.
Business Analytics vs. Data Science
It’s important to highlight the difference between data analytics and data science. While Both processes use big data to solve business problems they’re separate fields.
The main goal of business analytics is to extract meaningful insights from data to guide organizational decisions, while data science is focused on turning raw data into meaningful conclusions through using algorithms and statistical models. Business analysts participate in tasks such as budgeting, forecasting, and product development, while data scientists focus on data wrangling, programming, and statistical modeling.
While they consist of different functions and processes, business analytics and data science are both vital to today’s organizations. Here are four examples of how organizations are using business analytics to their benefit.
what do you mean by business analytics
There are four key types of business analytics: descriptive, predictive, diagnostic, and prescriptive. Descriptive analytics is the interpretation of historical data to identify trends and patterns, while predictive analytics centers on taking that information and using it to forecast future outcomes. Diagnostic analytics can be used to identify the root cause of a problem. In the case of prescriptive analytics, testing and other techniques are employed to determine which outcome will yield the best result in a given scenario.
Across industries, these data-driven approaches have been employed by professionals to make informed business decisions and attain organizational success.
DATA LIFE CYCLE STAGES
The data life cycle is often described as a cycle because the lessons learned and insights acquired from one data project typically inform the next. In this way, the final step of the process feeds back into the first.
Data Pre processing
When ever we are preparing any machine learning model or trying to get insights of the collected data we encounter some anomalies in the data. this might alter our results. thus it is best practice that to remove such data from our data sets, and thus removing and modifying data for further deduction is called data preprocessing.
Preprocessing includes many methods using which user can standardize their data. few of them are listed below :
1 . Data Cleaning
2. Data Integration
3. Data Transformation
4. Data Reduction
5. Data Discretization
6. Data sampling
Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end-users to create their own reports and dashboards. It is part of the Microsoft Power Platform.
research paper
types of data
Power BI dashboards
average temperatures country wise for pollution findings
Types of Data Analytics
Data analytics is broken down into four basic types.
- Descriptive analytics: This describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?
- Diagnostic analytics: This focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?
- Predictive analytics: This moves to what is likely going to happen in the near term. What happened to sales the last time we had a hot summer? How many weather models predict a hot summer this year?
- Prescriptive analytics: This suggests a course of action. If the likelihood of a hot summer is measured as an average of these five weather models is above 58%, we should add an evening shift to the brewery and rent an additional tank to increase output.
attributes for the research:-
types of stress:
financial stress:
work load
less income
over income
family stress
financial stress index
it is usually measured by profitability measure and a solvency measure.
social stress:
social isolation
age
unhappy
difficult companionship
living lifestyle
anxiety
mental stress:
it is affected depending upon the internal or external factors caused by different stress
physical stress:
external can be from physical over work or underwork,
emotional overflow,
body or mental tension,
internal can be from illness or medical procedure
Post trauma stress
peer stress:
money
competition due to literacy
personal envy
work stress:
unhealthy relationship among peers
incompetency in work
economical growth
emotional stress:
death of a close alibi
increase in financial or social obligations
chronic illness or injury
post trauma stress
depression
anxiety
main outcomes of stress on humans:
depression
anxiety
anger
grief
guilt
low self esteem
stress index
general formula =
Control — Controlled
— — — — — — — — — — — -
Control + controlled
lies between -1 to +1
to view my research conclusion visit my github repository.
Thank You!
Click: Github Link
