While the words data analytics may conjure up images of statistical nerds wearing white lab coats and poring over reams of seemingly useless and complicated data, the field is actually very valuable. Data analytics, when analyzed and interpreted correctly, can help professionals in every field – from accounting to healthcare understand key developments better.
It’s only when they have that type of understanding that they can make strategic decisions that can impact the employment of many, the survival prospects of terminally ill patients, and the ability of a company to survive an economic downturn, among other things. It’s time to understand what data analytics is, and more importantly how it’s applied to various professions!
If you have ever applied for a home loan and have been approved, you can thank data analytics. Data analytics is a complex set of processes that uses various statistical and mathematical tools and technologies to interpret and analyze text and numerical data. Managers use analyses and interpretations as the foundation for running businesses better and generating insights that inform strategic decisions.
In the mortgage industry, a good example might be using data from a statistical model to analyze certain variables that play a role in determining which customers are good borrowers and predicting their ability to pay back their loans within 15 or 30 years. Learn Data Analytics from Industry experts at Data Analytics Classes in Pune
Healthcare professionals and providers use data analytics to predict which patients would be most receptive to certain types of innovative healthcare. Doctors and nurses can also use data analytics to establish a normal baseline and use that to compare scans in sick patients versus healthy people. The findings and analyses can help them treat these sick patients better.
Healthcare professionals can also use data analysis to predict which sections of the population are most susceptible to a certain virus or bacterial outbreak. A good example would be to predict how many vaccinated versus unvaccinated people are susceptible to getting the Delta or Omicron variants of COVID-19.
Healthcare professionals use four types of data analysis when creating predictive models for various aspects of medicine and healthcare. These are:
- Descriptive analytics – professionals analyze previous patient data to spot trends and patterns in their overall health. They can also use this data to establish a baseline for health in these patients. For example, doctors can look at certain demographic and medical data to determine which sections of the global population are most vulnerable to getting COVID-19.
- Prescriptive analytics – doctors use machine learning and AI to make vital medical decisions and strategies.
- Predictive analytics – doctors and healthcare professionals could develop models to understand how likely it is for fully vaccinated healthy people to die from a particular strain of COVID-19.
- Discovery analysis – doctors and healthcare professionals use AI to analyze clinical data for patterns and insights that humans might miss. A good example could be the number of patients who could die from a rare side effect of a new breast cancer drug.
Accountants who work in firms use data analytics to predict which business departments are likely to be the most productive and profitable based on historical performance. These professionals can also analyze data to identify which business operations or departments are the riskiest. They can take measures to improve the company’s overall profitability and lower its expenses by minimizing those risks.
Some accountants work with marketing departments and provide these marketers with the interpretations needed for them (the marketers) to make strategic decisions that can strengthen sales and customer bases. Accountants can accomplish that by analyzing consumer buying behaviour and other marketing data. Learn Python from experts at Python Training in Pune
Businesses hire finance professionals for more than working with accounting to manage their budgets and help make them even more profitable. Finance professionals use data analytics to glean financial insights that can help support all departments – from production and operations management, to marketing – in their strategic decisions.
Finance wizards can also use data analytics to better understand their companies’ Key Performance Indicators. Examples of KPIs include revenue streams, profit margins, and payroll expenses. A full understanding of these KPIs can help finance professionals keep their companies profitable and financially viable during a bad and long recession.
Data analytics are transforming every profession – from healthcare to engineering to business. Professionals rely on insights gleaned from data analytics to make key decisions that can help save lives, keep companies profitable during economic downturns, or prevent massive layoffs. Data analytics is here to stay an