BIT-430: Introduction to Business Analytics course examines the basic business analytics concepts with specific emphasis on descriptive analytics. With our BIT-430: Introduction to Business Analytics homework help, learners are introduced to techniques and selected industry tools relevant for describing data behavior.
What is business analytics in health care and how it differs from health care and data analytics?
Business analytics is the process by which businesses use statistical methods and technologies for analyzing historical data in order to gain new insight and improve strategic decision-making. Also, business analytics is a data management solution and business intelligence subset which refers to methodologies such as data mining, predictive analytics, and statistical analysis in order to analyze and transform data into relevant information, identify and anticipate trends and outcomes thus making smarter and data-driven business decisions. In short, it is the use of math and statistics to derive meaning from data in order to make better business decisions.
Healthcare analytics is the process of analyzing current and historical industry data to predict trends, improve outreach, and even better manage the spread of diseases.
Data analytics refers to the discipline of analyzing raw data in order to change that data into useful information from which trends and metrics can be discovered.
Main components of business analytics.
It sorts through large datasets using databases, statistics, and machine learning to identify trends and establish relationships.
This is the process of gathering, organizing, and filtering data. This can be done either through volunteered data or transactional records.
Association and sequence identification.
This refers to the identification of predictable actions that are performed in association with other actions or sequentially.
Text mining explores and organizes large, unstructured text datasets for the purpose of qualitative and quantitative analysis.
Predictive analytics utilizes several statistical techniques to create predictive models, which extract information from datasets, identify patterns, and provide a predictive score for an array of organizational outcomes.
Forecasting analyzes historical data from a specific period in order to make informed estimates that are predictive in determining future trends and behaviors.
After trends have been identified and predictions have been made, businesses can engage in simulation methods to test-out best-case scenarios.
Data visualization provides visual representations such as charts and graphs for easy and quick data analysis.
Types of analytics in business.
1. Descriptive analytics.
This focuses on describing or summarizing the existing data using existing business intelligence tools to better understand what is going on or what has happened.
2. Diagnostic analytics.
Diagnostic analytics focuses on past performance to determine what happened and why.
3. Predictive analytics.
This type of business analytics emphasizes predicting the possible outcome using statistical models and machine learning techniques.
4. Prescriptive analytics.
Prescriptive analytics is used to recommend one or more courses of action on analyzing the data. That is, it can suggest all favorable outcomes according to a specified course of action and also suggests various courses of action to achieve a particular outcome.
Role of business analytics in health care.
· Improving productivity and collaboration in the healthcare organization’s facilities.
Data analysis may provide better ways of providing healthcare to patients.
· It enhances patient support in hospitals.
Business analytics enables hospitals to organize how to support patients well.
· Making the correct real estate investment for hospitals.
Business analytics can forecast potentially viable clinical sites. Therefore, healthcare providers are able to identify places that are more suited for opening health care facilities that are profitable.
· Optimize healthcare business operations.
Business analytics help hospitals to optimize their staff according to the workload in the facility. Moreover, it enables businesses to cut down administrative costs, monitor and control fraud.
· Improve the quality of patient care.
Analytics may help improve patient safety, patient wellness, and also help in improving patient satisfaction, acquisition, and retention.
· Improve patient care in ICU.
It helps hospitals to be better prepared for emergency cases. This is because prescriptive analytics may offer possible actions for future problems.
· Support long-term expansion plans.
Hospitals use predictive analytics for long-term planning and expansion projects.
· It helps pharmaceutical industries to develop new and more effective drugs.
Predictive analytics makes clinical trials shorter, more effective, and powerful.