Data Analytic projects

Question 1

Descriptive Analytics

Answer 1

Within a project, this type of analytics focuses on summarizing and describing historical data to provide insights into past trends and patterns. Descriptive analytics helps to answer questions such as ‘What happened?’ and ‘How many times did it happen?’ Descriptive analytics is perfect for the retail industry because retailers can analyze sales data, customer behavior, and inventory levels to identify trends and patterns.

Question 2

Diagnostic Analytics

Answer 2

Diagnostic analytics analyzes past data to identify the root causes of specific outcomes or events. Diagnostic analytics answers questions such as ‘Why did an event happen?’ and ‘What caused it to happen?’ In the healthcare industry, diagnostic analytics helps doctors and other medical professionals make more informed decisions about treatment options to improve patient outcomes.

Question 3

Predictive Analytics

Answer 3

Using historical data to forecast future outcomes, predictive analytics helps to answer questions such as ‘What is likely to happen in the future?’ and ‘How can we prepare for it?’ Banks and other financial institutions can use predictive analytics to analyze customer data and identify potential risks like defaulting on loans or credit card fraud. Predictive analytics allows financial institutions to make substantial decisions about lending and improve risk management.

Question 4

Prescriptive Analytics

Answer 4

This type of analytics recommends actions that can be taken to optimize or improve a situation. Prescriptive analytics considers data analysis and modeling to provide specific recommendations on what to do next. It answers questions such as ‘What should we do?’ and ‘How can we improve the outcome?’ This is the ideal analytics for the transportation industry because transportation companies can analyze traffic patterns, weather data, and other variables to optimize routes and reduce fuel consumption.

Question 5

Exploratory Analytics

Answer 5

This type of analytics involves exploring and analyzing data to identify potential trends, patterns, and relationships. Exploratory analytics is often used when there is no clear objective or question to answer, and the goal is to uncover new insights or opportunities. Exploratory analytics can be used in the manufacturing sector to identify areas for process improvement.