Data analytics [Neurosurgery Wiki]

This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong.
====== Data analytics ======

[[Data]] analytics is the science of analyzing [[raw data]] in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and [[algorithm]]s that work over raw data for human consumption.
----
Data analytics refers to the process of examining large sets of data to extract meaningful insights and draw conclusions. It involves using statistical and computational methods to identify patterns, trends, and correlations in the data.

There are several types of data analytics:

Descriptive analytics: Descriptive analytics involves summarizing and visualizing data to gain insights into past events or trends. This type of analytics is often used to create dashboards and reports that provide a high-level overview of key performance indicators.

Diagnostic analytics: Diagnostic analytics involves analyzing data to understand why certain events or trends occurred. This type of analytics is often used to identify the root cause of problems or to optimize processes.

Predictive analytics: Predictive analytics involves using historical data to make predictions about future events or trends. This type of analytics is often used to forecast demand, identify potential risks, or optimize resource allocation.

Prescriptive analytics: Prescriptive analytics involves using data to identify the best course of action in a given situation. This type of analytics is often used to optimize decision-making processes or to create automated decision-making systems.

Data analytics is used in a wide range of industries, including healthcare, finance, marketing, and manufacturing. It has become increasingly important in recent years as more and more organizations have access to large amounts of data and seek to use it to improve their operations and decision-making processes.