WEEK SIX
TOPIC 2: Types of Analytics
Contents
1. Data Analytics
2. Text Analytics
3. Business Analytics
4. Other Types of Analytics
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Get Help Now!As we have already discussed, analytics are “the quantifiable informational inputs that use past data to identify possible trends that may provide valuable insight for future action”.1 But “analytics” is a broad term, and there are several different types of analytics, depending on the data being analyzed, the specific application of the analytics, and the purpose of the analysis.
Below are the definitions and general applications of the most common types of analytics.
1. Data Analytics
Data analytics is the science of examining raw data with the purpose of drawing conclusions about that information.2 The category of “data analytics” is the umbrella under which most types of analytics fall.
2. Text Analytics
Text analytics is often used interchangeably with the term “text mining,” where both terms refer to the extraction of data or information from text.3 It is used for several purposes, such as summarization (trying to find the key content across a larger body of information or a single document), sentiment analysis (what is the nature of commentary on an issue), explicative (what is driving that commentary), investigative (what are the particular cases of a specific issue) and classification (what subject or what key content pieces does the text talk about).4
3. Business Analytics
Business analytics can be broken out into several different types: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
Three of these types were covered in the Business Intelligence, Analytics and Decision Making course. The following charts will look familiar to those who have taken that course:
The chart above explains the purpose of each type of business analytics, while the chart below shows the hierarchy of value attached to each type.
Below are the definitions for the three types above, as well as another type, diagnostic analytics:
A. Descriptive Analytics:
Descriptive analytics are about the past: What happened?
This type of analytics helps organizations understand what happened in the past, whether it was 5 minutes ago or 10 years ago. Understanding and learning from the past can influence and/or instruct future action.
B. Diagnostic Analytics:
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