Lesson 1 Flashcards
Is a statistical interpretation used to analyze historical data to identify patterns and relationships.
Descriptive Analytics
Seeks to describe an event, phenomenon, or outcome.
Descriptive Analytics
Is about discovering patterns in data and communicating these trends to various stakeholders.
Analytics
Four (4) Basic Types of Analytics
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
Summarizes and interprets historical data
Descriptive Analytics
Examines why things happened the way they did.
Diagnostic Analytics
Uses historical data to make predictions. It provides forecasts on probability and possible effects of particular future outcomes.
Predictive Analytics
Makes use of results from descriptive, diagnostic and predictive analytics to arrive at suggestions for businesses to ensure good potential outcomes.
Prescriptive Analytics
What information do descriptive analytics?
- Can be applied to a wide variety of everyday operational activities of a business.
- Reports on Inventory
- Various Workflows
- Sales Figures
- Revenue Statistics
How do descriptive analytics work?
The organization first need to create a set of metrics that will measure business performance against business goals.
With the necessary metrics in place, relevant data must be collected. It will then have to be managed, cleansed, and prepped for the next step, which is the data analytics.
Historical data collection for descriptive analytics is done using two main techniques:
- Data Aggregation
- Data Mining
How to apply descriptive analytics to an organization?
- Identify Relevant Metrics
- Identify Data to Support These Metrics
- Data Extraction and Preparation
- Data Analysis
- Data Presentation
The organization needs to know the metrics to be created.
These metrics should reflect primary business goals for each sector of the company or from the organization.
Identify Relevant Metrics
Find the data needed to support the required metrics.
The data can be found across several siloes and files for some organizations.
Identify Data to Support These Metrics
If an organization is working across multiple data sources, it will need to extract data, merge it, and prepare it for analysis to ensure uniformity.
Data Extraction and Preparation
This is a drawn-out process but is critical for accuracy.
Data Extraction and Preparation
Part of removing redundancies and mistakes and creating data in a format suitable for analysis.
Data cleansing
There are several tools available to provide descriptive analytics. These can range from basic spreadsheets to a wide range of more complex business intelligence (BI) software.
Data Analysis
The final aspect of descriptive analytics is presenting the data. This is usually done using visualization techniques, with compelling and exciting forms of presentation to make the data accessible for the user to understand.
Data Presentation
There are several benefits of descriptive analytics.
- Simple Analysis
- Many Tools Available
- It Answers Most Common Business Performance Questions
Descriptive analysis doesn’t require great expertise or experience in statistical methods or analytics.
Simple Analysis
Many apps make this function a plug-and-play form of analysis.
Many Tools Available
Most stakeholders and salespeople want simple answers to basic questions such as “How are we doing?” or “Why did sales drop?” Descriptive analytics provides the data to effectively and efficiently answer those questions.
It Answers Most Common Business Performance Questions
Challenges of Descriptive Analytics
- It is a Blunt Tool without Insight
- It tells an Organization What, Not Why
- Can Measure the Wrong Thing
- Poor Data Quality
