Data Management

Data Analysis is the process of examining data, usually in datasets, to draw conclusions from that data. It involves organizing, cleaning and studying the data to find patterns, connections and trends. Data analysis attempts to answer questions like "How is this happening?", "What is going on?", Why is this happening", and "What is the cause / result of this event?" 

Like Data Management, Data Analysis is accomplished through a process, which includes:

1. Define Objectives
2. Collect Data
3. Clean and Process Data
4. Exploratory Analysis
5. Statistical Analysis
6. Visualize and Communicate the Results
7. Define New Objectives

Popular Data Analysis Tools

• Apache Spark
• Covidence (for Meta-Analysis)
• Microsoft Power BI
• Python
• R
• Statistical Analysis System (SAS)
• Tableau

Check our Software and Programming Tutorials collection for more Data Analysis tools

• Gives information to make decisions
• Helps companies compete better
• Helps organizations understand what their customers, employees and shareholders want
• Solve problems
• Evaluate performance - What is not working? What is working well? What can be done better?
• Manage risk

Descriptive Analysis

What happened in the past? What led to current conditions?

Diagnostic Analysis

Why did something happen? What were the reasons for the outcomes?

Predictive Analysis

What are the future trends? What does this data tell us will happen?

Prescriptive Analysis

What does the data tell us we need to do to reach our goals or accomplish our objectives?