Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and make decisions based upon the data analysis.
If your business is not growing, then you have to look back and acknowledge your mistakes and make a plan again without repeating those mistakes. And even if your business is growing, then you have to look forward to making the business grow more. All you need to do is analyze your business data and business processes.
The Data Analysis Process is nothing but gathering information by using a proper application or tool which allows you to explore the data and find a pattern in it. Based on that information and data, you can make decisions, or you can get ultimate conclusions.
Data Analysis consists of the following phases:
1. Data Requirement Gathering
2. Data Collection
3. Data Cleaning
4. Data Analysis
5. Data Interpretation
6. Data Visualization
There are several types of Data Analysis techniques that exist based on business and technology.
However, the major Data Analysis methods are:
1. Text Analysis: Text Analysis is also referred to as Data Mining. It is one of the methods of data analysis to discover a pattern in large data sets using databases or data mining tools. It is used to transform raw data into business information. Business Intelligence tools are present in the market which are used to make strategic business decisions. Overall it offers a way to extract and examine data and derive patterns and finally interpretation of the data.
2. Diagnostic Analysis: Diagnostic Analysis shows "Why did it happen?" by finding the cause from the insight found in
3. Statistical Analysis. Statistical Analysis shows "What happen?" by using past data in the form of dashboards. Statistical Analysis includes collection, analysis, interpretation, presentation, and modeling of data. It analysis a set of data or a sample of data.
4. Predictive Analysis : Predictive Analysis: This Analysis makes predictions about future outcomes based on current or past data. Forecasting is just an estimate. Its accuracy is based on how much detailed information you have and how much you dig into it.
5. Prescriptive Analysis: Prescriptive Analysis combines the insight from all previous Analysis to determine which action to take in a current problem or decision. Most data-driven companies are utilizing Prescriptive Analysis because predictive and descriptive Analysis is not enough to improve data performance. Based on current situations and problems, they analyze the data and make decisions.