Difference between Analysis and Analytics

Data is the most important asset for every business as they need to know the issues due to which they are unable to gain profit. Businesses need to know the differences between data analytics and analysis. These words have different meanings but still, they are used interchangeably. If you are a data analyst, you will have to know the mood of the customers and the trends they follow. Data has exploded due to the usage of different electronic gadgets like laptops, smartphones, tablets, etc.

Data Analysis

Data analysis is performed when the performance of a business has to be taken into account. The variance between the actual figure and the number on the company budget is analyzed in this process. Experts have to analyze the reasons behind the decrease in sales or any other issues. The expectations of the stakeholders are also taken into account.

Different approaches are used to perform data analysis and they are discussed below −

A/B testing

A/B testing is a process in which two or more versions of a web page or an app is compared. This help to check which version is performing better. This testing helps in improving the app and web page.

Data Fusion and Integration

Data fusion and integration use various sources that are used to combine and analyze data to develop accuracy.

Data Mining

Data mining is a process in which data is extracted from different patterns for analysis. Data mining is also known as Knowledge Discovery in Data and its technique have been enhanced due to the development of data warehousing.

Machine Learning

Machine learning is the development of analytical research models is automated with the help of computer algorithms. It is a branch of artificial intelligence and it helps the computers to learn from the data available and make predictions accordingly.

Natural Language Processing

Natural Language Processing is a technology in which human languages are studied with the help of computer algorithms. It is a subfield of artificial intelligence which help the computers to process the human languages.

Types of Data Analysis

Data analysis is of different types and is used by many organizations to evaluate and manipulate data that is collected from different resources. Data analysis is of different types and we will discuss each of them in detail.

Hypothesis Analysis

This is a quantitative data analysis in which a theory or a hypothesis is tested by generating data. A new marketing campaign can be analyzed which will help in increasing the sales. Sales reports and customer engagement reports can also be generated.

Regression Analysis

This is also a quantitative analysis in which two variables are studied. One of these variables is independent and the other is dependent. This study is performed to know if there is any relationship between these variables. Regression analysis is of two types which are as follows −

• Simple Linear − This is a type of regression analysis in which a linear relation between the independent and the dependent variables is determined.
• Multiple Linear − This is a type of regression analysis in which the number of dependent variables is one but the number of independent variables is more than one. This analysis is conducted to know the effect of multiple factors on a single result.

Content Analysis

Content analysis belongs to the qualitative data analysis and text-based data is analyzed. This analysis includes data from social media posts, product reviews, etc. Organizations use this method to improve the quality of their products and services.

Data Analytics

Data analytics is a process in which the future is predicted and plans are made accordingly. Many tools are needed to help the experts to look forward and make future plans. Data analytics uses the components of data that have been obtained using analysis. Data analytics helps to predict the future performance of a company.

Types of Data Analytics

Data analytics is of different types which are as follows −

Qualitative Analytics

This is a type of analytics in which experts have to use their experience to go for the next business move.

Quantitative Analytics

This is a type of analytics in which different algorithms and formulas are applied to the numbers that experts have found through data analysis.

Descriptive Analytics

This is a type of data analytics in which data is gathered and visualized and helps organizations to make decisions.

Diagnostic Analytics

This is a type of analytics in which trends are determined so that they can be useful for the organization.

Predictive Analytics

This is a type of analytics in which future outcomes are foretold on the basis of historical data. Predictive analytics help companies to achieve their goals.

Prescriptive Analytics

This is the most advanced type of analytics in which useful insights are provided to the organizations to make further decisions. The results of predictive analyses are used to perform prescriptive analytics. Machine learning and other advanced tools are used to perform prescriptive analytics.

Benefits of Data Analytics

A business can get the following benefits of data analytics −

• Trends and patterns can be identified
• New opportunities can be generated
• Possible benefits and risks can be determined
• Proper strategies regarding future plans can be made

Difference between Analysis and Analytics

Data available is raw and it has to be converted into useful information so that businesspersons can use it for the progress of their businesses. There are many differences between data analysis and data analytics and we will look into them in detail.