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Data Analytics Vs Data Analysis: Are They Really Same Concepts?

Intro

Most people consider both data analysis and data analytics to be the same concepts/terms and use them interchangeably. However, it is a misconception and both terms are completely different from each other. So, to solve this problem once and for all today we are going to share with you the difference between both data analytics and data analysis.

What Does Data Analytics Mean?

Data analytics in simple terms means the process of collecting and analyzing data to find the answer to unusual trends and business problems. The main goal of data analytics is to find hidden insights and present them in such a way that anyone can easily understand them. By performing data analytics, you should have a clear image of the present/past performance of your business and what you should do to achieve your future business goals. To learn how to perform successful data analytics join the Data Analytics Online Course in Dubai right now.

Why You Should Perform Data Analytics?

Raw data is not very useful and carries zero value. However, by performing analytics you can discover, understand, visualize and present hidden patterns in your data to help top management in making business strategies. After analyzing your data, you should be able to:

  • Discover trends/insights.
  • Identify new opportunities.
  • Forecast future events and circumstances.
  • Make prudent decisions based on facts instead of your gut feeling.

How It Can Help Your Business?

By performing data analytics, a business can get lots of advantages and benefits like:

  • Understanding and predicting change in the behavior of customers due to change in factors like the price of a product or marketing process.
  • Preventing cyberattacks.
  • Enhancing data security and data integrity.

What Is the Process of Performing Data Analytics?

Following is the process of performing data analytics:

  1. Collect and combine data from various sources and mediums to analyze it.
  2. Categorize data
  3. Manage data in databases and data warehouses.
  4. Store data in a data storage device or solution.
  5. Perform ETL operations (Extract, Transform, Load)
  6. Analyze data to identify patterns and insights.
  7. Present found insights and patterns using visual dashboards and reports.

What Does Data Analysis Mean?

Data analysis is just a single piece of the data analytics cake. In simple terms, it is the process of data cleaning, transforming/converting, managing, and questioning data to find insights and useful information. While performing data analysis you will check, arrange and question a dataset to find meaningful information from it.

What Is the Process of Doing Data Analysis?

Following is the process of doing data analysis:

  1. Grant data access to others.
  2. Present data and insights with the help of data visualization software.
  3. Give suggestions based on found patterns and insights.

What Are the Different Types of Data Analysis Techniques?

Following are some of the most popular data analysis techniques:

  1. Text analysis: It is also known as data mining. The main purpose of this analysis is to find patterns and trends from large volumes of data using data mining tools.
  2. Statistical analysis: An organization uses statistical analysis to identify the reason behind particular patterns and trends by analyzing past data. It includes activities like collecting, analyzing, interpreting, and presenting data.
  3. Diagnostic analysis: Diagnostic analysis allows an organization to discover the cause of a particular trend using the data from statistical analysis.
  4. Predictive analysis: Predictive analysis as the name suggest helps an organization in making forecasts and predictions using data from the past.

Data Analytics Vs Data Analytics: Which One Is Better?

Data analytics is better than data analysis. Data analytics is a big cake/pie whereas data analysis is just a small piece of this pie or cake. As per Brack nelson who is a Marketing Manager at a leading digital SEO agency data analytics is more useful and encompassing than the data from data analysis. For example, sending top management virtual dashboards and reports is more useful than sending only numbers that are found using data analysis. Thus it is right to say data analytics is more powerful and useful than data analysis. To learn more about data analysis and analytics feel free to join the Data Analytics Online Course in Saudi Arabia.

Conclusion

Both data analytics and data analysis are different concepts. Data analytics is a big apple whereas data analysis is just a small bite of an apple. So, make sure you don’t get confused between both of them and use these terms interchangeably. Both the concepts are very different and have their advantages and disadvantages and you should not get confused between both of them.

 

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