In this age of advancement in the field of tech, data is one of the trendiest topics. When we study data or related subjects, the two terms, data analytics and data analysis, often cross our paths. Are these synonyms? Are they the same word or just closely related? Taking a data analytics course can help an individual understand this concept better. In this article, we’ll discuss the similarities and differences between these terms.

What is Data Analytics?

Data analytics is an umbrella term that deals with the concept of data and all functionalities and attributes related to it. The principal aim for specialists who work on data, such as business analysts, is to make the best use of the data available or accessible to them. This method can be efficiently learned with the help of several data analytics courses.

Raw data, which isn’t processed is valueless. How you use data is actually what makes it valuable. Data analytics comprises those steps, both human- and machine-enabled, which identity, decipher, and display your data to utilize it in the best possible manner for business strategies and outcomes.

Data analytics includes many processes:

  • Gathering data
  • Categorizing it
  • Maintaining the data in databases
  • Ensuring relevant data storage
  • Extracting useful data
  • Analyzing data for insights and patterns
  • Visualizing data

What is Data Analysis?

Data analysis is a small subset of data analytics. Data analysis comprises cleansing, converting, modeling, and inquiring data to find valuable information.

Following are the most commonly known data analytics techniques:

  • Text analysis – This process is also called data mining and it involves figuring out patterns and insights from data sets with the help of databases.
  • Statistical analysis – This involves demonstrating what exactly happened by employing prior stored data.
  • Diagnostic analysis – This elaborates the cause of why something happened by using insights to look for the root cause
  • Predictive analysis – When you want to find out what can happen in the future, you can use predictive analysis on existing data and make a prediction about future outcomes.
  • Prescriptive analysis – In this, the analyst gathers meaningful information from all the above mentioned analytics mentiods to make the final decision.

Comparing Data Analysis and Data Analytics

  • Data analytics is a general or broader form of analytics that is used by organizations to make the best use of data, whereas data analysis is a specialized portion of data analytics that is used to analyze data.
  • Data analytics is a traditional form of analytics that is used in many ways like the healthcare area, industry, telecom, insurance to obtain conclusions from data and implement important operations on data. Data analysis is a specific form of data analytics used in businesses and other domains to take useful information from data.

Conclusion

Nowadays, data usage is exponentially increasing, and a tremendous measure of data is gathered over organizations. Both data analytics and data analysis are crucial processes conducted over data to utilize it in the best possible manner. There are various data analytics courses available in the market to understand these concepts better.