What is the difference between data analytics and big data analytics? Is the salary the same?

What is data analytics?

Data analytics refers to the process of analyzing a large amount of data collected using appropriate statistical analysis methods, and studying and summarizing the data in detail without extracting useful information and forming conclusions.

Data analysis contains "data" and "analysis" of two aspects, including the collection, processing and organization of data, on the one hand, on the other hand, also includes the analysis of data, from which the extraction of valuable information and the formation of conclusions that help the business.

The results of data analysis are usually presented in the form of an analysis report. For a data analysis report, the analysis is the argument, the data is the argument, both are indispensable.

Traditional data analysis and big data analysis of the three similarities and differences:

First, in the analysis method, the two are not essentially different.

The core work of data analysis is to analyze, think and interpret the data indicators, the amount of data that the human brain can carry is extremely limited. Therefore, whether it is "traditional data analysis" or "big data analysis", the raw data need to be analyzed in accordance with the idea of statistical processing, to get a summary of the statistical results for human analysis. Both in this process is similar, the difference is only the size of the raw data caused by the different processing methods.

Secondly, there is a big difference in the center of gravity of the use of statistical knowledge.

Traditional data analytics uses knowledge centered around the theme of "whether the real world can be inferred from a small sample of data". "Big Data Analytics focuses on utilizing all types of full-volume data (not sample data) to design statistical scenarios that lead to statistical conclusions with both detail and confidence.

Third, there is a fundamental difference in the relationship with machine learning models.

"Traditional data analytics" in most cases, the knowledge of machine learning models as a black box tool to assist in analyzing data. The "big data analytics", more often than not, is a close combination of the two, big data analytics output is not only an analysis of the effectiveness of the evaluation, follow-up based on this to upgrade the product. In the big data analysis scenario, data analysis is often a prelude to data inking, data modeling is the result of data analysis.