The information extracted from massive amounts of data using data analytics is extremely valuable, for example, to support top-level business decisions, identify new sales and marketing opportunities, enhance an organization's social media marketing capabilities, increase user loyalty as well as repurchase rates, reduce user churn, and anticipate risks in advance and take precautions.
So what is data analytics?
Data analytics is the use of appropriate statistical analysis methods to analyze a large amount of data collected, and then processed and processed to develop the function of the data, mining the value of the data, the main purpose is to clean out the useful information and to form conclusions.
In short, data analytics is the process of analyzing the acquired data for a certain problem and discovering the business value.
Purpose of Data Analysis
Data analysis is the process of examining and summarizing data in detail in order to extract useful information and form conclusions. Data in this context, also called observations, are the results of experiments, measurements, observations, surveys, etc., and are often presented in quantitative form.
The purpose of data analysis is to focus and refine the information hidden behind a large number of seemingly disorganized data, and to summarize the inner laws of the object under study. In practice, data analysis can help managers to make judgments and decisions in order to take appropriate strategies and actions.
The role of data analysis
Data analysis has three main roles in the analysis of the daily operation of the enterprise, including the analysis of the status quo, the analysis of the causes, and the analysis of the forecast.
Current situation analysis
Simply put, it tells you what happened in the past. Specifically embodied in: first, to tell you the overall operation of the enterprise at this stage, through the completion of the various business indicators to measure the state of the enterprise's operations, in order to illustrate the overall operation of the enterprise is good or bad, how good the degree of how, and where the degree of bad.
Second, it tells you the composition of the various businesses of the enterprise, so that you can understand the development and changes in the various businesses of the enterprise, and have a more in-depth understanding of the state of the enterprise's operations. The status quo analysis is generally accomplished through daily briefings, such as daily, weekly, and monthly reports.
The descriptive data analysis used for status analysis is descriptive data analysis, descriptive data analysis belongs to a primary method of data analysis, common analysis methods are comparative analysis, average analysis, cross analysis, etc.
The analysis of the current status of the company's business is not only the analysis of the company's business, but also of the company's business.
Cause analysis
Simply put, it tells you why a certain status quo occurs. After the first stage of the status quo analysis, we have a basic understanding of the operation of the enterprise, but we do not know the operation of the specific good where, poor where, what causes. This is where a cause analysis is needed to further determine the specific reasons for the change in operations.
Cause analysis is accomplished through thematic analysis, according to the business operations to choose to target a current situation for cause analysis. Cause analysis belongs to the category of exploratory analysis, commonly used methods are grouping analysis, structural analysis, cross-analysis, DuPont analysis, funnel plot analysis, matrix correlation analysis, cluster analysis and so on.
Predictive Analytics
Simply put, it tells you what will happen in the future. After understanding the current state of business operations, it is sometimes necessary to make predictions about the future development trend of the enterprise, in order to provide an effective reference and decision-making basis for the formulation of business objectives and strategies to ensure the sustainable and healthy development of the enterprise.
Predictive analysis is generally done through thematic analysis, usually in the development of quarterly and annual plans, the frequency of which is not as high as the analysis of the current situation and analysis of the causes of the commonly used methods of regression analysis, time series, decision trees, neural networks, etc.
The analysis of the future development of the company's operations is also necessary to understand the current situation of the company's operations.
Specifically, we can divide the common data analysis methods into descriptive analysis, mathematical analysis, modeling analysis, descriptive data analysis belongs to the primary data analysis, usually used for the description of the status quo of things, while mathematical analysis and modeling analysis belongs to the advanced data analysis, the need to establish a certain statistical analysis model.
The process of data analysis
The process of data analysis can be divided into the following six steps, which are divided into a clear purpose of analysis, data collection, data processing, data analysis, report presentation, and report writing.
Data collection
Data collection is the process of collecting relevant data in accordance with the defined data analysis framework, which provides the material and basis for data analysis, and the data mentioned here include first-hand data and second-hand data.
Data processing
Data processing refers to the processing and organizing of the collected data to form a style suitable for data analysis, it is an essential stage before data analysis, data processing mainly includes data cleaning, data conversion, data extraction, data calculation and other processing methods.
Data analysis
Data analysis refers to the use of appropriate statistical analysis methods to analyze a large amount of data collected, to summarize and understand them and digest them, in order to maximize the development of the function of the data, play the role of data.
Data Visualization
Typically, data is presented in tables and graphs. Commonly used data charts include pie charts, bar charts, bar graphs, line graphs, scatter plots, radar charts, and so on.
Report Writing
A data analysis report is a summary and presentation of the entire data analysis process. Through the report, the cause, process, results and recommendations of data analysis are presented in a complete way for decision makers.
"The knowledge gained from paper is not as shallow as it should be, and the knowledge of the matter must be practiced." Knowledge from books, after all, is not perfect enough, if you want to y understand the reasoning, you must personally practice it, for data analysis, the same is true, only the combination of theory and practice, in order to achieve higher-order data analysis, in the data analysis of the road farther and farther.