Basis of data analysis

Enterprise data analysis

• Analysis of current situation ( analysis The present The data of ）︰ The overall situation at this stage , The proportion of each part 、 Development 、 change ;
• Cause analysis ( analysis In the past The data of ）︰ Why does a situation happen , Determine the cause , Make adjustments and optimize ;
• Predictive analysis （ Combined with data prediction future ）︰ Combined with the existing data, predict the future development trend .

Data analysis de classification

Offline analysis ( Batch Processing )

Face the past , Facing History , Analysis of existing data ;
There are obvious batch changes in the time dimension . Analyze every week (T+7), Analyze every day (T+1), So it's also called The batch .

Real time analysis (Real Time Processing |Streaming )

Face the present , Analyze the data generated in real time ;
The so-called real-time means that the time interval from data generation to data analysis to data application is very short , It can be subdivided into seconds 、 millisecond .

machine learning ( Machine Learning )

Predict what will happen in the future based on historical data and real-time data generated at present ﹔ Focus on the application of mathematical algorithms , Such as classification 、 clustering 、 relation 、 forecast .

Data analysis steps

• Around the data
• Where does the data come from 、 Where is the data going
• The core step : collection 、 Handle 、 analysis 、 application

Clear analysis purpose and thinking

• The purpose is the starting point of the whole analysis process , For data collection 、 Processing and analysis provide clear direction ;
• The idea is to systematize the analysis framework , For example, what to analyze first , Post analysis , Make logical connection between analysis points , Ensure the integrity of the analysis dimension , The validity and correctness of the analysis results , Data analysis methodology is needed to support ;
• Data analysis methodology is some related theories of marketing management , For example, user behavior theory 、PEST analysis 、5W2H Analytical method, etc .

data collection

• The process of data from nothing : For example, sensors collect meteorological data 、 Burying points to collect user behavior data
• The process of data transmission and handling : For example, collect database data to data analysis platform

Common data sources and types

Data processing

• To be precise , It should be called data preprocessing .
• Data preprocessing needs to process and sort out the collected data , Form a style suitable for data analysis , It mainly includes Data cleaning 、 Data transformation 、 Data Extraction 、 Data calculation ;
• Data preprocessing can Ensure the consistency and effectiveness of data , Let the data become Clean structured data .

What is clean structured data ?
Professionally speaking, it is the data of two-dimensional table , Row column correspondence ;
Generally speaking, it means clear format , Data conducive to interpretation

Data analysis

• Use appropriate analytical methods and tools , Analyze the processed data , Extract valuable information , The process of forming valid conclusions ;
• Need to master various data analysis methods , Also familiar with the operation of data analysis software ﹔

Data presentation

• Data presentation is also called data visualization , It refers to the chart display of analysis results , Because humans are visual animals ;
• Data visualization ( Data Visualization) It belongs to a kind of data application ;
  Be careful , The results of data analysis are not only visual display , You can also continue data mining (Data Mining )、 Ad hoc inquiry (Ad Hoc ) etc. .

Report writing

• The data analysis report is a summary and presentation of the whole data analysis process
• Analyze the cause of the data 、 The process 、 The results and recommendations are presented in full , For decision makers
• There needs to be a clear conclusion , It's best to have suggestions or solutions