Self-service BI tools can help business personnel fully understand and utilize enterprise data, create new analysis through visual operations, drag and drop, generate visual reports, and help enterprises make decisions. However, research in recent years has found that products with powerful analysis strategies and models, such as BI tools such as Tableau, qlikview, and congos, cannot fully meet the needs of users, because most current BI tools still lack some functional blind spots.
Self-service BI tools, also known as agile BI tools, have the biggest feature of changing the demand response model of IT staff and business staff. As long as the IT staff prepares the data, the business staff can freely and self-help carry out various data analysis and make various reports without other support from the IT staff. This kind of cooperation only exists when the analysis and data are relatively stable, that is, what I want to analyze, you have already prepared the data early. But this is not the case in reality. Many business personnel may use data that does not meet the requirements when re-analyzing. At this time, they need to find IT personnel to deal with it immediately, otherwise the analysis cannot be carried out. This broke the original cooperation method and brought a lot of trouble to everyone.
The solution to the problem is to open up some data to business personnel, so that they can process the data at the front end and process it into the data they need. Of course, it is impossible for them to write complex SQL like IT personnel. The only way is to provide a visual interface, so that business personnel can clean and transform data through the visual ETL process, and finally generate the required data.
Based on such a scenario, FanRuan Business Intelligence FineBI pioneered the self-service data preparation function - the SPA spiral analysis function, which perfectly solves the self-service data preparation needs of front-end business personnel. SPA Spiral Analysis, in essence, is to open the data processing authority of the business package to the business personnel, so that they have ETL capabilities, and can visualize the required data without technical background, greatly improving the analysis efficiency and reducing the support pressure of the IT department. At the same time, the efficiency of data preparation and modeling by the IT department is improved by 5 to 10 times.
The following picture understands FineBI's spiral analysis.
The operation steps of FineBI spiral analysis:
1. Create a new spiral analysis
2. After selecting the service package data table, perform ETL operation configuration and output the required data.
The merge table function in the new spiral analysis covers the join and union functions in etl processing. If you want to obtain the Cartesian product, or the data table splicing, etc., you can achieve it by merging tables.
3. Check the effect.
The newly created spiral analysis table can be selected and dragged from the service package selection area on the left in the component detailed setting interface, or deleted.
