Still worrying about business data analysis? Excel is only one add-in to self-service BI!

In the previous article "Excel Fusion Analysis-Perfect Integration of Excel and BI, Really Empower First-line Users", we introduced the positioning and main features of Excel Fusion Analysis, and also demonstrated the specific application scenarios of Excel Fusion Analysis with an example. After reading it, many Excel users expressed great interest and expressed their hope to continue to learn more about this feature. Therefore, this time we start with the characteristics of Excel fusion analysis, and continue to analyze the problems and advantages that Excel fusion analysis can solve!

We know that Excel fusion analysis allows them to use self-service BI functions without changing the habits of Excel users, that is, maintaining the advantages of Excel (easy to use, using Excel templates, data and functions, etc.); and It can solve the problems of Excel (security, performance, sharing, etc.); it can also integrate the powerful data acquisition and processing capabilities of BI tools. The following wheat introduces these characteristics one by one:

How does Excel Fusion Analysis retain the advantages of Excel?

1. Easy to learn and use
As we all know, Excel is highly popular and easy to learn and use. Excel integration and analysis to Excel / WPS as a designer , to achieve design and analysis reports by installing plug-in on Excel / WPS. Compared with other Excel designers, using Excel as the designer will not change the habits of Excel users. However, Excel users are more handy to operate on the familiar interface, saving learning costs and improving work efficiency!

2. Template reuse

There are a large number of Excel-based report templates for users. These templates include EXCEL graphics, formula functions, layout styles, etc., which have accumulated a lot of business wisdom of the enterprise, and the calculation and processing logic is complicated. If you change to other analysis tools, Excel business templates cannot be reused.

The Excel fusion analysis is operated on the Excel interface. It can separate the template from the data. When the data is updated and changed, the data of the entire template will be automatically updated, so as to realize the reuse of the template to dynamically update the data.

The following figure is "Customer Repurchase Analysis". It is divided into multiple Sheet pages, including customer repurchase trends, customer repurchase conversions, RFM analysis, industry analysis and other analysis content. The EXCEL graphics, formula functions, layout styles, etc. in these sheet pages are all set.

Note: If you want to view the specific content of "Customer Repurchase Analysis", please refer to our intelligent analysis online system.

As shown in the figure below, the data of these analysis templates comes from the yellow data column data automatically calculated from the original data in the blue column in the "Data Table". We only need to replace the original detailed data in the blue column in the "data sheet" with the data set data ready to be processed, and then the analysis chart on the analysis page can be automatically updated to realize the reuse of the entire EXCEL template.

3. On-demand data governance

Generally, without data analysis, problems with data integrity and data quality cannot be discovered. When we find that the original data is inaccurate when we analyze it, we can manually correct it in Excel for immediate analysis without waiting for the improvement of the business system. At the same time, it will drive users to do background data management and improve data integrity The efficiency of evolution.

As shown in the figure below, the original data of "Customer Source" in the sales details is inaccurate. We can manually create a "Customer Source Revision" sheet in Excel to correct it. After the correction is completed, the data can be analyzed immediately. Waiting for the improvement of system data, while also promoting business system data governance.

4. Calculation and analysis capabilities
We know that Excel has powerful calculation capabilities and data analysis capabilities. All analysis work of Excel fusion analysis is completed in Excel, which completely retains Excel's data reprocessing and data analysis capabilities.

(1) Completely retain related calculation capabilities such as Excel formula functions .

(2) Completely retain the various charting capabilities of Excel . In Excel, select the appropriate chart through the relationship between the data to make the theme and content expressed more simple and clear, such as line chart, bar chart, pie chart, etc., mini chart basic graphics, as well as accordion chart, bullet chart and other advanced graphics .

(3) Completely retain the data analysis capabilities of Excel . Pivot table can be used to aggregate and categorize detailed data, which can easily and quickly get the desired results. In Excel fusion analysis, it is also possible to use Excel's own pivot table for data analysis, such as realizing irregular and dynamically expanding reports.

How does Excel Fusion Analysis solve Excel's problems?

1. Performance issues

We know that Excel’s performance problems are quite prominent. For example, tens of millions of detailed data cannot be loaded by Excel; Excel calculation formulas are complicated, and it takes tens of minutes to open, etc., which seriously affects the use and analysis of users. Below we cite a few of the most common performance problems, and see how to use Excel Fusion Analysis to solve these problems.

Question 1: The front-line business personnel may obtain an Excel schedule, which may exceed tens of millions and cannot be loaded into Excel for analysis.

Solution: We can do data preparation work in Smartbi through perspective analysis and SmartbiMPP function, and the data can be summarized initially.

For example, every minute of sales records, there are tens of millions of data accumulated. We can use SmartbiMPP and perspective analysis to aggregate detailed data to get daily or weekly summary data, so that tens of millions of detailed data will become hundreds of thousands of aggregated data. After the amount of data becomes smaller, we can analyze it in Excel.

In addition, we can also add filtering parameters to the perspective analysis, and further control the number of data displayed through parameters, thereby improving performance.

Question 2: The calculation formula in the Excel table is complicated, and Excel opens slowly, which may take tens of minutes;

Solution: Excel fusion analysis supports operations on the personal Excel side and also supports operations on the server (cluster). We can open it on the Web after completing the calculation on the backend, and then export it to an Excel static file without formulas. Users only need to open the final result without formulas to view, and opening such an Excel static file will be very fast.

Question 3: The user wants to use the pivot table for exploratory analysis in Excel, and the ultimate goal is to view the exploratory results. However, because the amount of data is relatively large, such as hundreds of thousands, the pivot table is very slow to explore.

Solution: First, we can use the [Load 100 rows by default] function to perform pivot table exploration and analysis based on 100-row sampled data, which solves the problem of slow pivot table exploration and analysis.

Then, we publish the exploration results and load them with the full amount of data when they are finally displayed on the Web side, so that the final view of the exploration results is the full amount of data.

2. Sharing issues

Problem description: The report exists in the Excel file, so the form of sharing can only be to share the entire Excel file. Most users share the Excel file through email or instant messaging software, so the file is flying all over the sky and it is difficult to manage. In addition, this is not good enough for the control of the authority system and the convenience of distribution.

Solution: We can solve the problem of Excel file sharing by publishing resources on the platform through Excel fusion analysis.

1. We need to publish the prepared Excel fusion analysis report to the server for browsing and management. We can also share the published reports via Web links to achieve real-time data update.

2. Before sharing, you can set resource permissions, data permissions, and report permissions to realize that different users see different resources, different users see different data, and different users see different scopes in the same report. For details, refer to the next chapter on security issues.

3. Security issues

Problem description:
We know that using Excel for resource sharing will have security problems, which are mainly reflected in the following aspects:

• The authority is not easy to control, and it is inconvenient for users within the authority to view the corresponding report.
• It is impossible to share only analysis results without sharing detailed data;
• The data cannot be different for each person, and the data is dynamically updated according to user permissions.

Solution: Through our smartbi authority management system, we can help users solve the above problems and achieve the effect of safety management:

1. Through resource permissions, only users within the permissions can view the corresponding reports.
   

2. Realize through the data authority to the front-line business personnel, can only process the data within the scope of their authority.
   

3. Field-level desensitization protection is achieved through desensitization rules, and data permissions in reports are precisely controlled. The permission setting can be achieved through desensitization rules.
   
   

4. Through the permission setting function in the report, the viewing and browsing permissions of the detailed data inside the report can be controlled for different reports.
   

How does Excel Fusion Analysis integrate the powerful data capabilities of BI?

1. Self-service access

Problem description: We know that the process of obtaining data from Excel is troublesome. The data can be retrieved by exporting to Excel or pasting into Excel. In particular, the periodic and repetitive (same data, different regions, and different permissions) data acquisition must also be generated separately. Data preparation is completely dependent on IT, and the response is not timely enough.

Solution: In the product, IT only needs to help business users to make data catalogs and make wide tables. Business users can automatically fetch data through data sets, perspective analysis, etc. for processing, and then drag the result fields directly into Excel after processing. , Once refreshed, the data comes out. For periodic and repetitive access requirements, we can solve them through parameter filtering and permission settings.

In addition, the product includes a variety of functions to meet users' different access needs. The specific instructions are as follows:

✦ Self-service data set

If we want to realize cross-database query, we can realize that the data set is more self-service data set. The self-service data set mainly realizes cross-database and cross-table query; it will process the bottom data of the data to a certain extent, and it will handle it well. The table is saved as the basis for subsequent data visualization.

✦ Perspective analysis

Business users perform custom data processing on the list data based on the Smartbi perspective analysis function. By simply selecting the check box, they can filter out the summary data results required by Excel from the tens of millions of list data, and generate a perspective analysis result set, which fully meets the business needs User self-service data preparation!

Moreover, the results of perspective analysis are generally smaller. If the statistical performance is not fast enough, you can use SmartbiMPP for performance acceleration. In addition, perspective analysis can generate parameters by dragging and dropping fields to realize dynamic parameterization.

✦ Imported data file

In business, there is often a need to upload files and save them to the database, and then view the data in the data table; in order to facilitate user data management and use text data more conveniently, Smartbi can load file data and import data files into the cache library Or data source.

2. Data union

Online and offline data integration refers to the realization of data matching by obtaining online data and combining local static data through formulas for data analysis and display.

Application scenarios: There are many scenarios that require online and offline data integration. For example, sales detail data is obtained from an online database, but the "customer tag" is stored in a local Excel file, which has not yet been standardized and is on demand. Through joint analysis of online and offline data, we can have different promotion methods for customers with different labels.

Solution: First, realize self-service access to sales detail data through Smartbi data service and Excel plug-in function. Data connection, preparation and processing are carried out through the Smartbi data service function, and then in the Excel designer, drag and drop fields from the data set panel to the corresponding Excel cell to realize self-service access.

Then use the VLOOKUP function to match and obtain data from the "Customer Tag" page, thereby realizing online and offline data integration.

Through the above introduction, I believe that now you have a deeper understanding of the features of Excel Fusion Analysis! If you are also an Excel user and hope to use Excel fusion analysis to solve your problem, please go to our Smartbi official website experience center to experience it!