Multi-dimensional analysis

1. Overview

In the process of data analysis, if we want to understand the data, we need to explore from different dimensions. If you only analyze from a single dimension, important data information is likely to be missed.

The important feature of FineBI is its flexibility to quickly drag dimensions and indicators to obtain analysis results; if traditional tools are used, it will take a lot of time to create or switch charts from multiple dimensions frequently. Please follow me to analyze "SALES" from multiple dimensions.

2. Implementation process

First, we prepare a multi-dimensional data table. Upload "sales data.xlsx" to FineBI and use it to create components.

2.1 Analyze by year

Analyzing sales using year as a dimension, it can be seen that sales have gradually increased over the years, indicating that operating conditions have become better and better in recent years, as shown below:

2.2 Analysis by month

Looking at sales from the year alone is still too general. Let's take a closer look at the sales trend from the month.

It can be observed that the sales in July each year drop sharply, and the sales from January to April are also very low. After observing the information displayed by the data, we can follow him to discover the reasons behind it.

2.3 Analysis by region/category

In order to be able to find more data information, we try to analyze the "SALES" from more dimensions, drag into the "REGION, CATEGORY" dimensions, as shown in the following figure:

As can be seen from the above figure, except for the "Central South" region, all other regions have the highest sales in the furniture category. From this, after we discover the anomaly, we can further discover the reason, whether it is due to strong competitors in the central and southern regions, or the furniture department in the central southern regions is sluggish, looking for opportunities to increase furniture sales.

2.4 Summary

Above, we have observed "SALES" from the dimensions of year, month, region/category, and obtained multiple data information. It can be seen that if you analyze from a single dimension, you may miss important data information, so when we analyze data, we need to switch more angles or dimensions, and use FineBI to switch flexibly.