Make Yonghong data visualization charts in 5 minutes

How can non-professionals quickly make a data analysis chart in a few minutes (see the picture attached)? Yonghong provides more than 20 theme styles, which can satisfy users with different preferences.

Making such a chart is the same as making PPT. Making PPT is to drag different elements such as text, text boxes, pictures, etc. directly onto the page. To make such a data report, drag dashboards, charts, various types of tables, and various types of filters onto the page, and this is done.

For example, to make a chart, we can choose a certain data model, or just choose the data model of the user portrait just now, all fields in this model will be listed in the list on the left, just like cooking, all materials and raw materials are Inside, you can play freely later, and present what you want. For example, from simple to complex, to see what the profit of different products looks like, I drag the two fields of product and profit to the horizontal and vertical axes respectively. This is a simple requirement and can quickly display different products. What is the profit situation.
Analyzing the Chart

Suppose that the demand changes at this time, and I want to see the profit situation by date. It's very simple, drag the date field up and cover the product field. This is a dimension, and we can immediately see the trend of profit changing with date. If we want to see the profit situation of different products and different dates, we can combine the two dimensions, different products are displayed in different colors, and we can get the profit trend of each product. The same is true if you want to look at the mix of different products and different regions. Therefore, the adjustment and combination of dimensions can be changed arbitrarily.

For visualization, charts are not only for good looks, but also have business meanings themselves. For example, bubbles and word clouds are suitable for viewing concentration, and scatter is suitable for viewing the distribution of large entities. When looking at different business meanings in different scenarios, we need to use different chart types, and we can switch freely. For the statistical functions of the sum and average of profits, we can choose in it, change a calculation formula, and directly present the results in real-time calculation. This way we don't have to ask a question like in the past and don't know the answer until the IT department has a result, now I want to know, I can see it right away.

Many people think that for a prediction, the sum of squares and variance can no longer meet their needs. In the morning, we also emphasized another key point. As a one-stop big data analysis platform, we can allow users to complete both descriptive analysis and in-depth analysis on one interface and platform. For example, commonly used analysis algorithms are encapsulated in the front end, so that some business users, even users who do not understand data mining and machine learning at all, can easily use them.

If we want to predict the sum of six-month profits, we only need to simply configure a few options, which may include registration date, order date, purchase date, and each date field as a time column. At this time, the background will start to make a prediction calculation on the data, and then present a result. Because the complexity of the mining algorithm is greater than that of the summary statistics for descriptive analysis, it will take a relatively longer time. The blue curve we see is the historical data, and the orange data to the right is the forecast for the next six months. We can also compare some data to see if the prediction is accurate, to tune the parameters of the algorithm, which requires a professional person to do, or a different algorithm to make predictions. On a platform, whether it is in-depth analysis or exploratory analysis, it can be quickly operated and implemented within a few minutes.