The road to visualization of Quick BI, the preferred product for cloud data analysis

Introduction to Quick BI is an intelligent data analysis and visualization BI product tailored for users on the cloud. It helps companies quickly complete the transition from traditional data analysis to data cloudification + analysis cloudification, and transforms business data into production After exiting, it will be pushed to the organizations for consumption at the fastest speed. This article focuses on the ability and evolution of Quick BI in visual analysis.

Quick BI is an intelligent data analysis and visualization BI product tailored for users on the cloud. It helps companies quickly complete the transition from traditional data analysis to data cloudization + analysis cloudification, and maximizes the output of business data. The fast speed is pushed to the consumption side of each organization.

This article focuses on the ability and evolution of Quick BI in visual analysis.

Quick BI visual analysis capability map

The result of the traditional report is the interpretation of the statistical model rather than the interpretation of the business. Therefore, the expectation of visual analysis is not reports, but DataStorytelling with analysis (insight) and narrative capabilities (insights), and visualization of Quick BI's 160e7c9c6f4237. The definition also extends from "visualization chart" to "insight + interpretation".

Part1 visualization

The visualization of Quick BI includes visualization charts, templates, and themes; the theme supports 6 sets of default themes (including dark and light skin colors), as well as user-defined themes to adapt to different product styles.

The visualization charts are divided into comparison charts, trend charts, distribution charts, relationship charts, proportion charts, and spatial charts according to analysis intent. The detailed follow-up will be expanded in another visualization.

Part2 Data Insight-Analytical Components

Visualization has always been the core capability of BI products, and Quick BI believes that data visualization should be upgraded from simple data presentation to rapid data analysis, and interactive visualization can significantly improve the efficiency of data analysis.

In addition to quickly discovering the association and composition relationship between data through interactive operations (drilling, linkage, jumping, circle selection, exclusion, etc.), Quick BI further provides interactive charts (indicator disassembly diagrams) to open new Quick insight into the way.

The newly added indicator disassembly diagram can help users customize the indicators and latitude required for analysis. Users can adjust the analysis dimensions and disassembly sequence at any time, and quickly locate the cause of impact when indicators fluctuate or abnormal.

At the same time, Quick BI's new line dynamic component supports the expression of static data in a dynamic form. Conventional pie charts, bar charts, bubble charts, etc. often can only express sliced data, but cannot express data that changes over time. Quick BI allows the most common graphics to intuitively express the dynamic changes of the business by combining the playback axis and the timeline.

For example, the dynamic bar chart used in the epidemic this year allows everyone to understand the changes in the epidemic situation in various countries and regions over time at a glance. Here, for example, offline and online user activity changes over time.

Part2 Data Insight-Volatility Analysis

In addition to describing the current information of the data, Quick BI can also combine machine learning, artificial intelligence, and visual analysis capabilities to allow analysts to quickly obtain and discover the value hidden in the data. For example, volatility analysis can help users automatically disassemble and analyze the causes of core indicator volatility in trend graphs, and present the impact of various factors on volatility in natural language. For example: the change trend of the order quantity of a store is as follows. The key influencing factors that affect the quantity of orders through the analysis of fluctuation reasons are that new\_add is 1111, and the area is North China. You can inquire whether some operations and operations have been carried out. .

Part3 Building a data story

In order to solve the multi-report and scattered in the business. And when the content of a single report is large, but there is no other person to explain, the reader cannot understand the problem, so the ability of Data Storytelling is introduced.

Data Storytelling is a data expression method that combines interactive data visualization and narrative technology, and presents the analysis content in an eye-catching and easy-to-understand format. Gartner has paid more attention to the value of data storytelling in the field of ABI in the past two years. Quick BI has also combined its own capabilities and domestic user scenarios to launch two levels of data story building capabilities.

is the multi-page level. 160e7c9c7005c2 Quick BI supports the organization of a large number of reports and links into " Data Portal" , which can help companies present the data analysis system progressively from a certain business perspective. Such a portal can range from the overall situation of the company to the form of sub-business and sub-department, or it can expand the data content one by one according to each link of production. A portal is a perspective for analyzing and using data. A good portal can often clearly express the business composition and even strategic direction of an enterprise.

The second level is page level . A single dashboard often focuses on an analysis topic or several analysis indicators, and it is often analyzed within a single page in the form of overall overview, trend change, and segmentation of different dimensions. Analysts often encounter problems such as lack of analysis ideas, many analysis components, and not knowing how to choose. Quick BI’s newly introduced "story line" component can greatly improve the efficiency of analysts’ organization and analysis of ideas and presentation of data value, so that Visitors to the report can quickly grasp the meaning and value behind the data.

We will explain the above three parties separately in the follow-up, so stay tuned!

To learn more about Quick BI, please check https://www.aliyun.com/product/bigdata/bi

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