In our work, we often encounter a variety of data. In order to analyze these data, we tend to visualize them.

The first step in data visualization is to choose the right chart.

How do I make graphs? Since the Excel era, the conventional wisdom has been that there are several “categories” and several “series” to populate data. Choose a chart that shows the results visually. This process is actually a rough analysis of the results of the data, and then graphically expressed, we call visualization 1.0. In addition, there are some problems for data analysis and statistics personnel in the presentation of traditional charts:

A. Visualizations depend on the limited types of diagrams provided by the tool

The types of charts provided by the tool are limited, and the need for analysis is infinite. Imagine that once the results of the analysis are multidimensional and you have only a few charts in your hand, data visualization is limited.

B. Understanding a set of artificially defined attributes such as “classification”/” series “is inherently difficult to use

This small editor has a deep experience, every time I use Excel to make charts, I do not understand what is classification, what is series, all kinds of blind click. Excel 2013 will automatically generate charts, but with more dimensions, there will be a lot of debugging. In fact, “classification”, “series” and other concepts, for the initial contact with analysis users, or take some time to deeply understand.

C. Don’t know what chart to use, but make a chart for the sake of making a chart

According to the majority of user surveys that want data analysis, 59% of users said that “the biggest problem facing users is what kind of graph analysis to display data.”

Therefore, in an era where data analysis is prevalent and is likely to become a necessary skill in the future, charts should assist analysis, condensing information from large, disordered data and facilitating exploratory analysis along with analytical thinking. We call this the era of Visualization 2.0.

Most of the visualization tools on the market are 1.0, which can assist in the analysis of ideas. There are not many visualization tools to display graphs. Tableau is a pioneer. The latest version of FineBI 5.0, in addition to the experience of exploratory data analysis, with data mining attributes, dynamic display features, is also worth recommending.

FineBI V5.0’s visual analysis is based on The well-known Grammar Of Graphics, which provides unlimited chart recommendations, unlimited property mapping effects, and new analysis capabilities.

It canceled the chart type concept, with “shape” and “color”, the “size”, “prompt”, “label” attributes such as (in addition to support free set also supports and dynamic display) field is bound to chart type to replace, thus FineBI will get rid of the chart type restrictions on visual effect, so as to achieve unlimited capacity chart type to show.

Smart charts are recommended for presentation

FineBI can recommend smart chart types based on the fields (dimension type/number, indicator number, and data periodicity) that users drag in, and display current data statistics in the most suitable form.

For a simple example, if you take a string of data, say, “month” and “sales” and drag it to the panel, it will automatically choose to display it in a bar chart.

As the chart above shows, there is no longer a struggle between pie charts and line charts.

FineBI visualization:

Analytical chart

Charts follow the thinking of data analysis.

For example, “faceted presentation” actually provides a perspective of data observation by analyzing multiple indicators side by side. For example, if I want to observe the data trend of temperature and shirt sales at the same time, I can use faceted analysis to make statistical observation of the data. The correlation of different indicators can be analyzed through the faceted analysis, so as to discover the potential correlation of data.

To take a simple example, we use a faceted display model to observe the impact of different degrees on overtime hours and earnings (non-actual data) :

Correlation between sales volume and growth in different years (non-actual data) :

Dashboard — Build data analytics stories

Often, we use data to create compelling, informative, and persuasive stories in data-reporting scenarios. In addition to providing unlimited chart analysis, FineBI dashboard also allows users to flexibly analyze the layout of data charts, easily build your data chart thinking logic, so that you have unique insights into data, and then achieve the purpose of effective communication or data reporting.

Real estate sales visualization data analysis story

Sales increased month by month year by year

— Higher real estate sales in all cities

— High sales, sales area far ahead

Home sales have led in every year

Multi-angle sales visualization data analysis story

— What should be sold, when and where? Children’s clothing, women’s clothing, men’s clothing?

A: Which category sells best?

B: Which region has the best sales?

— Which stores have the best sales

— Which brand has the best sales

A: What are the best sales days?

Chart adaptation

In addition to the rich chart presentation mentality, FineBI offers four adaptive patterns within charts, including:

Standard adaptation: built-in algorithm, when there is a lot of horizontal and vertical data, the chart automatically generates the scroll axis in the corresponding direction.

Overall fit: horizontal and vertical fill current display components.

Width adaptation: fill the data horizontally and judge whether there is an internal rolling shaft vertically according to the data situation.

Height adaptation: fill the data vertically and judge whether there is an internal rolling shaft according to the data horizontally.

Four adaptive modes meet different layout requirements of user dashboard design. At the same time, FineBI also allows users to manually adjust the width of the axis elements to meet more customized presentation requirements.

Dynamic chart presentation

In addition to static chart display, FineBI also supports users to add chart annotation and flicker animation, which can be dynamically displayed by users’ freely defined conditions, breaking the traditional static and rigid presentation form of charts and allowing users to experience more vivid data chart display effect.

Big data chart performance

In addition, the chart big data mode provided by FineBI can support the chart display of more than one million data volumes depending on the front-end performance.

Data analyst’s new weapon — data mining

FineBI, a data analysis tool, currently supports three data mining methods such as time series algorithm, clustering algorithm and classification algorithm, and also supports integration with R language.

If you want to predict future sales, you want to categorize your user base intelligently, or you want to know which users are more likely to get feedback when you text them, FineBI will do it.

In addition, FineBI also combines the time series algorithm and clustering algorithm with chart analysis, that is, we can not only realize the prediction and clustering, further, just need simple drag and drop can immediately see the prediction and clustering results, so that data mining is not only usable, but also easy to use.

The last

Due to space constraints, the graphs in this article are just the tip of the FineBI tool iceberg. Its essence is not only a data analysis visualization tool, but also can assist enterprise data analysis tool. Interested students can go to FineBI official website to activate the trial (personal free). I hope this BI tool can help you improve the efficiency of data analysis in your daily work.