Create rich multi-layer visualizations in Oracle Analytics Cloud

An overlay chart is one of the most versatile visualizations available in Oracle Analytics Cloud. It enables dashboard creators to present rich data through multiple different charts stacked in layers on a single visualization; thereby making the overlay chart a robust and powerful mode for visualizing your data.

Let’s assume that a sales dataset for a retail organization looks like this:

To analyze this data, you can leverage the following features of overlay charts:

1. Multi-layered visualization: Because an overlay chart is composed of multiple individual charts overlaid on top of each other, all individual charts share the common category axis. Therefore, an overlay chart provides a separate grammar edge to each chart layer so that the chart in a layer can be formatted independently of charts in other layers.
   You can start with plotting quarterly Profit in conjunction with Discount and Shipping Cost Trend on an overlay chart. In the following image, Shipping Cost, Discount, and Cumulative Profit are plotted against the Order Date (Quarter) in separate layers as an area chart, bar chart, and stacked bar chart respectively.
   
   You can add as many layers as you need on an overlay chart. Supported chart types are bar, stacked bar, line, area, category, and stacked category.
2. Control transparency of a chart layer: When multiple charts overlap on the same area as in an overlay chart, portions of one chart might hide important portions of another chart. You can adjust the transparency of a chart layer to discern the characteristics of other chart layers. This increases the visibility of other chart layers, making the overlay chart able to display a comprehensive insight.
   In the following figure, the transparency of the stacked bar chart for the profit has been adjusted to accentuate the line and area charts.
   
3. Add KPI style card visualizations: While the chart visualizations provide insights at a specific granular level, a summary measure can add valuable context to the granular data. You can add measures to the tile section of the grammar panel of an overlay chart to display KPI style visualizations as in the following figure:
   
   You can add one primary measure and up to 4 secondary measures into the tile of an overlay chart. From the property panel, you can configure the position, alignment, and other formatting of these KPI visualizations in the tile.
   
   You can also apply conditional formatting to KPI measures in the tile by adding and applying the conditional formatting rules on the overlay chart. The following figure shows a conditional formatting rule to format the background of profit data values greater than $2,500,000. This rule is available to be applied on the tile as well as the chart. The rule is applied to the tile, and the background of the profit data values turns green as specified in the rule.
   

Perform pareto analysis with an overlay chart
There is a wide range of applications for overlay charts, and pareto analysis is one such case. Pareto charts are used to analyze data about the frequency or cost of problems or causes in a process. They help to identify the most significant or high-priority areas for improvement or investigation. 

Using the previously mentioned dataset, you can perform a pareto analysis to identify top/bottom profitable products by following these steps:

1. Create a calculation (Product Profit Rank) to rank products, based upon profit by each product.
   
2. Create a calculation (Profit %) to perform a running sum of profit % contribution of each product to overall profit.
   
3. Create a calculation (Product Profit Quintile) to bin the products into 5 quintiles, based upon profit by product.
   
4. Create a pareto chart by putting the Product Profit Rank calculation into the Category (x-axis) grammar, the Profit % calculation into the y-axis of a line chart layer, and the Profit field into the y-axis of a bar chart layer.
5. Add the Product Profit Quintile calculation into the color grammar of both line and bar chart layers, as shown in the following figure:
   

The figure also shows the aggregate sum of profit and the total count of products into the tile of the chart to add context. The formatting of the measure was updated in the tile for a better appearance.

Call to action
Just like a pareto analysis, an overlay chart can be used to perform other complex analyses such as comparing multiple measures from a data series, finding the correlation of a measure across different data attributes, and many other functions. Overlay charts offer many more capabilities to create robust visualizations, and you can exploit these to create rich and fine-tuned visualizations to fit your needs. For more details, watch Overlay Chart Visualization in Oracle Analytics. Visit the Oracle Analytics community to post any queries or ideas.