OCC Dashboard

Through Operations Control Center (OCC) dashboards you can view in real-time the key areas of your SAP environment with multiple indicators correlated in single views for early detection of top offenders. The capacity to detect issues at early stage is a game changer in improving users experience.

Operation Control Center Dashboard provides a direct access to key metrics stored inside Focused Run. It is primarily intended for IT and business experts who need to build quickly detailed views for in depth analysis.

OCC Dashboard is flexible and easy to use, it offers a single web interface to administrate, configure and display your dashboard instances. Several data providers help to access data sources on different time periods and different resolutions. You can filter and merge various metrics on the same chart while the look and feel can easily be changed with few clicks.

Release Notes: The OCC Dashboard is available starting with FRUN 2.0 FP01.

Data visualization is based on the following concepts:

  • Rolling Time Dimension
  • Query
  • Chart / Renderer
  • Query Attributes

Rolling Time Dimension

To build compelling stories with your data, IT analytics are constructed on a rolling time dimension containing two attributes: period and granularity.

The period defines the duration of the measurements and the resolution defines the scale of the data points.  (Ex: Today / HourLast 6 Months / Month).

The time dimension is propagated from the dashboards to the individual charts.

Query

Data are manipulated by queries.

A query is responsible to return either a set of measures (series) or a row-column structured data format (table). There are two types of series:

  1. Time series: A series of data points indexed in time order.
  2. Categorical value series: The values of measures are represented on the y-axis, while dimensions provide the axis of the chart.

Chart / Renderer

Chart

The chart is responsible of the data visualization. Some charts are dedicated to the table format while other charts are used for series format.

A chart could display multiple series. In that case, the series need to have a common dimension of the x-axis. In most of the case, the x-axis is given by the selected time period. In that case, charts are useful for showing the relationship between multiple measures over a period of time.

Renderer

Renderer are divided into the following categories:

  • Trend: This chart is typically used to show trends over time. Depending on your needs, a single Scale or a Double Scale or a Table chart can be used.
  • Comparison: This type of chart shows comparisons between two or more categorical values.
  • Distribution: It focuses on displaying the distribution of values within a data set.
  • Compliance: It Indicates compliance of dimensions towards an objective.
  • Table: The table chart shows raw data in a structured row/column format. You can choose between a dynamic table or an alert tree table. Tables offers usually break-down functionality with jump-in to detailed charts.

Query Attributes

Query attributes are attached to queries. They are instructions for the different charts on how to render the data and enrich dynamically the visualization.

Legend

The text to be displayed for the dimension visualized by each data sets.It supports two patterns:

  1. Single dimension (ex: Number of transports)
  2. Primary / Drill-down dimension (ex: Number of Tests / Passed)
  • Color: The color of the data points in the chart.
  • SLA, Yellow and Red Thresholds: An objective expressed by numerical thresholds used by compliance charts to give a view of a status of a dimension in relation to a goal. 
  • Jump-in: Renderer to be used for drill-down navigation between two charts.
  • Trend: Indicate if a measure should grow or reduce over time. It is used by compliance charts to compute the trend compliance.
  • TrendLine: A boolean to add a trend line based on linear or quadratic regression.
  • Display Value: Option to enrich line graph with the display of the value for each data points.
  • Display Attributes: Used to filter table data based on the column's name of the table's header.
  • Sort Attributes, Filter Attributes: Used to sort table data based on the column's name of the table's header.

How to Configure OCC Views

Before configuring the OCC Views first you have check How to Create a Dashboards. Afterwards there are four steps are needed to configure an OCC gadget.

1 Select Time Range: Period/Granularity


2
Select Renderer: Chart or Table


3
Add Queries


4
Configure Queries

The Query Editor lets you define the content by selecting and configuring a data source from one of the following options

  • System Monitoring
  • Real User Monitoring
  • Synthetic User Monitoring
  • Open Component Monitoring