OBIEE also adopt this approach, in fact, the middle layer of OBIEE ‘s RPD file, the business model and mapping layer , is where the data model reside.
All of this star schema concept is not a unique feature of OBIEE , OBIEE  is just an Oracle ‘s implementation of the star schema analysis.
For the above star schema, The central table is call the fact table, the other 4 tables is called the dimension table, which is correspondent with OBIEE ‘s logical fact table and logical dimension table. In general star schema concept, numeric data in fact table is call measure, which is the same with OBIEE ‘s naming convention. The most common business intelligence operation is drill down data into more detail data or vice versa. For example, Below is a business intelligence report describe the sales revenue for 2009 is.
And here ‘s an example of the time dimension which have a month-quarter-year hierarchy. The navigate choice of the interaction properties of a column permits you to navigate to an other answers and optionally to set a filter.
For a column in an answer, you can configure it to add a web-link on each value which point to an other answers that will be filtered with the help of the value in the weblink.
First, create the target answers with the details information that you need and add the drill column as filter. The result : When you click on the web-link of a customer id, the value is passed to the detail report and is then used to filter the details informations. Enterprise Manager 12c is the latest and greatest incarnation of Oracle’s toolset for Enterprise Management (the clue’s in the name), of which Cloud Control (nee Grid Control) is one of the key tools.
In this post and the next I am going to expand on what my colleagues have covered, looking firstly at how we can use (dare I say, leverage) Usage Tracking data to drive monitoring and alerting of important areas such as response time and dashboard error rates, and secondly the incorporation of existing JMeter-based performance tests into EM12c.
Alerts within EM12c are primarily handled through Incidents, which are concisely defined as “[…a] situation or issue you need to act on”.
The reference manual gives a nice illustration of how events and incidents are related, here. A target’s metrics trigger Events through Thresholds, which can be defined at both warning and critical levels if required. All of the above is core functionality provided by EM12c and in a sense generic to any target.
To provide flexibility in the monitoring that EM12c provides there is the concept of a Service. In the remainder of this post I am going to explain how to build an EM12c Service Test based on Usage Tracking data to monitor and alert on things like failing dashboards and dashboard response times.
Usage Tracking is functionality available within OBIEE that logs every user request to the BI Server into a set of tables stored in the RCU (BIPLATFORM) tables.
Which reports are requiring excessive number of queries on the database (and thus adding load to the BI Server in federating the results)?
Wouldn’t it be useful if our Enterprise Management tool (EM12c) could monitor the rate at which errors were being received by users, and alert us if it goes above a certain rate?


To start with you will create a new Generic Service which is going to be the container for this particular Service Test and any similar ones. On the Service Test page, set Test Type to Oracle SQL Timing (it doesn’t matter that it’s called a “timing” test even though we’re more interested in the rows returned). Specify your RCU database details and credentials, and then paste your SQL statement into the Query area. On the next screen, Performance Metrics, click the radio button next to the default Total Time (ms) and click Delete. Click on the name of your service and under Key Test summary you should see your service test listed. Click on the name of it to see the data it has collected – if you’ve only just created it then most likely there will be no data shown. To validate the service test, generate some failures in OBIEE if you haven’t already (locking the datawarehouse DB account is a quick -if unsubtle- way to do this) and wait for the service test collection interval to come round. The great thing about defining a service test is that it keeps history, so you can track things like error rates over time.
This is using the Usage Tracking RPD that comes with SampleApp v309R2, merged into the existing RPD running on my system. So that wraps up my first post on this subject, demonstrating creating a custom service test to make use of the invaluable Usage Tracking data. Below is a typical start schema with 4 dimension (product,time,channel,region) and a product sales fact table. It can be used for a unified overview of disparate services including servers, databases, and of course OBIEE. Just as you wouldn’t expect to grok OBIEE in an instant and a comprehension of the basics of the BI Server, an RPD, Answers, and so on will aid a good implementation, the same is true for EM12c. These include servers (known as hosts), databases, database listeners, but also components of parent targets. The Status metric mentioned above will have a default Critical Threshold of “Down”, which is how EM12c will raise an alert for a component that is not running. Each target will have its own metrics for which thresholds can be defined, whether this is the OBIEE Presentation Services “Connection Pool Current Authentications” or the deadlock rate in TimesTen. A Service can have one or more Service Tests defined within it, and these can be a variety of functions that return metrics, such as availability or performance data. Both tables reside in the RCU (BIPLATFORM) schema and can be queried just as you would any table in the database. Launch the creation process from the EM12c Setup menu in the top-right, then Add Target and Generic Service. Set the Collection frequency to be however often you want to run this check – but make sure the value you choose matches up with the timespan you specify in your SQL otherwise you’ll miss or double-count errors. Note that whilst the query above brings back details of the failed analysis, the test we’re building is simply looking at the number of rows, so for the sake of brevity our SQL statement could actually just select a single column – it’s the predicate that matters. Now you can set the desired thresholds for your new metric – how many analyses should fail in the time period (eg 30 minutes) should cause a Warning, and how many would be Critical?


As with all new configurations and targets in EM12c, you have to practice a bit of patience for agents and the like to sync up, to hit their collection frequency, and so on.
It should momentarily refresh the screen and show the results, including the number of rows fetched. Next, I’ll be looking at how we can integrate JMeter tests into EM12c for clever reuse of existing code and a simple way of tracking system performance. Monitoring and alerting is core to EM12c, as well as extremely flexible management of any problems that arise. The frequency of a metric collection can be configured, with a different Collection Schedule per Metric. From these metrics, thresholds can be defined just as they are against metric data from a pre-defined target, and thus events and notifications driven.
It’s easy to implement (see here for a step-by-step tutorial from Oracle), and provides a wealth of valuable data including when a report ran, which dashboard it was part of, how long it took, how many rows it returned, and even the query that was sent to the database to run it. They can also be modelled into the OBIEE RPD and reported on through the front end, but that’s a separate topic (have a look at the superb SampleApp v309R2 for inspiration). This, and any other Usage Tracking query you care to craft, can be easily integrated into EM12c through the definition of a Service Test using the Oracle SQL Timing test type. I have defined my Generic Service as being called “OBIEE”, associated with an Exalytics system called EXA01. For the purposes of this type of test it doesn’t matter from where it runs, but other types of testing (including JMeter that I’ll talk about in the next post) it is very useful to be able to define multiple, geographically separated, execution hosts (“Beacons”). If all has gone well you should now see your service listed along with a green arrow under “Key Tests” showing that the service test we just built (the only service test so far, therefore the Key Test by definition) is up. If you are feeling impatient, you can click on Verify Service Test to get to a screen from where you can manually run it (note that clicking this alone doesn’t run the service test yet). EM12c also offers natively all of the control and configuration functionality for OBIEE that exists in its sibling that is installed with all OBIEE installations, Enterprise Manager Fusion Middleware Control. It’s on eDelivery, linked to from here, listed under Oracle VM Templates (x86 64 bit), Part Number B73896-01.
One metric that most targets will provide is Status and this particular metric is collected every minute by default.
For non-Exalytics, just select the FMW domain (bifoundation_domain) of the system you’re monitoring. Other metrics are collected less frequently, from every 15 minutes up to once a day or less.



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