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Linking Dashboards and Reports in BOE Dashboard Builder

Posted by Hemanta Banerjee on January 13, 2011

One of the common requests I have found on the BOB board relates to how can we link WEBI/CR reports with XCelsius dashboards. The common scenario is where we are showing some summary information in an XCelsius dashboard and I want to show some related detailed report using WEBI or CR on the same dashboard.

In BusinessObjects Enterprise XI 3.1, Edge XI 3.1 and Crystal Reports Server 2008 v1, the new Interportlet Communication (IPC) feature in Dashboard Builder allows the transfer of information between distinct analytics. Now you can pass parameters from an Xcelsius dashboard to another XCelsius dashboard or to Crystal Reports and Web Intelligence. Using this framework, I will show 2 simple ways to link between:

  1. Two XCelsius dashboards
  2. Between an XCelsius dashboard and Web Intelligence/Crystal Reports

XCelsius to XCelsius linking

An XCelsius dashboard used as a source document has to be configured with a Portal Provider Connection. The target analytic also has to be configured with the Portal Consumer Connection. We will send parameter data between two analytics with the use of a simple example: sending information from a list box selector in one analytic to drive a chart in another dashboard. The steps are

Create the provider analytic

1. Create the list box control for the years: As you can see below I have created a simple list box control with the years.


The selected item from the list box is placed in cell B2 in my example (marked in yellow). I have also set the size of the canvas to fit the component.

2. Create a new portal data connection as shown below.


Choose provider as the Connection Type and give a name to the range (in my example Year). Since we are passing a single cell of data, select Cell  as the range type and the cell B2 which is the target of the list box selection. Also go to the usage tab and instruct the data connection to communicate with the consumers when the value in the target cell (B2) changes.


This will ensure that whenever the user makes any selection on the list box, the label will be passed to the target/consumer of the portal connection.

Create the target analytic

1. In the target dashboard I have created a simple dashboard where I have a chart combo box.


In the properties of the combo box I have set the combo to read the current selection from a cell. When the selection in the cell changes it will read the row of the data corresponding to the selected year and place it in the target row which drives the chart.

2. Define the portal data connection of type consumer as shown below.


Keep in mind that the Range name has to be the same for both the provider and the consumer. Also since the provider is going to pass a single cell I have selected the range type as Cell and have it update cell B2 which drives my drop down and chart.

Combine them in the dashboard

Now log on to InfoView and create a new Corporate Dashboard. Drag your “Provider” and “Consumer” analytics onto the dashboard. Also activate “Content Linking”.  This can be done by setting the properties of the Provider analytic. Choose the Provider analytic as the “Source Analytics”, and Consumer as the “Target Analytics” as shown below.


XCelsius to WEBI/CR linking

An XCelsius dashboard used as a source document for Crystal Reports and Web Intelligence has to be configured with the FS Command connectivity. The parameters are then assembled in an OpenDocument URL by the Dashboard Builder framework. For more information about the OpenDocument syntax, see the documentation:

To illustrate this example I have a summary report in XCelsius and use WEBI to show the detailed month wise breakdown.

Create the provider analytic

The steps to create the provider are the same. In fact I have used the same analytic that I used in the previous example. The only difference is that since the dashboard builder framework uses the OpenDoc URL format to pass the parameters I need to massage the parameter so that it can sent to WEBI as shown below.


In cell D2, I take the selection from B2 and use excel formula (="&lsSYear="&B2) to create the parameter for the data connection.

Now go to the data connections and add a new FS Data connection as shown below.


The trigger also has to be set in the usage tab, so that the data connection sends the new value whenever the value in the cell D2 changes.


Now export this to SWF and save it in the infoview portal.

Create the WEBI Report

The steps to create the WEBI Report is fairly simple. As shown below I have created a simple WEBI report which takes in the year as the prompt.


The only thing to keep in mind is the name of the prompt should correspond to the formula set in the provider analytic. For example in my case the open doc param formula in the provider analytics is ="&lsSYear="&B2 which corresponds to the Year prompt in WEBI.

Save WEBI report in the infoview portal and test the content linking as shown earlier.

If you want more details you can check out the user guides at

OpenDocument User Guide: http://help.sap.com/businessobject/product_guides/boexir31/en/xi3-1_url_reporting_opendocument_en.pdf
Dashboard Builder User Guide: http://help.sap.com/businessobject/product_guides/boexir31SP3/en/xi31_sp3_dashboard_user_en.pdf

Posted in BusinessObjects, Dashboard, WEBI, XCelsius | Tagged: , , | 4 Comments »

Creating live dashboards using QAAWS

Posted by Hemanta Banerjee on January 7, 2011

Happy new year to everyone. As the first post for the year I wanted to put something that was simple and common. In the last couple of months I have run into several scenarios of customers asking me the best mechanism to create live dashboards in XCelsius. As you know the only way to create live dashboards in XCelsius is by using Web Services. While you can create web services on your own the hard way, with the BOE platform there is a very nifty utility called Query As A Web Service (QAAWS) which allows you to create web services very easily from the universe.

QAAWS is a web service generator. It uses the query builder to essentially to build a query and publish the query to the platform and makes it available as a web service. Here is how you can use it.

Create the Query and Publish to the platform

1. Launch QAAWS and create a new query. Give it a name that is user friendly.


2. You can set additional parameters such as authentication mode and timeout at this stage. Usually we would keep them as default.


3. As you can see in the steps the next step is to select a universe. Based on your security setting you will be presented with a list of universes that you can use for building the query. The process of selecting the universe and building the query is the same as you would do when using WEBI.


In my example I have purposefully chosen a query which has a prompted filter. I can drive this prompt using a drop down box or other selectors from the dashboard.


As you can see my query has 1 input parameter and 4 output parameters. Now all I need to do it click on the publish button to publish the webservice to the platform.


The URL shown above is the URL for the webservice and I can use this in XCelsius to build my dashboard.

Using the Query in XCelsius

In the data connections dialog of XCelsius you can add a new live office connection. Here you need to enter the URL that we got from QAAWS.


We also need to bind the cells to both the input and output parameters. For the input parameter I have bound it to cell C3 of the spreadsheet as shown below.


The same way you need to bound the output to your spreadsheet. The only thing to keep in mind is that if your query will return multiple rows of data you would need to select a range of cells bigger than the maximum possible range as shown below.


For debugging purposes you can also get the number of rows returned by the query and bind it to a cell as shown below.


And after all of this voila you have a live dashboard…


Posted in Dashboard, QAAWS, WEBI, XCelsius | Tagged: , , | 6 Comments »

Migrating from development to production in BOE (Lifecycle manager)

Posted by Hemanta Banerjee on December 8, 2010

One of the cool new features in BOE XI 3.1 is the new lifecycle manager (LCM) module. Migrating reports and other objects from development to production has been a challenge in all of my previous implementations and I am happy that BusinessObjects provides some out of the box functionality to make this process really simple. When using LCM for migration you create jobs. Once a job is created it can be used several times to promote content from one deployment to another.

Please note that LCM is a separate installation and requires the following Services:

  1. Central Management Server: LCM job itself is an object which is saved in CMC.
  2. Adaptive Processing Server: The LCM job server is added to the Adaptive processing server
  3. Web Application Server: LCM is a web application
  4. Input FRS : This is a server you need available after installing, as jobs that you create in LCM are saved in the Input FRS and CMS repository.
Administrative Settings

Access to the LCM application is set by managing the security for the application in CMC as shown below.


Also before creating new jobs you need to add the source and target BOE systems in the LCM application using the administration options shown below.


Creating the LCM Job

To migrate objects, you have to first have to specify which content you want to promote. This is done in LCM tool with 3 main steps:

1. Create a Job: A job is collection of objects that can be moved from one BOE environment to another.

When you create a new job you must logon to the source system and an Input FRS should be running and enabled as the Job is saved as an Object in the CMS database and as a file in the Input FRS.


In the example above I am migrating objects from my BOE environment as the source to a BIAR file.

2. Add Objects: Add the required objects from the CMS repository that should be migrated. In this example I am migrating all the reports related to the sales and finance department.


3. Add the dependent objects : Objects such as universes, connections, images and other dependencies on which the primary objects depend on also have to be added to the job. LCM will automatically compute the dependents when you click on “Manage Dependencies”.


And now all the objects and their dependents are selected in the job as shown below.


Now my job is ready for the next step which is promotion. You can promote content when deployments are connected and also when they are isolated. When deployments are connected you can directly migrate to the destination. When they are isolated you use a LCMBIAR file to transport the content.

Promoting to target

But before promoting you need to set a bunch of options.


1. Map Connections: You need to map all the universe, QWAAS URL and Crystal report database connection mappings to the target.


2. Schedule: To set how often the job should run.


3. Security: You can specify to promote the security of the objects in the job as a best practice only promote security when changes have been made, typically with a significant revision of the application.

4. Test: As the last step you can test what would happen when promoting the job, without committing the objects to destination

To promote a job you can schedule it or you can run it manually. The figure below shows the 2 scenarios of connected and isolated environments.

Posted in Administration, BusinessObjects, LCM | Tagged: , , , , | 3 Comments »

BOE Universe: Generating list of values based on data

Posted by Hemanta Banerjee on November 19, 2010

Let us take a simple scenario. Let us say we have a countries dimension which has all the countries. If we want to use this dimension table to get a list of countries where we have customers, as well as use it to get a list of countries where we have offices we can create 2 aliases COUNTRY_OFFICE and COUNTRY_CUSTOMER and create objects from the aliases. No issues till now, except if we try to get a list of countries where we have offices. Since we have used the master country table it will list all the countries irrespective of whether we have office there or not.

Let us see how it works below.


In the example above I have a country table and I use it for both client and showroom country. Now if I query for showroom country i.e. countries where I have showrooms here is the query produced.


As you can see it lists all the countries in the countries table which is not what we wanted. In order to get the correct list of countries I have to join with the SHOWROOM table so that the countries list is restricted based on the SHOWROOM dimension table. This is done by specifying that whenever the Showroom Country object is used in a query, the Showroom table must also be inferred in the FROM clause of the SELECT statement. Providing that the Showroom_Country table is joined to the Showroom table the object is then guaranteed to only return countries in which showrooms exist.


Making this change ensures that we always get the correct set of countries when we query for showroom countries.


While this does not seem that critical it becomes very important especially when we want the user to select the showroom country in a prompt for example. We only want those countries to be in the prompt list where we have showrooms and making this change will ensure that we always get the correct list.

Posted in BusinessObjects, Universe, WEBI | Tagged: , | Leave a Comment »

Outer Joins in Universe (BusinessObjects)

Posted by Hemanta Banerjee on November 15, 2010

Lets take a simple scenario. I want to generate a report that shows the sales by showroom, and the report should display all the showrooms in the report. For the showroom with no sales it should display the region with a NULL value for sales.


The usual join (also called as inner join) will not work in this scenario. We need what is called as an outer join. If you want to know more about outer joins you can checkout the Wikipedia link here.

To enable outer join you need to first set the ANSI92 parameter to Yes. This will change the query from the simple join to an an inner join syntax with from clause as shown below.


You can also enable the FILTER_IN_FROM parameter. This pushes the where clause of the join inside the from which reduces the number of records in the join condition and will greatly improve performance.


Now we can setup our outer join. As shown below we can setup the right outer join betwen the fact table and the showroom dimension table.


The effect of this is that all showrooms irrespective of whether they had a sale or not will be returned by the query.


So in conclusion while it is easy to setup outer joins in the universe, one should be very careful when using outer joins as it can result in a cartesian product of all rows especially when using full outer join.

Posted in BusinessObjects, Universe | Tagged: , , , | 1 Comment »

Is it my time yet ?

Posted by Hemanta Banerjee on November 11, 2010

Over the last couple of weeks I have came across several posts in the BOB Board that revolve around time based analysis. Since the questions seem keep repeating it makes it an ideal candidate for a blog posting. Most of the analysis that I run into involve either analysis the most current data i.e. current day, current week, or current month. In fact most of the standard reports are probably built with that as the default selection parameter. And also in most of the cases this data is being compared with some other period like either last quarter or last year.

In my previous posts I have covered 2 very key topics

  • Period to date analysis – Examples would be YTD or MTD type of analysis which I have covered here
  • Prior Period Analysis – Covered here.

In this post I will cover how to make date selections easier for users, especially in scenarios where they want to analyse the most recent period. You might ask why all of this work when I can select dates using the filter criteria in WEBI. The answer is usability. As you can see below it is much simpler to select “Current Year” or “Last Week” from the prompt selection rather than having to go through a set of dates.


So how can we design something like this. It is quite simple actually. First off I define a derived table with the set of pre-defined date ranges that I want to make available for the users.


The code for the derived table is actually quite simple. For example in my case I have used the MAX function to determine the current date based on the dates in the dimension table.

Select 3 AS ITEM_INDEX, ‘Last Week’ as DATE_RANGE, dateadd(dd,-7, max(DATE)) as DATE_RANGE_MIN, max(DATE) as DATE_RANGE_MAX from DATES_TABLE
Select 4 AS ITEM_INDEX,’Current Month’ as DATE_RANGE, cast(CAST(datepart(yyyy,max(DATE)) as varchar(10)) + ‘-‘ + CAST(datepart(mm,max(DATE)) as varchar(10)) + ‘-01’ as DATETIME) as DATE_RANGE_MIN, max(DATE) as DATE_RANGE_MAX from DATES_TABLE
Select 5 AS ITEM_INDEX,’Current Year’ as DATE_RANGE, cast(CAST(datepart(yyyy,max(DATE)) as varchar(10)) + ‘-01-01’ as DATETIME) as DATE_RANGE_MIN, max(DATES_TABLE.DATE) as DATE_RANGE_MAX from DATES_TABLE
Select 6 AS ITEM_INDEX,’Current Qtr’ as DATE_RANGE, ‘DATE_RANGE_MIN’ =
        when datepart(qq,max(DATES_TABLE.DATE)) = 1 then cast(cast(datepart(yyyy,max(DATES_TABLE.DATE)) as varchar(10))+ ‘-01-01’ as datetime)
        when datepart(qq,max(DATES_TABLE.DATE)) = 2 then cast(cast(datepart(yyyy,max(DATES_TABLE.DATE)) as varchar(10))+ ‘-04-01’ as datetime)
        when datepart(qq,max(DATES_TABLE.DATE)) = 3 then cast(cast(datepart(yyyy,max(DATES_TABLE.DATE)) as varchar(10))+ ‘-07-01’ as datetime)
        When datepart(qq,max(DATES_TABLE.DATE)) = 4 then cast(cast(datepart(yyyy,max(DATES_TABLE.DATE)) as varchar(10))+ ‘-10-01’ as datetime)
        else cast(‘1900-01-01’ as datetime)

My code assumes that the dates dimension table is updated and contains only the valid dates. If that’s not the case then you would need to use either a system function like GetDate() to get the current date or use some form of control table for the current date information. This has been explained quite well by Dave in his blog.

This derived table has been joined to the fact table using a between clause as shown below.


I also need to define the contexts to resolve the loops created by the joins.


Now we are ready to add the "DATE_RANGE” column to the universe. In my specific example I have defined the object as a hidden object in the universe and defined a filter called DATE_RANGE with a @prompt as shown below. This is to make it easy to use. I do not want to clutter up the time hierarchy with unnecessary objects. However I want to give the flexibility to the users to easily pick a date range for their analysis.


DATE_RANGE.DATE_RANGE = case when @Prompt(‘Select Date Range for Analysis:’,’A’,’Date Range\Date Range’,mono,free) = ‘*’ then ‘All Days’ else @Prompt(‘Select Date Range for Analysis:’,’A’,’Date Range\Date Range’,mono,free) end

The prompt condition allows the user to either pick ‘*’ meaning all dates, or pick some other date range for analysis. Using the approach above ensures that during adhoc analysis the user has to drag the date range to the query filter and they will be prompted with a set of pre-defined filter conditions to restrict the data.


I have also gone ahead and defined another condition object called “Custom Date Range” that shows the calendar to the user and allows the user to pick any date range from a standard calendar. The custom date range prompts the user for a start and end date and filters the data based on the user selection.


DATES_TABLE.DATE >= @Prompt(‘Select Start date:’,’D’,’Period\Date’,Mono,free,not_persistent,{‘2001/01/01’}) AND DATES_TABLE.DATE <= @Prompt(‘Select End date:’,’D’,’Period\Date’,Mono,free,not_persistent)

So in summary using some of the techniques given here as well in the other posts around time slicing, you can implement quite sophisticated and flexible time based analysis. To access the other articles in the series click on the links below.

  • Period to date analysis – Examples would be YTD or MTD type of analysis which I have covered here
  • Prior Period Analysis – Covered here.

Posted in BusinessObjects, Prior Period, Time Sliced | Tagged: , , , , , | Leave a Comment »

Managing performance by using Aggregate tables in the universe

Posted by Hemanta Banerjee on November 9, 2010

In most large data warehouses one of the common strategies employed by DBA’s to speed up performance is to use aggregate tables. Generally aggregate tables contain information that has a coarser granularity than the detail data. For example in a retail datamart I might have information at the transaction level. However most of the analysis will be performed at the daily level by brand. Without aggregate tables the database will fetch the lowest level of data and will perform a group by at the day level for specific brands which can be a very expensive operation. Instead as part of the ETL process I can pre-aggregate the data at the daily level which would reduce the number of rows by a huge factor. The Sales_Receipts fact table would contain this detail data, but the records in that table might also be aggregated over various time periods to produce a set of aggregate tables (Sales_Daily, Sales_Monthly, and so on).

There are multiple ways of managing aggregates. One option is to create aggregate tables in the database as materialized views and let the query optimizer of the database handle the performance using seamless query rewrite. I will describe this in a separate post. In this post I will focus on using the aggregate awareness functionality of the universe.

My sample database tracks the sales of cars. My detailed fact table VW_SALE_MODEL is used to track the sales at the lowest level of detail i.e. client, showroom, model and color.


Using these I can create a family of aggregate fact tables. For example I have created a aggregate table called VW_SALE that aggregates the data at the client and showroom level. Similarly I can create additional aggregates at the year level.


Once I have create the aggregates I need to map them into the universe which is a 4 step process.

1. Add the aggregate tables and setup the joins with the dimension tables. I have not created standalone aggregate tables since I want to make sure that I can leverage the hierarchies defined in the dimension tables. This process is similar to adding any fact table in the universe.


2. Define the aggregated measures using the @aggregate_aware function. The @aggregate_aware function is used to setup aggregate awareness in the universe.

The syntax of the @Aggregate_Aware function is @Aggregate_Aware(sum(agg_table_1), sum(agg_table 2) …., sum(agg_table_n)) in the order of preference. For example agg_table1 should be the highest level aggregate, followed by agg_table 2 and so on. This is used by the universe to pick the best aggregate table to answer the query.


In my example I have stated that either try to get the sales total from the aggregate table or get it by calculating it using the detailed table.

3. Define the incompatibilities. For example in my structure the model and maker classes are not captured by the aggregate. Also the aggregate table only contains information about sales and not about the quantity sold. We need to define these incompatibilities so that when the user generates a query, the universe can quickly scan through the compatibility list to determine the best aggregate that can be used to answer the query.


When I define it as shown above all queries that include Model or Maker will go to the detailed table. All other queries will be satisfied by the aggregate table.

4. Resolve any loops. Since I have joined the dimension tables to both the fact I have created some loops in the universe which I need to resolve. I can do that by creating separate contexts for the aggregate fact and the detailed facts.

Now I am ready to using my aggregates. To illustrate let us go to WEBI and see the impact of our design. When I query for sales by showroom the entire query is answered by the aggregate table.


As soon as I add the maker to the query BO now retrieves the data from the detailed table instead.


The same approach can be used to capture additional aggregates such as Year level or Qtr level and BO will dynamically go from using the summary table to using the detailed table as the user is performing the drill down.

So in summary, aggregate tables are very powerful and necessary in most real implementations and BO provides a fairly simple way to model it within the universe.

Posted in Aggregate Awareness, BusinessObjects, Universe | Tagged: , , , | Leave a Comment »

WEBI – How to display “Others” in country field based on Rank

Posted by Hemanta Banerjee on November 8, 2010

One of the frequent questions I come across is – I want to view the top 5, however I want everything else that is not in the top 5 to be placed in 1 bucket called others. I ran into the same question on the BOB board today and since it was simple enough here comes the solution.

Getting the rank within WEBI is quite simple using the RANK function. The syntax for the function is RANK(measure name; dimension name; top|bottom). For example of I wanted to find out the rank by sales I could define RANK([Sales Revenue], [City], top).

In order to make my life easier I have defined variable called Rank as shown below.


I can use that in a report filter to get only the top 3 regions by Sales Revenue.


Now to display all other regions I will use the WEBI function NOFILTER. This will return the total sales across all the regions irrespective of the filter. Using the formula below I can get the sales for all the regions that are not in top 3.


By placing this in the footer of the table I can get the report to show the sales for others.


Posted in BusinessObjects, WEBI | Tagged: , , | 2 Comments »

Auditing III: How to enable auditing for Crystal Reports and WEBI viewing

Posted by Hemanta Banerjee on November 4, 2010

A couple of weeks back I had written an article on enabling auditing in BOE. The same functionality is available in Crystal Reports server as well. However I had missed out what activities can be audited. So writing this post to complete my previous posting. Below are the most of the common scenarios that the administrators want to audit.

Crystal Reports Cache Server: Viewing of Crystal reports is audited by Crystal Cache Server.


Crystal Reports Jobs: Can be turned on by enabling auditing for Crystal reports job server.


Destination Job Server: Will audit all jobs that output to emails, ftp, and file system.


Event Server: Audits all events that are registered on the BOE or Crystal Reports server.


Publication Job Server: Will audit all publication jobs.


WEB Intelligence: Audits access to all WEBI reports.


For steps on how to turn on auditing and how to look at audit data you can go to my previous posts on the same topic.

Auditing I: How to enable audits logging in BOE XI 3.1 

Auditing II: How to import the auditing reports in BOE

Posted in Administration, Audit, BusinessObjects | Tagged: , , , , , | 1 Comment »

How to do Year Ago or Prior period type comparison in WEBI

Posted by Hemanta Banerjee on November 3, 2010

Again a post inspired by the BOBJ board which talks about a generic requirement whereby making it easy for adhoc users to perform relative time period based analysis as easy as possible. The users should be able to select the date using a prompt or otherwise and ask for values for either the selected period or some other reference period such as Current Year Last Week or Prior Year by simply selecting a different measures named as such from the Universe.

This is actually quite simple once you get around to designing it. All we need to do is make sure we run multiple queries once for each time period and then join the queries at runtime in the BI Server. WEBI provides such functionality in the form of contexts. For example if we define the current period and YAGO (year ago) in 2 separate contexts, then when we pull Sales and YAGO sales in the same report BI Server will automatically run 2 queries and join the results. That’s what I want to leverage.

My example shows how to setup 2 measures, Sales and YAGO Sales. However this can be done for any number of measures as well as any number of reference periods as the process is quite simple. So here is what I have done.

1. For each relative time period we need to define an alias of the fact table in the universe. For example I need current period and YAGO therefore I have 2 fact tables – Sales and YAGO Sales.


2. It is also very important to have a proper dates/calendar table that you can use for your time based calculations. In my schema it is the DATES_TABLE with a structure as shown below.


3. Now join the 2 facts to the dates table. The main fact table for current period will be joined normally to the dates table, however the YAGO sales will be joined to the dates table with a lag.

image image


Ofcourse you would also need to define all the other joins between the YAGO_SALES fact and the other dimension tables for completeness. Now that the 2 join conditions have been defined as you can define the measures from each of these tables. When user say runs the query for October 2010 then Sales revenue will be the value for Oct-2010, however YAGO will be Oct-2009 since YAGO sales will join with the date table with a 1 year lag due to our join condition.


Now in order to force the 2 queries we need to define the contexts – 1 for each fact table. This will resolve the loops as well as force the BI Server to issue 2 separate queries to the database.


Now in the query as will see the BI Server will issue 2 queries one for each context and combine them in the result set.


The beauty of this approach is that it is automatically level based. If the user selects a date in the prompt the results will be for same date last year, for month it will be same month LY, for Qtr will be same Qtr last year and for year will be last full year.

You can use the same mechanism to define last week or last month.

Posted in BusinessObjects, Prior Period, WEBI | Tagged: , , , , , , , | 2 Comments »

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