Hi,

We were using custom folder names in Qlikview for QVDs(Raw,Trandformed,Custom) and we want to move to QDF deploy tool for Qlik Sense, but it seems that whenever you deploy a new container, the tool copies the init.qvs to all container with a version most probably embedded in the exe. I tried changing the inline in the init.qvs from the template container, but the tool is copying another version.

Any ideas if this copy can be skipped or changed to copy from the template container?

Thanks,

Bogdan

hello guys, what's up,
I need help with how I can compile a new “QlikDeploymentFramework.exe” because I made a change to the standard qvs “12.Index.qvs” and every time I create a container, “QlikDeploymentFramework.exe” undoes my changes in all existing containers.
This also occurs in my “.gitignore” file because I do not enable the “Instals Qvc Lib” option and with that the “.gitignore” is also mortified for what is compiled inside my “QlikDeploymentFramework.exe” version 1.7.4, this mess my whole environment.
So I would like to make changes to these two files and complicate a new “QlikDeploymentFramework.exe”, how is that possible?
Thank you in advance.

Hello we all know that we can use the function LCGV to connect to a container and generate variables for the path of the desired folder...
now we've been using QDF at my company for almost 2 years and the thing is that we cannot know which container connects to which container
is there a way to visualize or to generate kind of dependency list between containers?

things are becoming cumbersome and like spider web if I can say
kindly advise
@Michael_Tarallo 
@Magnus_Berg 
@Damian_Waldron 

I have two QlikView Publisher server with a production and development QDF Framework Root.  I was hoping it is possible to create a Qlik Sense node that has apps and a single lib mount to the development QDF Root and a separate Qlik Sense Server that had a single lib mount to the production QDF Root.   is it possible to segregate nodes for reloading apps?

Hello guys,

I are launching Qlik Sense in our company additionally to QlikView and we are going to have at the beginning only one site on one node. We are 6 people in our developer team and I am looking for a solution how can I design the deployment and development process that enable us to host productive apps and at the same time to develop new one in team work on the same site. Does somebody has the same situation? Are there any deploying best practices? Can we handle this situation with various streams? 

We are planning additional dev site for the future, but at the beginning we have to work on one site.

Thanks in advance!

BR,

Rumen

The next generation BI tools have changed the IT landscape of enterprises with features such as self-service reporting, ease of development and deployment, cloud and big data support. With these rich features and initiatives to modernize IT, there has been surge in adoption and migration to tools such as Qlik and Tableau. The enterprise tools are now focused on automation and reducing IT development and maintenance overheads. And QA, being an integral and critical part of development process, must have clear automation approach supported by tools. The white paper describes a BI QA Automation framework.

Enterprises use BI tools such as SAP BusinessObjects, SAP Crystal Reports, OBIEE, Qlik and Cognos for catering their reporting needs. One of the key factors for successful BI project implementation is the level of trust on the data depicted in reports and dashboards. Lack of trust in data causes attrition in user adoption and often results in project failure.

BI testing is the process of validating the data, format and performance of the reports, subject areas and security aspects of the governing project. Emphasis on a thorough BI Testing is key for improving the quality of the reports and user adoption. However, testing of the BI projects is different from traditional web application testing since the contents of the report is automatically generated by the BI tool based on the tool metadata. The focus of this article is to propose an automated approach to test the report data and its utilization would be a report migration project.

Need for Report QA Automation

Report Data Testing is an important process of assessing the reliability of information visualized on the report. It is required to sustain the trust of the user on the reports because reports are often used as key basis for management decisions and the user assumes that the information on the report is representative of source data.

A typical approach to verify report quality is to verify calculations on the reports themselves to the data in the source report or data warehouse. Thus the BI testing process becomes a manual one, which increases the workload for testers and making it prone to mistakes. Most BI tools manipulate/transform the source data, which makes it even harder to manually test. Manual testing also is a slow and cumbersome approach which compromises the accuracy of the testing.

It needs to be ensured that report data exactly matches with the expected output, as the reports act as a basis to make critical decisions. Having a manual QA process to validate reports has multiple downsides:

• Reports with large data cannot be accurately validated by manual process, and leaves room for potentially uncovered mismatches.
• Huge efforts required for manually validating the report data.

QA Automation Solution Design

As described in the Solution Architecture below the QA automation is done in following steps:

1. 1. Qlik report extracts are generated by exporting the report contents
2. 2. Based on the dimensions and measures identified by the automation utility, code Generator generates the Qlik script file to validate Qlik report data. The Qlik script test engine (an automated process to run the generated script) compared the Qlik data against Gold dump / Legacy BI report extracts and logs the differences in the test log on a database.
3. 3. Gold dumps of expected report content are acquired from business user or by connecting to the legacy BI system which is to be migrated to Qlik.

Fig 1: QA Automation Solution Architecture

1. Legacy BI Report Data Extractor – Automated extract of data from  Legacy BI Report data based on gold dump is pulled in Excel or CSV format and stored at the Extract Repository, as shown in the above figure.
2. Qlik Data extractor – Automated extract of data from migrated Qlik report based on gold dump same as that of the Legacy BI Report is pulled in Excel or CSV format and stored at the Extract Repository.

3. Qlik Code Generator – It is the module developed as an independent tool where user identifies the dimensions or primary fields by which the rows are identified uniquely and the measure fields whose data is to be compared. The Dimension and Measure fields are placed in a Database source system. Once the Dimensions and measures are known to the system, the Qlik Code generator engine initiates and generates the QlikView script to populate the Qlik report with data discrepancies and save it in a Qlik script file.
4. Test Engine – Once the code is generated the user have option to run the Test Engine which will push the code to a Qlik interpretable QVS file on the Qlik Server and initiate the Qlik data comparison report load. On completion of the Qlik Load, the test result will be generated and displayed with option to export it into excel and preserve the result for future reference. The test result will provide the summary of the data discrepancies and the detailed view will highlight the missing data and data mismatches in red background. 

Generated Code Template

QA Automation Report

Fig 3: Report Output

The above figure is the snapshot of the test engine output where the “Comparison Summary” provides the count of Total mismatched data points and mismatch count by Measure. Also depicts count of data points which are present in either source or target.

The Detailed view highlights the mismatched data points in RED background. The column of interest here is “Table” from which one can identify to which source this data row belongs to i.e. in our case OLTP data means transaction data from SAP Crystal Reports and OLAP means Dimensional data from Qlik.

Benefit of ’s BI QA Automation Approach

As per the  Analyst Firm Gartner- “The average organization loses $14.4 million dollars annually through poor data quality.” 

• ’s automated approach saves a substantial amount of effort and time with enhanced accuracy
• To the organization which would adopt our approach will be benefited in terms of reduced project cost due to less number of testers and also reduced technical skills of the testers.
• A good automated BI report testing tool is also characterized by its user friendliness, which designed utility totally complements, so that even a non-technical user can also use it.
• Light weight and ease to configure are other features which makes the  BI QA automation solution a desired utility by any user.

Conclusion

Automated BI report Data Quality Analysis approach is a full-proof automated solution to the challenges faced by the Quality Analysts while performing data matches in the environments like report migration from one BI tool to another. It has multiple file format support feature and based on the pre requisite that the data is freeze at same point for both the reporting tools. The observation is that it reduces the testing effort by around 80 percent with reduced number of resources and lesser technically skilled. So it ensures that the trust on the reports is enhanced by reducing the efforts.

Hello
I've been working with the QDF for more than one year now...

currently I have a qlik sense application with so many variables defined
Today I need to do so many updates on these variables and as you already know the variables editor in Qlik is annoying
is there a way using QDF functionalities to export the variables to a CSV file and then load them using the function I mentioned in the subject?
Actually I managed to export the variables using the Document Analyzer to an excel file which then I saved as CSV file but the function failed to import them successfully because when I saved them to CSV the delimiter is ";" semi-column

kindly advise 

I have Open Hub BW Object as DataSource to feed a report in QlikView. I have done some research about how to establish the connection with this type of object and found no proper solution.  Have you tried it ?

Thanks !

BWPerson

I'm currently looking at sample applications in QDF. One of them - NorthWindExampleMart.qvw - breaks on load with error

Ошибка в строке скрипта:
for vL.tttt = 0 to vL.xxxx-1 

Oшибка в строке скрипта: stands for something like Error in script line:

Firstly I've checked that I generated QVDS by QVD-Generator-Example.qvw and loaded successfully Example_NorthWind_Mart.qvw datamart. Then I tried to debug this error, unsuccessfully.

Finally I've noticed some irregularity in NorthWind_Mart.qvw on table view:

All tables have names corresponding to they source QVD file names, but instead of Customer table we have vL.temp_table.

I've added

RENAME TABLE vL.temp_table TO Customer 

at the end of Example_NorthWind_Mart.gvw script and after that NorthWindExampleMart.qvw application loads successfully for me.

If somebody stumbled upon same error, that may be quick workaround.

Best regards, Vadim Tsushko

Hi everyone,

We have very recently started using the QDF, and I have encountered an issue. In one of our extraction apps, there is one table that is for some reason seen as vL.temp_table. All the fields are qualified and start with 'vL.temp_table.', and the table gets stored as vL.temp_table.

Now the strange thing is that this happens to the second table extracted from the system. I can probably solve this problem by naming the table during the extraction statement, but I'm just wondering why this is happening? The vL.temp_table is dropped during initialisation, so I don't understand how it could interfere with the rest of the script at all? I am mostly curious because I don't want to run into similar issues in the future without noticing.

I don't think I can post the exact script but it goes as follows:

<Set system variables>

<Include InitLink.qvs>

<Connect to database>

Qualify *;

SELECT*
FROM <table>;
Repeat for about 15 tables

<Loop to store tables>

<Loop to drop tables>

Thanks for any help provided!

Hi,

I have created new QDF envirnment to use in Qlikview, but for some reason my QV app won't find other containers if it is located in subfolder. For example my QDF might look like this 4.test/1. Testi and 4.Test/2.Testi and if I call 2.Testi in container 1.Testi using CALL LoadContainerGlobalVariables it gives base path missing. If I create new container right in Root (5.Test) I can call other containers and it works just fine. I have tried creating new QDF and same happens in there. Also container maps in all folders are correct and updating if I do something. Below is image of my QDF if that helps explaining what I mean.

Br,

Henri

I was upgrading from a Qlik Sense Free Trial to Paid version. I recieved a welcome email that needed to be activated...once activated an error message "You have met the allowable number of tenants you can create. To manage your license, contact Qlik Sales." is there any way to resolve this today without waiting for someone from sales to get back to me tomorrow? 

Qlik Deployment Framework 1.7.4 is released on github, this version includes:

• New function ETLLogEntry and WriteETLLog that creates an ETL log as a table and writes this log to disk when needed (15.ETLLogEntry.qvs) /thx Rod Stewart
• Updated Variable Editor to work in later QlikView releases, but Variable Editor application might not work well on QlikView 12.3 and later due to macro execution issues. Recommendation is to use Deploy Tool instead
• Added MIT license in containers
• Other minor bug fixes

https://github.com/QlikDeploymentFramework/Qlik-Deployment-Framework/releases/tag/1.7.4