Gain valuable insights into your ‘Project Repository’ with TX Dictionary Project
The purpose of the TXDictionary project is to provide visibility into your project repository Meta Data across one or many projects. The TXDictionary project was designed to assist developers, data architects and Business users to gain insights into their Discovery Hub projects.
It includes a Discovery Hub project designed to take advantage of the multi-layer platform, connection to a project repository, data consolidation, transformation and cleansing in the Data Staging Area, and a robust reportable data warehouse in the MDW. The TXDictionary project is a great example of leveraging the power Discovery Hub® to simplify a very complex relational data model into a Dimensional Data Warehouse. It also includes a Qlik Model, Qlik application and several Qlik dashboards which provide easy visibility into all your projects in a given repository.
Current list of tables and fields within the project can be found in the attached file: DataDictionary.xls
The following is a sample table contained in the DataDictionary.xls
Dashboards included in Qlik Application created in TX Dictionary project
The Qlik dashboards provide easy access and reporting on one or many projects within your repository. There are 4 Dashboards included as part of the ‘TX Dictionary’ project ‘TX Dictionary’, ‘Execution Time’, ‘Failed Executions’, and ‘Data Quality’.
TX Dictionary Dashboard
The TX Dictionary dashboard allows users to browse one or many projects to understand project data sources, databases, table and query information, all data fields including data types, transformations, the source or sources of each field and the population methods. You may filter this information by project, database type, database, container, or by field. This allows users to really zoom into vital project information at any desired level.
The following is a snapshot of the Dashboard:
Execution Time Dashboard
The Execution Time dashboard provides valuable insight into Execution package information within 1 or many projects. Monitor execution packages, schedules, execution steps and average execution time by table. Filter executions by project, scheduled package, and step type.
The following is a snapshot of the Execution Dashboard:
Failed Executions Dashboard
The failed executions dashboard is a companion of the execution dashboard with emphasis on understanding the status of each execution. Users can view all execution packages post execution along with start and end time information, execution steps, status, total execution time and Execution message log information. Filter executions by project, scheduled package, execution package and execution status.
The following is a snapshot of the Failed Executions Dashboard:
Data Quality Dashboard
The data quality dashboard gives users a graphical bar chart depicting the amount of good, warning and error information for each table within a project(s). Filters can be applied by project, data quality status and by table.
The following is a snapshot of the Data Quality Dashboard:
Download and Initializing the TX Dictionary Project
Download the TX Dictionary Project from the Cube Store
Once imported Select ‘Yes’ to run the Connection Manager
Create a ODX database
Connect to an Existing Project Repository and ‘Test Connection’
Create a MDW database
Create a DSA database
Once complete ‘Test Connections’ and validate the Connection States are all Green
Deploy and Execute the Project
Setting Up Qlik Applications and Initializing Dashboards
Copy ‘TX Dictionary.qvf’ file into your Qlik Apps folder
Create QlikSense App from Discovery Hub
This should create the connection script required to connect QlikSense or QlikView to the Discovery Hub Qlik views
QlikSense
If this does not create the ‘MDW’ connection in QlikSense automatically then you need to manually create a ‘MDW’ connection in QlikSense that points to the correct MDW database in Discovery Hub
QlikView
Deploy QlikView script to a text file, make sure you choose QlikView syntax.
Use the include statement in Qlikview to point to the Qlik script file
Load data in Qlik to ensure connectivity
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