Integrating External Data into DataMiner Dashboards

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Hi Dojo,

I am looking to integrate external data containing Device name, timestamps and polled value results into DataMiner and visualize this data using Dashboard graph.

Could you please advise on the recommended approach to achieve this? Specifically:

  • Are there any preferred or required file formats for importing external data? Eg:Json, CSV or xlsx?
  • Do I need to create any specific elements to manage this data?

Any guidance or references to relevant documentation would be greatly appreciated.

Thank you.

Miguel Obregon [SLC] [DevOps Catalyst] Answered question

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Hi Aswiny,

Depending on the nature of the external source, an ad hoc GQI might be a suitable option in this case. Please see the documentation here:

Ad hoc data sources | DataMiner Docs

Either format is possible; however, text-based files will be easier to integrate than binary types like MS-Excel. I would say, if you can control the output of the external source, CSV and JSON are preferred.
Consider implementing mechanisms that filter, and update based on the size and frequency of changes from the external source.

Gelber Mahecha [SLC] [DevOps Enabler] Posted new comment
Ashwiny J K Anandan [DevOps Advocate] commented

Hi Gelber,

Thanks for the response and the documentation.

Kindly advise with GQI fetching the data from external file source, is it possible to generate graphs for certain time range: daily, weekly, monthly?
Gelber Mahecha [SLC] [DevOps Enabler] commented

Hi Ashwiny,

Yes, the GQI could provide data for use by other graphics components. If you want to add time range filtering, it is a matter of adding an input argument so that the response will be constrained within the time frame.
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Hi Aswiny,

As a follow-up to Gelber’s proposal, I suggest starting by clearly defining your requirements. This will help determine the most suitable approach. Below some points to consider:

  1. Will you perform filtering, sorting, or aggregation on the external data?
    The larger the data set that you plan to process, the larger the time that GQI will take to return the result in a line chart. I see that you plan to visualize monthly data in a line chart, depending on the granularity of your data set, visualizing this information in a line chart could significantly impact performance. Worst case scenario, there will be a timeout.
  2. Do you plan to integrate this external data source with others?
    For example, perform an inner join between two or more external data sources will cause extra processing.
  3. How many concurrent users will access your dashboard/LCA?
    Keep in mind that each user opening a dashboard will execute the adhoc data source. While caching can mitigate this, it adds complexity to the solution.

Based on thee points, you could decide if adhoc data source is sufficient. If none of these conditions pose a significant risk, the adhoc approach may work well. Otherwise, it’s worth considering the connector approach for better performance and scalability.

Hope it helps.

Miguel Obregon [SLC] [DevOps Catalyst] Answered question