Power Bi Questions

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Please help on below Questions? in power bi service. steps.

1) Access/authorization requests

2) Monitoring of Power BI Datasets/Loads/Performance of Power BI
 3) Evt. Deployment tasks of Datasets to QUA/PRD for Power BI incl. monitoring
 4) Load optimization of Power BI Datasets.
Sep 24, 2020 in Power BI by vnk
• 390 points
103 views

2 answers to this question.

0 votes

Hi, @Vnk

1) Access/authorization requests

You need to get an Azure Active Directory (Azure AD) authentication access token. Your app uses a token to get access to Power BI dashboards, tiles, and reports.

  • The first step to get an access token is to get an authorization code from Azure AD. Construct a query string with the following properties, and redirect to Azure AD.
  • After you construct a query string, you redirect to Azure AD to get an authorization code.
  • Once Azure AD redirects back to your web app with an authorization code, you can use it to get an access token.

2) Monitoring of Power BI Datasets/Loads/Performance of Power BI

Monitoring performance is relevant in the following situations:

  • Your Import data model refresh is slow.
  • Your DirectQuery or Live Connection reports are slow.
  • Your model calculations are slow.

Slow queries or report visuals should be a focal point of continued optimization.

answered Sep 24, 2020 by Gitika
• 65,870 points
0 votes

Hi, @Vnk,

Despite the efficiencies achieved by the VertiPaq storage engine, it is important that you strive to minimize the data that is to be loaded into your models.

  1. Larger model sizes may not be supported by your capacity. Shared capacity can host models up to 1 GB in size, while Premium capacities can host models up to 13 GB in size. 
  2. Smaller model sizes reduce contention for capacity resources, in particular memory. It allows more models to be concurrently loaded for long periods of time, resulting in lower eviction rates.
  3. Smaller models achieve faster data refresh, resulting in lower latency reporting, higher dataset refresh throughput, and less pressure on the source system and capacity resources.
  4. Smaller table row counts can result in faster calculation evaluations, which can deliver better overall query performance.
answered Sep 24, 2020 by Gitika
• 65,870 points

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