Data Query in Power BI - Part 1
DataQuery - We are using this to connect data in Power BI. For those areas, where we have limitations to import the entire data in our Power BI file i.e. .pbix, we are using DataQuery there. On the runtime, DataQuery connect the source data, run the query model on the source data, and it display those in our Power BI dashboard in visual format.
Let's see what are the data sources supported by DataQuery. Following are the data sources supported by Power BI. While using DataQuery and publish, Power BI Service still creates the dataset (like import), however no data will be save there. Only query parameter with other information will be store which will run on source data.
Why we are using DataQuery? For what circumstances we need to use this feature in Power BI? Following are some areas where we have to sue this.
Let's see what are the data sources supported by DataQuery. Following are the data sources supported by Power BI. While using DataQuery and publish, Power BI Service still creates the dataset (like import), however no data will be save there. Only query parameter with other information will be store which will run on source data.
- Amazon Redshift
- Azure HDInsight Spark (Beta)
- Azure SQL Database
- Azure SQL Data Warehouse
- Google BigQuery (Beta)
- IBM Netezza (Beta)
- Impala (version 2.x)
- Oracle Database (version 12 and above)
- SAP Business Warehouse Application Server
- SAP Business Warehouse Message Server (Beta)
- SAP HANA
- Snowflake
- Spark (Beta) (version 0.9 and above)
- SQL Server
- Teradata Databas
Why we are using DataQuery? For what circumstances we need to use this feature in Power BI? Following are some areas where we have to sue this.
- Import Data size is too BIG
- Limitation of placing the data on outside organization as for security and other policy
- Data is changing very frequently - like SharePrice, News Report, or your daily support maintain tickets
- Data security - not everyone allows to view company's data - current year year to date balance sheet or sales vole, or bid value
- Source data is under OLAP - SAP HANA or SAP BW - Specific to these cases, additional modeling restrictions are here
No support for calculated columns
Additional limitations for measures
No support for defining relationships:
No Data View
Column and measure details are fixed
Additional limitations in DAX
Additional limitations for measures
No support for defining relationships:
No Data View
Column and measure details are fixed
Additional limitations in DAX
Here are some impacts we can see when using DataQuery.
- Performance on Loading Data - Normal loading data from other data sources is within <=5s
- Single Data Source - Unable to connect multiple source at the same time
- Limited Data Transformations - like parsing data from other sources using JSON
- Modling limitation - Defining relationship between table; no calculated column; no full flavor of measure etc
- No built in data hierarchy
- No clustering
- Calculated tables not supported
- Quick insights is not supported
- Q&A is not supported
More to know about DataQuery - I'll continue this in my next article.
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