![]() Then, we will manually type the name of attribute we want to extract and voila, the field is added. Choose extract element (just like shown below). But this time, let’s do it different way - let’s click the arrow down icon at the top of the “sessions” column to access the data transformation menu. Let’s name it as pages_visited and do the same thing with errors attribute. We have separated the field pages_visited into separate column. When viewing the field, it is possible to click on any attribute of the object and click “Extract” in order to extract the field into a discrete column. You can inspect the contents of this column in any row by hovering over this cell and clicking three dots. Mongodb bi tools full#You can download the full dataset, and here is a sample of our data: 1 Not only that, we also use Dremio to reshape and blend different data sources so they are easier to use in Power BI (of course, there is a possibility to do all the crunching in Power BI, but some of it, for example transforming nested objects, is better done in Dremio).įirst, we will need to connect to a running instance of MongoDB in order to get to the database. This can pose a bit of problem, especially that Power BI is targeted at the non-programming audience and MongoDB is a quite versatile database used for many use cases, e.g., textual data, nested objects, and arrays representation, naturalistic data model all of that are a perfect match for such applications as mobile development, IoT, analytics and many more.įortunately, Dremio allows us to connect to the data from MongoDB very easily. Mongodb bi tools driver#Of course, there is the ability to use ODBC driver for mongo (which is unfortunately slow) or integrate it via custom R code, but you will have to complete a lot of work and coding manually. An instance of such limitation is the ability to connect to NoSQL schema (e.g., MongoDB) directly. However, everything has its limitations, and Power BI is no exception. Power BI is a big player in the market of business intelligence solutions, and there are good reasons why: it is flexible, features a vast library of standard visualizations, and provides the ability to connect to an array of data sources of varying types.
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