Category: SQL Server

Azure, BISM Tabular, Business Intelligence - BI, DAX, Excel, Power BI, Power BI Desktop, Power BI Embedded Capacity, Power BI Premium Capacity, Power BI Service, Self-Service BI, SQL Server, SQL Server Analysis Services - SSAS, SQL Server Management Studio - SSMS, Tableau Desktop

What Does XMLA Endpoints Mean for Power BI and How to Test it for Free?

Test Environment from Power BI XMLA Endpoint

XMLA endpoint connectivity for public preview has been announced late March 2019. As at today, it is only available for Power BI Premium capacity users. This sounds like a massive restriction to a lot of people who don’t have a Premium capacity, but they’d love to see how it works. In this article I show you an easy way to get your hands to Power BI XMLA endpoint as quick as possible. Before I start, I’d like to simply explain what XMLA endpoint is and what it really means for Power BI users.

Power BI is Like Onion! It has layers!

Generally speaking, Power BI has two different layers, presentation layer and data model layer. Presentation layer is the visual layer, the one you make all those compelling reports and visualisations. The data model as the name resembles, is the layer that you make your data model in. This layer is the one you can access it via XMLA connectivity.

In a Power BI Desktop file, you can see both layers:

Different layers of Power BI

How XMLA Relates to Different Layers in Power BI?

As you may have already guessed, XMLA is only related to the data model layer and it has nothing to do with the presentation layer. So you may connect to a data model, browse the data model, import data from the model to other platforms like Excel and so forth.

XMLA Is Not New!

Seriously? Yes, seriously. It is not new. It’s been around for many years and perhaps you’ve already used it zillions of times. Whenever you’re connecting to an instance of SQL Server Analysis Services, either Multidimensional or Tabular from any tools like SQL Server Management Studio (SSMS), Power BI Report Builder, Excel, Tableau, etc…, you’re using XMLA connectivity indeed.

Power BI is an Instance of SSAS Tabular

It is true. Power BI runs a local instance of SSAS Tabular model. So, whenever you open a Power BI Desktop file (PBIX), Power BI creates a local instance of SSAS Tabular model with a random local port number that can be accessed on your local machine only. When you close the file, the local instance of SSAS Tabular is shut down and its port number is released.

I first revealed the fact that you can connect to the underlying data model in Power BI Desktop from whole different range of tools like SSMS, SQL Server Profiler, Excel, etc… on Jun 2016. So, we indeed were using XMLA to connect to Power BI data models for a long time. We can even take a step further to import our Power BI data models into an instance of SSAS Tabular. In that sense, we are literally generating XMLA scripts from Power BI to create the same data model in SSAS Tabular. How cool is that?

Sooo… What is new then?

Continue reading “What Does XMLA Endpoints Mean for Power BI and How to Test it for Free?” →
Business Intelligence - BI, Excel, Power BI, Power BI Desktop, Power Query, Quick Tips, Self-Service BI, T-SQL

Quick Tips: How to Filter a Column by another Column from a Different Query in Power Query

Filter a Column by a Column from a Different Query in Power Query

A while ago I was visiting a customer that asked if they can filter a query data by a column from another query in Power BI. And I said of course you can. In this post I explain how that can be achieved in Power Query. The key point is to know how to reference a query and how to reference a column of that query in Power Query. This is useful when you have a lookup table that can be sourced from every supported data source in Power Query and you want to filter the results of another query by relevant column in the lookup query. In that case, you’ll have a sort of dynamic filtering. So, whenever you refresh your model if new records have been changed in or added to the source of the lookup query, your table will automatically include the new values in the filter step in Power Query.

Referencing a Query

It is quite simple, you just need to use the name of the query. If the query name contains special characters like space, then you need to wrap it with number sign and double quotes like #”QUERY_NAME”. So, if I want to reference another query, in a new blank query, then the Power Query (M) scripts would look like below:

let
    Source = Product
in
    Source

Or something like 

let
    Source = #"Product Category"
in
    Source

Referencing a Column

Referencing a column is also quite simple. When you reference a column you need to mention the referencing query name, explained above, along with the column name in brackets. So, the format will look like #”QUERY_NAME”[COLUMN_NAME]. The result is a list of values of that particular column.

let
    Source = #"Product Category"[Product Category Name]
in
    Source
Referencing a Column from Another Query in Power Query
Continue reading “Quick Tips: How to Filter a Column by another Column from a Different Query in Power Query” →
Azure Analysis Services, BISM Tabular, Business Intelligence - BI, Data Warehousing - DW, DAX, Excel, Power BI, Power BI Desktop, Power Pivot, Power Query, Quick Tips, SQL Server, SQL Server Analysis Services - SSAS, T-SQL

Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models

Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models
Photo by Markus Spiske

In an article I posted a while back I showed different methods of creating Time dimension in Power BI and Tabular models. The Time dimension I explained was in Minutes. In this post I show you simple way to create Time dimension supporting Seconds. As this is a quick tip, I only show you how to get the Time and ID columns in the Time dimension. If you need to add time bands (time buckets) check this out for more details.

Time Dimension in Seconds Grain with Power Query (M):

Copy/paste the code below in Advanced Editor to generate Time dimension in Power Query:

let
Source = Table.FromList({1..86400}, Splitter.SplitByNothing()),
#"Renamed Columns" = Table.RenameColumns(Source,{{"Column1", "ID"}}),
#"Time Column Added" = Table.AddColumn(#"Renamed Columns", "Time", each Time.From(#datetime(1970,1,1,0,0,0)+#duration(0,0,0,[ID]))),
#"Changed Type" = Table.TransformColumnTypes(#"Time Column Added",{{"ID", Int64.Type}, {"Time", type time}})
in
#"Changed Type"
Time Dimension in Power Query

Time Dimension in Seconds Grain with DAX:

Run the DAX expression below in a new calculated Table in Power BI or SSAS Tabular model:

Time in DAX = ADDCOLUMNS(
                       GENERATESERIES(1, 86400, 1)
                        , "Time", TIME(0, 0, 0) + [Value]/86400
                        )
Time Dimension in Seconds Level with DAX
Continue reading “Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models” →
Azure, Azure Analysis Services, BISM Multidimensional, BISM Tabular, Business Intelligence - BI, On-premises Data Gateway Enterprise Mode, Power BI, Power BI Desktop, Power BI Service, SQL Server, SQL Server Analysis Services - SSAS

Preparing On-premises Data Gateway Implementation Plans for Enterprises

Definitive Guide to On-premises Data Gateway Implementation
Photo credit: Kayla Duhon

If you are a Business Intelligence consultant working on Power Platform, Azure Logic Apps and Azure Analysis Services landscape, you probably know that On-premises Data Gateway cab be one of the most essential parts of your engagements with your customers. In many cases, installing On-premises Data Gateway can be a one-man-band job but in many others, it requires teamwork effort. Either way, it can go smoothly if you already have a well-thought implementation plan otherwise, it can quickly turn into a beast that can exhaust the whole implementation team and the customer for some days.

In this post, I do my best to provide you with some guidelines that can help you with your On-premises Data Gateway implementation planning. This post may look rather long, and some of the points are generic, but it is worthwhile mentioning them. Consider the following points before, during and after the engagement:

  • Understanding the use cases
  • Culture of the engagement
  • Environments (Dev, UAT, Prod)
  • Communication
  • Security
    • Corporate/environmental firewalls
    • Proxy Servers
    • Identity Access Management
  • People
  • Documentation
  • Installation, configuration, and testing

Here is a diagram of the important points that you should consider:

Implementing On-premises Data Gateway
Implementing On-premises Data Gateway

Use cases

You need to understand the use cases of On-premises Data Gateway (Standard Gateway) for your customer. If they need the gateway for their Power Platform, Azure Logic Apps, Azure Analysis Services or all of them. This is important as you either need to have access to your customer’s Power BI Service or Azure Portal or both, or you need to assist your customer to configure On-premises Data Gateway in Azure or in Power BI Service. The next points are:

  • Accessing customer’s Azure Portal and/or Power BI Service: The customer to decide whether to create a new account with sufficient rights for you or give you the credentials of an existing account. It is important to make sure you can access all environments and you have necessary rights to install/configure the gateway
  • You assist/consult a person at customer side with the implementation: you need to make sure you communicate with that person and see if he/she understands the requirements before the implementation date. Send them a calendar invitation beforehand to make sure he/she is present at that date. Always ask for a backup person just in case of an emergency happening to the primary person.
Continue reading “Preparing On-premises Data Gateway Implementation Plans for Enterprises” →