Optimising OData Refresh Performance in Power Query for Power BI and Excel

OData has been adopted by many software solutions and has been around for many years. Most solutions are using the OData is to serve their transactional processes. But as we know, Power BI is an analytical solution that can fetch hundreds of thousands (or millions) rows of data in a single table. So, obviously, OData is not optimised for that kind of purpose. One of the biggest challenges many Power BI developers face when working with OData connections is performance issues. The performance depends on numerous factors such as the size of tables in the backend database that the OData connection is serving, peak read data volume over periods of time, throttling mechanism to control over-utilisation of resources etc…

So, generally speaking, we do not expect to get a blazing fast data refresh performance over OData connections, that’s why in many cases using OData connections for analytical tools such as Power BI is discouraged. So, what are the solutions or alternatives if we do not use OData connections in Power BI? Well, the best solution is to migrate the data into an intermediary repository, such as Azure SQL Database or Azure Data Lake Store or even a simple Azure Storage Account, then connect from Power BI to that database. We must decide on the intermediary repository depending on the business requirements, technology preferences, costs, desired data latency, future support requirement and expertise etc…

But, what if we do not have any other options for now, and we have to use OData connection in Power BI without blasting the size and costs of the project by moving the data to an intermediary space? And.. let’s face it, many organisations dislike the idea of using an intermediary space for various reasons. The simplest one is that they simply cannot afford the associated costs of using intermediary storage or they do not have the expertise to support the solution in long term.

In this post, I am not discussing the solutions involving any alternatives; instead, I provide some tips and tricks that can improve the performance of your data refreshes over OData connections in Power BI.

Notes

The tips in this post will not give you blazing-fast data refresh performance over OData, but they will help you to improve the data refresh performance. So if you take all the actions explained in this post and you still do not get an acceptable performance, then you might need to think about the alternatives and move your data into a central repository.

If you are getting data from a D365 data source, you may want to look at some alternatives to OData connection such as Dataverse (SQL Endpoint), D365 Dataverse (Legacy) or Common Data Services (CDS). But keep in mind, even those connectors have some limitations and might not give you an acceptable data refresh performance. For instance, Dataverse (SQL Endpoint) has 80MB table size limitation. There might be some other reasons for not getting a good performance over those connections such as having extra wide tables. Believe me, I’ve seen some tables with more than 800 columns.

Some suggestions in this post apply to other data sources and are not limited to OData connections only.

Suggestion 1: Measure the data source size

It is always good to have an idea of the size of the data source we are dealing with and OData connection is no different. In fact, the backend tables on OData sources can be wast. I wrote a blog post around that before, so I suggest you use the custom function I wrote to understand the size of the data source. If your data source is large, then the query in that post takes a long time to get the results, but you can filter the tables to get the results quicker.

Suggestion 2: Avoid getting throttled

As mentioned earlier, many solutions have some throttling mechanisms to control the over-utilisation of resources. Sending many API requests may trigger throttling which limits our access to the data for a short period of time. During that period, our calls are redirected to a different URL.

Tip 1: Disabling Parallel Loading of Tables

One of the many reasons that Power BI requests many API calls is loading the data into multiple tables in Parallel. We can disable this setting from Power BI Desktop by following these steps:

  1. Click the File menu
  2. Click Options and settings
  3. Click Options
  4. Click the Data Load tab from the CURREN FILE section
  5. Untick the Enable parallel loading of tables option
Disabling Parallel Loading of Tables in Power BI
Disabling Parallel Loading of Tables in Power BI Desktop
Continue reading “Optimising OData Refresh Performance in Power Query for Power BI and Excel”

Power BI 101, Report Authoring Tools

This is my last blog post in 2021. I wish you all a wonderful break and a happy new year.

In the first post of my Power BI 101 series, we learnt that Power BI is a data platform containing various tools and services. We also explained the currently available subscriptions within the Power BI platform. The focus of the second post of this series is on what we should learn to achieve our goals more efficiently. In this post, we focus on the reporting tools available to us according to our subscription plan. From this post onwards, we discuss more specific aspects of the Power BI platform.

We learnt so far that Power BI is not just a reporting tool to build sophisticated reports; it is indeed a platform supplying a wide range of features from data preparation, data modelling and data visualization to contribute to an organisation’s data analysis journey in many ways such as sharing datasets, reports, and dashboards. All of these are possible only if we take the correct steps in building our Power BI ecosystem. But, it is very true that Power BI gives us the flexibility to create professional-looking and eye-catching visualisations providing easy to understand insights around a subject. The most renowned tool within Power BI is Power BI Desktop, but it is not the only tool available to us to create reports. Besides, Power BI Desktop reports are not necessarily the best answer to all business requirements. In fact, the business requirements define the Power BI architecture that supports those requirements. Based on the architecture, organisations decide to acquire a certain subscription plan, and based on the subscription plan, we have various reporting tools available to us. At this point, you might ask, “well, what architecture supports my organisation requires?”. Let’s answer that question in a future blog post.

For the purpose of this blog post, it is enough to know what reporting tools are available under which subscription plans. Let’s get started.

Reporting tools available in Power BI

As mentioned earlier, there are various reporting tools available to us. Let’s first see what reporting tools are available to us regardless of the subscription plans. Then we will look at the subscription plans supporting those tools.

Power BI Service

Power BI Service is a SaaS (Software as a Service) offering from Microsoft in the cloud. The users within an organisation, depending on their access rights, may create reports directly in Power BI Service. The users can also securely share and distribute those reports. While creating or editing reports is possible in Power BI Service, it is strongly recommended to avoid this method for several reasons. The most obvious one is that the changes we make to a report may soon get overwritten by someone else that republishes the same report from Power BI Desktop. Check this blog post from SQLChick to see why you should avoid creating or editing reports directly from Power BI Service. The reports are downloadable in PBIX format. 

You can access Power BI Service here.

Power BI Desktop

It is a desktop application built for data preparation, data modelling and data visualisation. If you like to learn about data modelling with Power BI, check out my book here. We can use Power BI Desktop to connect to more than 250 different data sources, preparing, transforming and cleansing that data and at lastly visualising the data. Power BI Desktop is the predominant and most renowned report authoring tool available in the Power BI platform. It has many more functionalities and is more flexible than Power BI Service. For instance, setting up Role Level Security (RLS) is not available in Power BI Service. The file format of the reports created in Power BI Desktop is PBIX. 

Download Power BI Desktop from here.

Power BI Report Builder (Paginated)

Paginated reports aka pixel-perfect reports are formatted in a way to fit perfectly on a page. That report page might later be printed. We have exact control over page formatting to display our data in tables or charts. The reports are not as interactive as the reports created in Power BI Desktop.

Paginated reports are based on RDL technology which is standard report format in SQL Server Reporting Services (SSRS). The tool for developing a paginated report in the Power BI ecosystem is Power BI Report Builder. The reports file type is RDL. We can currently publish Paginated reports only to a Workspace that is backed with either a Premium Per User (PPU) or a Premium Capacity. 

Download Power BI Report Builder from here.

Power BI Desktop Optimised for Report Server (RS)

Power BI Report Server (PBIRS) is an on-premises server capable of rendering Power BI report files (PBIX). If we have a PBIRS up and running within our organisation and we require to publish Power BI reports to PBIRS, then we will need to create our reports in a special edition of Power BI Desktop which is optimised for PBIRS. This edition is different from Power BI Desktop, which we usually use to create and publish our reports to Power BI Service. For instance, Power BI Desktop RS does not include the preview features we used to see in Power BI Desktop until those features are released. Building reports in Power BI Desktop RS guarantees that the reports are fully functional after being deployed to our PBIRS. We can install Power BI Desktop and Power BI Desktop RS side-by-side on the same machine. 

Download Power BI Desktop RS from here.

Continue reading “Power BI 101, Report Authoring Tools”

Quick Tips: Adding Leading Zero to Integer Values (Padding) with DAX and Power Query

Quick Tips: Adding Leading Zero to Integer Values (Padding) with DAX and Power Query

There are some cases that we want to add a leading zero to a digit, such as showing 01 instead of 1, 02 instead of 2 and so on. We have two options to do this in Power BI, doing it in Power Query or doing it with DAX.

Adding a Leading Zero in Power Query

The first method is doing it in Power Query using the Text.PadStart() function.

Here is how the syntax of the function:

Text.PadStart(text as nullable text, count as number, optional character as nullable text)

And here is how the function works:

Text.PadStart(input string, the length of the string, an optional character to be added to the beginning of the string util we reach to the string length)

For example, Text.PadStart("12345", 10 , "a") returns aaaaa12345 and Text.PadStart("1", 2 , "0") returns 01.

Let’s create a list of integer values between 1 to 20 with the following expression:

{1..20}
Creating a List of Integer Values Between 1 to 20 In Power Query
Creating a List of Integer Values Between 1 to 20 In Power Query

Now we convert the list to a table by clicking the To Table button from the Transform tab:

Converting a List to a Table in Power Query
Converting a List to a Table in Power Query

Now we add a new column by clicking the Custom Column from the Add Column tab from the ribbon bar:

Adding a New Column to a Table in Power Query
Adding a New Custom Column to a Table in Power Query

Now we use the following expression in the Custom Column window to pad the numbers with a leading zero:

Continue reading “Quick Tips: Adding Leading Zero to Integer Values (Padding) with DAX and Power Query”

The Story of my Book, “Expert Data Modeling with Power BI”

Expert Data Modeling with Power BI
Expert Data Modeling with Power BI

In 2020, the world celebrated the new year with many uncertainties. Well, life is full of uncertainties, but, this one was very different. The world was facing a new pandemic that never experienced before. The first COVID19 case in New Zealand was confirmed in February 2020. In March 2020 the entire country went to lockdown for the first time. The world was experiencing a massive threat changing everyone’s lives. I was no different. Every day was starting with bad news. A relative passed away; a friend got the virus; the customers put the projects on hold etc. Nothing was looking normal anymore. You can’t even go to get a proper haircut, because everyone is in lockdown. This is me trying to smile after getting a homemade haircut. I bet many of you have done the same thing.

Soheil's Homemade Haircut
Soheil’s Homemade Haircut

One day, I checked my email and saw a message from Packt Publishing. They wanted to see if I am interested in writing a book about Power BI. That was a piece of good news after a long time. I always wanted to write a book about Power BI. Indeed, I attempted for the first time in 2016, but I couldn’t manage to get my ducks in a row to grasp the publishers’ attention.

I was not unfamiliar with writing books; indeed, I wrote my first book back in 2006 about Multimedia Applications in Persian. One of my passions in life is listening to music. And CDs were the most accessible music source with high-quality sound. I recall I saved money for some months, and I bought a Discman to listen to the music on the go. But CDs are rather bulky, and you could not have many of them in your pocket. So the next project was to save even more money to buy an MP3 player. But, converting Audio CDs to MP3 without compromising a lot on the sound quality was a real challenge for many people. And, that was my motive to write my first book in Persian to share my little knowledge with everyone. 

Continue reading “The Story of my Book, “Expert Data Modeling with Power BI””