PowerBI.tips

Author: mike carlo

  • Overcoming Challenges in the Center of Excellence

    Overcoming Challenges in the Center of Excellence

    Starting a center of excellence (COE) can feel daunting. We face political challenges. This article pushes to explore the challenges of a COE and some recommendations to handle these challenges.

    The Importance of Attention to Detail

    Microsoft does a great job in outlining the key aspects of COE. For more details on this topic check out the Fabric adoption roadmap found here. A summary of those items are in the list below:

    I strongly feel that documenting the result of these conversations is a huge win. The documentation can be used to show leadership that you have a solid plan. Discussing these topics pushes towards a health data culture. Lastly, when you bring documentation to leadership you show thought of aspects that drive success.

    Foundational Attributes for Success

    The optics of the COE matter. COE performance and leadership are crucial, as they can impact the entire organization. Don’t underestimate the value of setting clear goals. Taking time to identify pain points with your current organization structure help with planning process for the COE.

    • Setting clear goals
    • Addressing pain points that you see, plan to solve those pain points
    • Just start, don’t worry about making the COE perfect, plan for adjustments

    Sometimes I feel that people try to over plan. Therefore, read up on the best practices provided by Microsoft’s documentation, write down your decisions then get moving! I have observed just by communicating and developing the plan really creates some momentum. Bear in mind it won’t be perfect in the first iteration. Plan on being flexible to adjust the COE to the organizations needs.

    Recommendations for Overcoming Challenges

    • Attention to Detail: Paying attention to aspect you can control of the COE’s performance. Engage leadership so they support the development of the COE. Remember the COE is a vote in the direction of better data culture for your company.
    • Setting Clear Goals: Defining clear goals helps the team align towards a unified direction. Address pain points that could derail or distract from the creation of the COE. Connect the success of the COE to Objectives and Key Results (OKRs) outlined by the leadership team.
    • Regular Communication with Executives: Regular communication with the executive team helps remove mis-aligned expectations. When you win let leadership know, they can promote your success. Success means more buy-in from the company.
    • Feedback: Gathering feedback and pivot. Have empath for the process and be willing to adjust. If something is not working within the COE try something new. Ask others involved in the COE for recommendations, some of the smartest people are the ones you already work with.

    For more thoughts on the COE and overcoming those challenges check out our episode on the explicit measures podcast.

  • Exploring the Power of Semantic Link

    Exploring the Power of Semantic Link

    Semantic link is one of the most promising technologies coming from the Microsoft Power BI and Fabric team. Semantic link has the potential to automate so many redundant tasks and tedious work. Automating and using code enables BI developers to free up time for more value-added work. Join Stephanie Bruno and Mike Carlo as they do a thorough demo of using Semantic Link.

    Semantic link is a powerful tool that allows direct access and manipulation of data within semantic models using code and notebooks. It offers automation, streamlined data extraction, and centralized data management within models. Throughout this workshop, we’ll delve into the diverse functionalities of semantic link and its potential benefits for data scientists, analysts, engineers, and fabric admins.

    This demo covers a range of topics, including:

    • Accessing and visualizing a Power BI report within a notebook
    • Exploring the list of reports in a workspace
    • Retrieving insights about tables and columns in a semantic model
    • Listing and comprehending measures within a semantic model
    • Visualizing and understanding table relationships
    • Utilizing semantic link for data access and manipulation

    Live Demos and Practical Demonstrations

    Our expert presenter, Stephanie Bruno, will lead live demonstrations and hands-on exercises to illustrate the practical applications of semantic link. The demos will encompass:

    • Creating a new notebook and connecting it to a workspace
    • Retrieving and visualizing reports within the notebook
    • Exploring tables, columns, and measures within a semantic model
    • Understanding and visualizing table relationships
    • Accessing and manipulating data using semantic link
    • Employing DAX magic to write and evaluate DAX expressions

    Throughout the workshop, we’ll showcase how semantic link empowers data scientists to access and utilize measures without the need to reconstruct complex logic. Additionally, we’ll highlight the seamless integration of semantic link with Python, facilitating efficient data manipulation and analysis.

    More where that came from

    If you like this type of training and content, join us over at Training.tips for 60+ hours of additional training.

  • Does a Power BI developer need Python?

    Does a Power BI developer need Python?

    In this episode of the Explicit Measures Podcast, we discuss the values of adding Python knowledge. It is well known that more organizations are moving to cloud platforms. Because of this, we should ask the following questions:

    • What will be the needed skills for Power BI professionals?
    • Is this for the Business or for a Data Engineer?

    We invite you to jump in and listen to the podcast as we discuss these topics. Enjoy!

    YouTube Explicit Measures Podcast

    Listen on the go

    Don’t want to watch the video, no problem we are on all major podcast platforms.
    Spotify
    Apple Podcasts
    iHeart Radio

    Ask Chat GPT

    As in all our episodes we like to end with what does chat GPT say. Thus, our question for this episode is

    Should I learn Python for Power BI development?

    Chat GPT response

    The response was quite interesting, discussing the various factors as to why Python is valuable. Overall, we gave chat GPT a better than average score of about 6.5 out of 7.

    Learning Python can be beneficial for Power BI development. Python is a versatile programming language that is widely used in data analysis, data manipulation, and data visualization tasks. Power BI has its own built-in capabilities for data processing and visualization. Python can extend its functionality and provide additional flexibility.

    Here are a few reasons why learning Python for Power BI development can be advantageous:

    Data Manipulation

    Python has a rich ecosystem of libraries such as Pandas, NumPy, and scikit-learn. These libraries are excellent for data manipulation, cleaning, and transformation. Use Python to preprocess and shape your data before loading it into Power BI.

    Advanced Analytics

    Python offers a range of libraries for advanced analytics and machine learning, such as TensorFlow, Keras, and PyTorch. Integrating Python code into Power BI, you can leverage these libraries to perform complex calculations. Additional features could include predictive modeling, or create custom machine learning models to enhance your data analysis capabilities.

    Custom Visualizations

    Power BI provides a variety of built-in visualizations. But, if you have specific visualization requirements or want to create custom charts. Python can be a powerful tool for visual development. Libraries like Matplotlib and Seaborn offer extensive options for data visualization. Enabling you to generate interactive and customized charts and graphs to present your insights effectively.

    Automation and Integration

    Python can help automate repetitive tasks and streamline your Power BI workflows. You can write Python scripts to extract data from different sources, transform it, and load it into Power BI automatically. Python’s integration capabilities enables connections with other tools and platforms, such as web APIs, databases, or cloud services. Python expands the scope of your data analysis.

    Community Support

    Python has a large and active community, with abundant resources, tutorials, and forums available. Learning Python can provide you with access to a wealth of knowledge and expertise. A Large community makes it easier to find solutions to specific challenges.

    In conclusion, while it is not necessary to learn Python for Power BI development. It can certainly enhance your capabilities and offer more flexibility in data manipulation, advanced analytics, custom visualizations, and automation. Consider your specific requirements and goals for a project. Your project requirements may determine whether investing time in learning Python would be beneficial.

    Chat GPT – May 12 Version

    Not bad Chat GPT. I would disagree with a couple points made on how easy it is to integrate python into Power BI. Two options I am aware of today using Python in Power Query.

    Option 1 – Using Python in Power Query

    Using Python in Power Query from Microsoft Learn

    Option 2 – Using Python for Visuals

    Using Python to develop a Visual

    I feel that more of python is used in cloud services. This was a major point brought by Seth in the podcast. Very valid point.

    Overall, we hope you enjoyed the podcast! See you next time.

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  • Super Fast Data Loads to Prod

    Super Fast Data Loads to Prod

    When you have really large data models loaded in powerbi.com there are challenges around quickly loading gigs of data into a data model. This is particularly challenging when working with data models in production. When changes are made which require a full load of data tables this can take hours to refresh. This means when a production change needs to be made, this should be done in low use times, evenings or over the weekend. What if we could greatly increase the load speed? but, we can!!

    TL/DR

    Let us cut to the chase. How do we solve this issue? We use Power BI backups with Azure blob storage. This feature can be found here on the official Microsoft Documentation.

    Below is a high level architecture and movement of the Power BI data models across the blob storage account.

    The Solution

    The high level solution goes something like this:

    1. Create two workspaces, one in prod and one for pre-loading data
    2. Connect both workspaces to premium
    3. Turn both premium capacities to large dataset capacities
    4. Link azure storage to both workspaces
    5. Publish a modified data model into the pre-load workspace, this contains the changes to the data model.
    6. kick off a full load of the data model in the pre-load workspace
    7. Open SSMS connect to the backup the pre-load workspace XMLA endpoint
    8. Backup the pre-loaded model to azure blob storage using SSMS
    9. Open azure bob storage, copy and paste the .abf file into the prod workspace
    10. Use SSMS to connect to the prod workspace XMLA endpoint
    11. Use the restore feature from SSMS to load the .abf file back into the model in production

    Instructions

    Below are the step by step instructions as show throughout the experience.

    When you link your Power BI workspaces you will see inside the Blob storage a folder for powerbi and another folder for power-bi-backup. Note, it is important that both workspaces the pre-loading data workspace and the prod workspace point to the same blob storage account.

    For each workspace PowerBI.com will create a single folder for each workspace. See below we have two workspaces for this demo.

    We can use the XMLA endpoint found in the workspace settings to connect and see the partitions within our data model. For this example we have a pre-loaded dataset called nyctaxi. This dataset was deployed into a workspace and fully refreshed loading all the data into all the partitions.

    Below is a the same dataset, with the exception there are no partitions preloaded. We assume we are going to use the backup created from the above dataset and then load the partitions into the Prod model.

    Note: in this example we are pushing all the partitions and all data in the partitions into production. Usually your production model will already have partitions. Thus, it is easier to show our model adding partitions for this demo. If you really want to confirm the data is correctly being restored from backups you would look at the row counts found in each partition.

    Here we log into the pre-loaded data set using SSMS.

    Right Click on the data model that you are going to backup. Select the option labeled Back Up… in the drop down menu.

    After clicking Back Up… a menu will appear letting you to name the backup file.

    It is recommended to allow the file to be overwritten and to apply compression to the files. Once your settings have been configured, then you can Click the OK button at the bottom of the window to accept the changes.

    After the backup completes we will be able to see the .abf file inside the blob storage folder.

    Using the copy and paste buttons form the azure portal you move the files between the workspace folders.

    Below is the copied model .abf file from the demo-synapse (pre-loaded data) into the Prod workspace named (Demo – Test Models).

    In SSMS we connect to the production workspace. Again Right click on the data model and select Restore… shown in the drop down menu.

    The restore menu will appear. In this menu clicking on the Browse button will bring up another window letting the user to select the data model from the storage account.

    Note: on this screen you will need to select Allow database overwrite and it is optional to select if you want to Overwrite security

    Below is a screen shot of the selection screen for picking the model

    Once the restore has completed we can go back to our production model and see we now have partitions loaded.

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  • Data Culture with Matthew Roche

    Data Culture with Matthew Roche

    This month we partnered with the relaunch of the Des Moines user group to host Matthew Roche. This month’s topic is all about data culture. If you don’t know Matthew you should get to know him. His experience in developing enterprise data access is second to none. Along this journey of working with the largest Microsoft clients Matthew has learned a lot about their data cultures.

    Obviously working with so many companies you can see what works and what does not. In this video webinar, Matthew discusses what is Data Culture. Additionally, there are aspects of what determines a successful environment.

    Check out the full video below. Link for YouTube Video.

    Thank You and Follow

    Massive thank you to Matthew our presenter. Huge shout out to James Bartlett and Dipo Thompson for the planning. Be sure to follow our presenters on LinkedIn.

    Other Data Culture Projects

    Matthew has also worked on many other impactful projects. One such project has been the Power BI Roadmap. This the best guide for individuals wanting to start their Power BI journey. On the Explicit Measures Podcast we discuss the Power BI roadmap quite often. Thus, we feel it adds a ton of value. Check it out for yourself.

    Visit the Power BI Adoption Roadmap here

    Data Culture Image from Adoption Roadmap

    Data Culture Slides

    For the link to the slides of this presentation please download them here.

    If you like the content from PowerBI.Tips please follow us on all the social outlets. Stay up to date on all the latest features and free tutorials.  Subscribe to our YouTube Channel.  Or follow us on the social channels, Twitter and LinkedIn where we will post all the announcements for new tutorials and content.

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  • A better way to Mobile

    A better way to Mobile

    Where does the Power BI Mobile app fit within your report building plan? This topic is widely un-discussed within the Power BI community. Many blogs and tutorials focus mainly on developing Power BI reports for a desktop screen.  More specifically, a report design that fits a wide screen monitor. However, building reports for the mobile app require additional considerations.

    The Current State of Mobile

    First before we get to the recommendations for mobile reporting developments, let us discuss the current status of building a mobile report. To create a mobile centric view Power BI desktop follow these steps:

    1. Click on the View ribbon
    2. Click on the button labeled Mobile layout
    Click on the Mobile Layout

    Portrait Mode Only

    This takes you to a new screen where the mobile device is positioned in portrait mode.  At the time of writing this article there are no options to build a mobile view in landscape. If you desire to have a mobile report that can be viewed in landscape mode you actually have to create a normal report view but with a narrower screen.

    View of building reports in the mobile view.

    Simplified Build Experience

    The report canvas is greatly simplified. Meaning you don’t get all the advanced features of a normal report page. Stacking visuals on top of each other is not an option. Changing the color of the background is not an option on this screen. Instead, to change the mobile page background color you have to leave the mobile view.  Return to desktop mode change the color and then return to the mobile view.

    An Alternative Approach

    Due to the limitations mentioned above. We propose that you build a report page with custom dimensions.  From my experimentation a width of a page from 600 to 800 pixels meets my needs. The page length can be as long as you need it so that all the required visuals can fit on the page. Previously pages have grown to 1000 to 2000 pixels in length. 

    How to customize the page size?

    Follow these instructions to change the page size

    1. Click somewhere on the Report page to deselect any visuals
    2. Open up the Visualizations Pane
    3. Click on the Format button; the one that looks like a paint roller
    4. Open the section named Page Size
    5. Change the drop down menu for Type to be Custom
    6. Type in a new Width and Height for the page

    Change View of Report for scrolling

    By making the page narrower but longer, the default view of the report will cause UX challenges. To fix this the report is will need to render as a scrollable object. To do this we adjust the view settings of the page

    1. Click on the View ribbon
    2. Click on the button named Page View
    3. A drop down menu will appear
    4. From this dropdown menu Click on the option named Fit to width
    Fit Page to Width

    Other UI / UX Considerations

    As a report designer it is important to consider the UI for report consumers. In most reports I design everything that the user can see fits on a single page.  Scrolling on a page is not a major issue.  As we introduce scrolling on mobile we run into issues with some visuals. 

    Table Visuals Cause Issues

    Take for example a table visual.  This visual it’s self has scrolling built in. Thus, if you are scrolling a page on mobile when you touch inside the table and swipe up the mobile experience swipes the table visual.  This UX can lead users to get suck inside a table when attempting to scroll the page.

    Table Scrolling Solution

    A solution to address users getting stuck inside a table is to provide a pixel boarder. The boarder can be either dual boarders on the left and right or just one boarder on the left or right. Inside this boarder do not place any visuals that would require scrolling, such as a table.

    Adding a Scrim for added Clarity

    In addition to just retaining a pixel gap on the sides I recommend also adding some color to the background. The concept of the color either in blocks or via a gradient color. See the following sample scrim for reference.

    Mobile Scrim Product

    If you like the content from PowerBI.Tips please follow us on all the social outlets. Stay up to date on all the latest features and free tutorials.  Subscribe to our YouTube Channel.  Or follow us on the social channels, Twitter and LinkedIn where we will post all the announcements for new tutorials and content.

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  • The Dice Game

    The Dice Game

    Well, it’s Friday, time to take a little break and play the Dice Game! The Power BI community is creative and is always developing amazing ideas. This is another incredible example that you can play right in Power BI! The brain child of this game is Kerry Kolosko, an Analyst out of of Australia.

    Play the game

    Below is a sample of the game. Again, fully built in PowerBI. Check out give it a good old roll of the dice!

    The Magic in the Game

    There are animations moving elements all on the report canvas. Rounded buttons to click on. All sorts of neat visual elements. These creative elements are capable via a custom visual, HTML Content. The HTML Content visual is maintained by Daniel Patrick-Marsh.

    Daniel’s work on custom visual development is top notch. So if you are super impressed with this report go download this visual from App Source.

    DOWNLOAD HTML Content Visual

    Download the Game

    For those of us who are really curious and want to see all the code. Download the full Dice Game found here.

    DOWNLOAD the Dice Game

    Please Follow

    If you like the content from PowerBI.Tips please follow us on all the social outlets. Stay up to date on all the latest features and free tutorials.  Subscribe to our YouTube Channel.  Or follow us on the social channels, Twitter and LinkedIn where we will post all the announcements for new tutorials and content.

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  • Power BI End-to-End Architecture

    Power BI End-to-End Architecture

    Melissa Coates of Coates Data Strategies has produced a new version of the Power BI End-to-End architecture document. If you haven’t seen this document it is definitely worth a read.

    Summary of Changes

    If you’d like to watch a quick webinar of the updates to the document you can watch it here.

    Twitter Announcement

    Here is the original announcement and release via twitter.

    https://twitter.com/SQLChick/status/1346112838964801543

    If you’d like to download the latest document you can find it here:
    https://www.coatesdatastrategies.com/diagrams

    Note: The diagram can be downloaded as a PDF and as an Image.

    How it started / How it’s going

    If you are on social media at all you will see meme’s about How it started vs. How it’s going. In the thread of Melissa’s tweet we have a fun image showing the progression of Power BI End-to-End architectures. The number of changes since 2015 is absolutely stunning. Power BI has grown up a lot since 2015. That being said, I’m greatly encouraged to see the Microsoft Power BI team pushing amazing new features.

    Learn More about Power BI End-to-End

    A one page document can contain a lot of information about Power BI. However, it can’t capture every aspect of Power BI. Thus, if you’d like to learn more about Power BI and it’s Administration, Please check out Melissa’s Training. The Power BI Development and Governance Workshop is a deep dive for users who need to administer Power BI.

    Sign up for the workshop here.

    Conclusion

    We hope you enjoy this great document to use or share with your team. I’m confident that you will find areas of interest or learn about new ways to leverage Power BI.

    Special thanks to Melissa Coates for participating in the quick webinar around the Power BI End-to-End architecture.

    If you like the content from PowerBI.Tips please follow us on all the social outlets. Stay up to date on all the latest features and free tutorials.  Subscribe to our YouTube Channel.  Or follow us on the social channels, Twitter and LinkedIn where we will post all the announcements for new tutorials and content.

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  • Phil Seamark on Aggregation Tables

    Phil Seamark on Aggregation Tables

    I was having a candid conversation with Phil Seamark from DAX.tips about Aggregation Tables. During that conversation, I was asking about patterns in using Aggregation tables. Within that 10 minute conversation I was blow away by all the possible patterns. Because of this, we pleaded for Phil to present these patterns to the Milwaukee Brew City User Group.

    Patterns in Aggregation Tables

    Watch the full webinar below from our user group:

    Aggregation Patterns

    While these patterns are described in detail here are the various patterns that can be used for Aggregation tables. Also, Phil includes a great introduction, found here. For each of these articles Phil describes proper usage for the pattern.

    Horizontal Aggs

    The Horizontal Aggs is typically developed using a time dimension. Thus, most aggregation tables would fit this pattern.

    Example of a horizontal Aggregation table

    Accordion Aggs

    The Accordion Aggs are similar to a horizontal Agg. However, the time periods are not equal.

    Accordion Aggregation table. Non uniform incremental aggregations.

    Filtered Aggs

    The Filtered Aggs would contain multiple Aggregation tables of the same data. But, each Agg table could contain different gains of data. For Example, data aggregated by Week, Month or Year.

    Filtered Aggregation example.

    Incremental Aggs

    Finally, the Incremental Aggs. This type of aggregation would be used when aggregating transactions per day by store, and or product.

    Incremental Aggregation where you can aggregated transactions over time

    Thanks Phil

    A special thanks to Phil for presenting. Since, we know you are a busy guy doing tons of great work. Thank you for taking time out of your day to present this wonderful topic. We hope you enjoy this exploration into Agg Tables.

    Check out Phil’s other contributions

    Phil has been quite active on the PowerBI.tips site. Check out all his other fun contributions.

    Like and Follow

    If you like the content from PowerBI.Tips please follow us on all the social outlets. Stay up to date on all the latest features and free tutorials.  Subscribe to our YouTube Channel.  Or follow us on the social channels, Twitter and LinkedIn where we will post all the announcements for new tutorials and content.

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  • Power BI Direct Query Composite Models = Amazing

    Power BI Direct Query Composite Models = Amazing

    Well Microsoft has done it again. They have added a great feature in the Power BI desktop release for December 2020. Direct Query to Power BI data sources is a thing. As a result, this means we unlock new Architectural patterns.

    Enterprise Modeling

    In the Microsoft Release notes we get a glimpse of our new normal. Previously, Power BI datasets could only direct query certain data sources. Here is a full list of data sources for Power BI Desktop. The Enterprise Sematic model is simply larger view of a data model.

    Sample Direct Query diagram

    Read more about Composite Models on the 2020 Power BI release plan.

    What is a Power BI Composite Model?

    Quick background on Composite Models. A Composite model is a data model. More specifically, a Power BI data model. Typically Power BI models have multiple data sources. Such as, Excel, or SQL server. For certain data sources we load data in one of two ways, Importing, or Direct Query. The Import method loads data into the Power BI file. While, Direct Query leaves the data inside the data source, but sends queries to retrieve data on demand. Learn more about Import and Direct Query in these articles.

    Read more about Composite models from the Microsoft documentation found here.

    Why is this Important?

    When we think of an organization there are likely hundreds of data models. These data models support by many different teams. Each model is solves some sort of problem. As an example, we can think about models developed for Human Resources. The Human Resource model informs the HR team about acquiring new talent, or track an interview process. Other teams such as Engineering track spend or project details.

    Organization Reporting

    Using this method, imagine a user who needs to see data from both human resources and engineering. Thus, a user would need to visit two different reports. Obviously value can given by combining multiple data models. This would enable the creation of a single report using data from both sources.

    Direct Query for Power BI datasets

    Now, lets consider the Enterprise Data model. In the Microsoft documentation this is called the Enterprise Semantic Model. We can think of the Enterprise Semantic Model as storing metadata linking tables of data and storing relationships between tables. Direct Query to PowerBI.com now lets us make models of models.

    From our previous example now consider this architecture.

    Direct Query used on PowerBI.com data models

    Report builders can now create a single model that queries other data models. This provides data from multiple subject matter areas. Thus, enabling a single report to combine data from multiple locations.

    Centrally Managed Models

    Often in larger organizations there will be different teams creating models. This means, you might not have access to modify an Enterprise build model. Again, Direct Query to models to the rescue. As a report author, I want to reuse an existing model. However, I would like to add more data to the model that would enrich my reporting. This may come in the form of a connected excel document. For this architecture consider the following diagram.

    Referencing an Enterprise model and adding supplement data through direct query

    This new architecture is the ultimate success for self service business intelligence. Enterprise governed models can be enhanced by business users. Therefore, providing flexibility while controlling model governance and standards.

    More Architecture thoughts

    Power BI is evolving at a rapid pace. Because of this, Power BI is rapidly becoming one of the key tools. Therefore, more thought to Enterprise Architecture must be considered. Learn more about key architectural decision points in our previous articles, Data Architecture, and The Greater Data Solution.

    Composite Models Conclusion

    These are just some of my initial thoughts on this amazing new world we have. There will likely be many more designs and implementations from the community of Power BI developers. I’m extremely excited to see other patterns emerge from using Direct Query against Power BI datasets.

    Read more from the official blog release and Microsoft documentation:

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    Power BI Swag Now Available

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    Purchase the Power BI mask
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