Scenario: You plan to display a Power BI report on a monitor. You want the report to automatically cycle through report pages, showing each after a configurable time delay, like a photo slide show.
Solution: There are at least two solutions to accomplish this:
The Microsoft-supported way is to install the Power BI Mobile for Windows and use its presentation mode feature, which is shown in the screenshot below.
Besides the built-in cross-filtering and cross-highlighting among visuals, Power BI supports two explicit filtering options: slicers and filters. Which one to use? Traditionally, you would use a slicer when you want the user to easily see what’s filtered on the report page. But with the introduction of the new filter pane and slicer enhancements, the choice becomes more difficult. Let’s compare the two options:
Criteria
Slicer
Filter
Placement
Report page (requires space on the page as other visuals)
Report pane
Filter target
Visual, page, report
Visual, page, report
Configuration
Drop-down, list, slider (numbers and dates), “buttons”
Passing a filter via JavaScript APIs to set default values cross-filters the slicer but doesn’t pre-select the slicer default value
Sets the filter as expected
A glaring gap for both filters and slicers is that you can’t currently set the default value programmatically, such as to default a date filter to the last date with data. As a workaround, you can add a field to the Date table, such as IsToday, that is set to Yes for the last date and prefilter on this field, but users must be educated to know how to remove the filter if they want to select another date. This is especially cumbersome with slicers, which don’t even support a single date selection, unless configured as a drop-down or Before/After.
Based on experience, people tend to rely mostly on slicers. But because it’s not uncommon to create reports that must be visually appealing on desktops and mobile devices, here are some recommendations to accommodate both large and small displays.
Use slicers judiciously because they take space on the report page. This could be an issue with mobile devices. Besides taking space, mobile users find it difficult to select values in slicers. I typically use slicers only for common filters, such as Date. Another scenario where slicers could be useful is when you need to visualize the items in a special way, such as a slider or to show a hierarchy of items.
Use filters for the rest of the filtering needs, especially if you plan to optimize reports for mobile viewing in portrait mode and/or use Power BI Embedded to embed reports.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2020-02-09 16:31:362020-02-15 14:27:18Power BI Slicers and Filters
MS BI fans, join us for the next Atlanta MS BI and Power BI Group meeting on February 3rd, Monday, at 6:30 PM at the Microsoft office in Alpharetta. Shabnan Watson will discuss how to apply aggregations to Power BI DirectQuery datasets to improve report performance. Melissa will sponsor the meeting. For more details, visit our group page and don’t forget to RSVP (fill in the RSVP survey if you’re planning to attend).
Presentation:
Aggregations in Power BI
Date:
February 3rd, 2020
Time
6:30 – 8:30 PM ET
Place:
Microsoft Office (Alpharetta) 8000 Avalon Boulevard Suite 900 Alpharetta, GA 30009
Overview:
Aggregations are one of the most important optimization methods for managing big datasets in Power BI. Combined with Direct Query storage mode, they allow big datasets to be analyzed efficiently by answering high level analytical queries quickly from memory while sending more detailed queries back to the source database. In this session, you will learn about the concept of aggregations, different table storage modes in Power BI, different kinds of aggregation tables, how to configure aggregation tables so that they can answer high level user queries, and finally how to use tools such as DAX Studio or Extended Events to determine if the aggregations are actually being used.
Speaker:
Shabnam Watson is a Business Intelligence consultant with 18 years of experience developing data warehouse and BI solutions. Her work focus within the Microsoft BI Stack has been on Analysis Services and Power BI. She is an active member of PASS community and has spoken at PASS Summit, PASS SQL Saturdays, PASS Women In Technology Virtual Chapter, and other Local user groups. She is one of the organizers of SQL Saturday Atlanta and SQL Saturday Atlanta BI Edition. She holds a master’s degree in computer science, a bachelor’s degree in Computer Engineering, and a Certified Business Intelligence Professional (CBIP) certification by The Data Warehouse Institute (TDWI).
Sponsor:
Bad data is bad business. Melissa helps organizations profile, cleanse and verify, dedupe and enrich all their people data (name, address, email and phone number) and more. With clean, accurate and up-to-date customer information, organizations can monetize Big Data, improve sales and marketing, reduce costs and drive business insight. https://www.melissa.com/
Prototypes with Pizza
TBD
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2020-01-27 09:29:522021-02-17 01:02:03Atlanta MS BI and Power BI Group Meeting on February 3rd
Register for my full-day academy training at #PowerPlatformWT in Atlanta on Feb 10th for only $599 and learn how Power BI can bring your data to life!
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2020-01-15 15:21:512020-01-15 15:21:51Get Power BI Training at Power Platform World Tour
Although Power BI has been evolving for almost five years now, basic concepts are sometimes worth revisiting. Recently, I had a discussion regarding the Power BI Pro storage quota on the Power BI MVP list and I want to share the conclusions confirmed by Microsoft.
For workspaces in shared capacity licensed with Power BI Pro (not a workspace in a Premium capacity):
There is a per-workspace storage limit of 10 GB. So, My Workspace gets 10 GB and so does any org workspace.
There is also an unofficial cross-workspace aggregate quota of 10 GB * the number of Pro User Licenses intended as a backstop to prevent abuse so that a Pro user doesn’t keep on indefinitely creating workspaces to get new chunks of 10 GB. So, if you have 50 Power BI Pro users, the aggregate cross-workspace storage quota would be 500 GB irrespective if only one or multiple Pro users contribute. You won’t see the cross-workspace quota in the Power BI Service UI and it’s not exposed through service code.
BTW, you should ignore the “Manage data storage in Power BI workspaces” document until it’s been updated (the current timestamp is 12/20/2018). As it stands, this document contains wrong and incomplete information. For example, sharing datasets, reports, dashboards should have no effect on the workspace storage quota for consumers.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2020-01-07 09:52:232020-01-07 09:52:23Power BI Pro Storage Quota
MS BI fans, join us for the next Atlanta MS BI and Power BI Group meeting on January 6th, Monday, at 6:30 PM at the Microsoft office in Alpharetta. I’ll introduce to Power BI Premium Automated Machine Learning (AutoML). Prologika will sponsor the meeting. For more details, visit our group page and don’t forget to RSVP (fill in the RSVP survey if you’re planning to attend).
Presentation:
Power BI Automated Machine Learning (AutoML)
Date:
January 6th, 2020
Time
6:30 – 8:30 PM ET
Place:
Microsoft Office (Alpharetta) 8000 Avalon Boulevard Suite 900 Alpharetta, GA 30009
Overview:
With the growing demand for predictive analytics, Automated Machine Learning (AutoML) aims to simplify this process and democratize Machine Learning so business users can create their own basic predictive models. Join this presentation to learn how to apply AutoML in Power BI Premium to predict the customer probability to purchase a product. I’ll show you the end-to-end AutoML process, including:
· Create a dataflow
· Choose a field to predict
· Choose a model type
· Select input variables (features)
· Train the model
· Apply the model to new data
· Bonus: Integrate Power BI with AzureML
Speaker:
Through his Atlanta-based company Prologika (https://prologika.com), a Microsoft Gold Partner in Data Analytics, Teo Lachev helps organizations make sense of their most valuable asset: their data. His strategy formulation, trusted advisory and mentoring, design and implementation services empower clients to apply effectively data analytics in order to understand, improve, and transform their business processes. Teo has authored and co-authored several books on organizational and self-service data analytics, and he has been leading the Atlanta Microsoft BI and Power BI group since he founded it in 2010. Teo has been a Microsoft Most Valued Professional (MVP) Data Platform since 2004.
Sponsor:
Prologika is one of the most trusted names in Data Analytics. Our clients, from small businesses to Fortune 100 enterprises, derive tremendous value from our services. Our mission is to help organizations make sense of data by applying the latest technologies for descriptive and predictive analytics and get actionable insights. Your organization will spend less time mining for information and be better equipped to make sound business decisions. https://prologika.com
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2020-01-03 10:30:282021-02-17 01:02:03Atlanta MS BI and Power BI Group Meeting on January 6th
Organized by Microsoft and Dynamic Communities, the Power Platform World Tour will take a place in Atlanta from 2/10-2/12, 2020. I’m teaching Power BI Dashboard in a Day (DIAD) on Feb 10 for a full day. Although this is a paid event ($599), you should get a great business value as the audience will probably be smaller and I’ll be able to provide more personal attention. Then, I’ll present “Bridge Analytics and Developer Worlds with Power Platform” on Feb 12 and show how Power BI can integrate with Power Apps to allow you to change the data behind a report.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2019-12-18 16:34:102019-12-18 16:34:10Power Platform World Tour
Power BI incremental refresh (a Power BI Premium feature) refreshes a subset of a table with imported data. The main goal is to reduce the refresh time so that new data becomes available online faster. Patrick LeBlanc has a great video about how to make the incremental refresh even more incremental by using the “Detect data changes” feature and he explains in detail how it works.
What if you want to fully refresh the dataset set up for incremental refresh? For example, you configure a table for incremental refresh periodically, but you want to fully process the dataset nightly, such as to pick the latest changes to dimensions. Currently, the only option to fully refresh the dataset with an incremental refresh policy is to republish the dataset and refresh it (this works because the first refresh is always full). When the XMLA endpoint becomes writeable, you’ll have the option to do so in an XMLA script. For example, the following script fully refreshes the InternetSales table without applying the refresh policy settings. Notice also the effectiveDate setting that allows you to overwrite the current date for testing purposes.
MS BI fans, join us for the next Atlanta MS BI and Power BI Group meeting on November 4, Monday, at 6:30 PM at the Microsoft office in Alpharetta. Stacey Jones will present Power BI options with Python. Accelebrate will sponsor the meeting. And I will share some tips demoing the latest Power BI Desktop features, such as the new ribbon, decomposition tree and AI integration. For more details, visit our group page and don’t forget to RSVP (fill in the RSVP survey if you’re planning to attend).
Presentation:
Integrating Power BI with Python
Date:
December 2nd, 2019
Time
6:30 – 8:30 PM ET
Place:
Microsoft Office (Alpharetta) 8000 Avalon Boulevard Suite 900 Alpharetta, GA 30009
Overview:
Python is well suited for Data Science and big data professionals. It has been voted as the most popular programming language in 2019. Microsoft made big investments in open-source R and Python, especially to extend Power BI. Join this session to learn how you can integrate Python with Power BI. Learn how to use Python in these ways:
· Use Python as a data source
· Transform data
· Produce beautiful visualizations
Speaker:
Stacey Jones specializes in mentoring and guiding firms in their efforts to build a modern Data, AI & BI governance programs that empower their business with Self-Service BI and Data Science capabilities. He currently serves as the Principal Data Solutions Architect at the Atlanta Microsoft Technology Center (MTC).
Sponsor:
Don’t settle for “one size fits all” training. Choose Accelebrate, and receive hands-on, engaging training precisely tailored to your goals and audience! Our on-site training offerings range from ASP.NET training and SharePoint training to courses on ColdFusion, Java™, C#, VB.NET, SQL Server, and more. Accelebrate.com
Prototypes with Pizza
“New ribbon, decomposition tree, and AI integration in Power BI Desktop” by Teo Lachev
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2019-11-28 08:49:492021-02-17 01:02:02Atlanta MS BI and Power BI Group Meeting on December 2nd
At Ignite 2019 Microsoft announced the public preview of large datasets in Power BI Premium. This is a significant milestone as now datasets can grow up to the capacity’s maximum memory (previously, the max size was 10 GB with P3 plan), thus opening the possibility of deploying organizational semantic models to Power BI. I consider this feature mostly suitable for organizational BI as I don’t imagine business users dealing with such large data volumes. I tested large datasets during its private preview, and I’d like to share some notes.
The Good
Today, BI developers can deploy organizational semantic models to three Analysis Services Tabular SKUs: SQL Server Analysis Services, Azure Analysis Services, and now Power BI Premium. SQL Server Analysis Services is the Microsoft on-prem offering and it aligns with the SQL Server release schedule. Traditionally, Azure Analysis Services has been the choice for cloud (PaaS) deployments. However, caught in the middle between SQL Server and Power BI, the AAS future is now uncertain given that Microsoft wants to make Power BI as your one-stop destination for all your BI needs. From a strategic perspective, it makes sense to consider Power BI Premium for deploying organizational semantic models because of the following main benefits:
Always on the latest – Both AAS and SQL Server lag in features compared to Power BI Premium. For example, composite models and aggregations are not in SQL Server 2019 and Azure Analysis Services. By deploying to Power BI, which is also powered by Analysis Services Tabular, your models will always be on the latest and greatest.
Feature parity – As I explain in my “Power BI Feature Discrepancies for Data Acquisition” blog, some Power BI features, such as Quick Insights, Explain Increase/Decrease, Power Query, are not supported with live connections to Analysis Services. By hosting your models in Power BI Premiums, these features are now supported because Power BI owns the data, just like you import data in Power BI Desktop and then publish the model.
The Bad
As a Power BI Premium feature, large datasets will require planning and purchasing a premium capacity. Given that you need at least twice the memory to fully process a model (less memory should be required if you process incrementally), you must size accordingly. For example, a 15 GB model would require at least 30 GB of memory to fully process, bringing you into the P2 plan territory. Memory is the most important constraint for Tabular. Unlike SQL Server, which doesn’t license by memory (you can add as much memory you like without paying a dime more in licensing fees), Power BI Power BI Premium plans cap the capacity memory. So, you’ll end up having a dedicated P1 or P2 plan for hosting your organizational semantic model, and another P plan(s) for self-service BI.
I’d like to see elastic scaling happening to Power BI Premium at some point in future. Instead of boxing me into a specific plan, which more than likely will be underutilized, I’d like to see Power BI Premium scaling up and down on demand. This should help lowering the cost.
The Ugly
The lack of DevOps in Power BI Premium will put another hole into your budget. Unlike SQL Server, where you pay only for production use, no special DEV or QA environments and licensing options exist in Power BI Premium. So, you must plan for additional premium capacities, such as for three separate capacities: PROD, DEV, and QA (I know of organizations that need many more DevOps environments). At this price point, even large organizations will reconsider the licensing cost of hosting their models in Power BI. How about leaving QA and DEV on prem? This would require coding for the least common denominator which defeats the benefit of deploying to Power BI Premium. You can get innovative and attempt to reduce licensing cost by purchasing Azure A plans for DEV and QA and stopping the A capacities when they are not in use, but I wonder how many organizations will be willing to go through the pain of doing this. The Cloud should make things easier, right?
Large datasets will open another deployment option for hosting organizational semantic models. This might be an attractive option for some organizations and ISVs. Others will find that staying on-prem could lower their licensing cost. Once the Power BI Premium XMLA endpoint supports write operations (promised for December 2019 in the roadmap), BI developers can use a tool of their choice, such as Tabular Editor or Visual Studio (I personally find Power BI Desktop not suitable for organizational model development, mainly because of its slow performance, lack of source control and extensibility) to develop and deploy semantic models that are always on the latest features and unifying BI on a single platform: Power BI.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2019-11-10 10:24:122019-11-10 10:24:12Power BI Large Datasets: The Good, the Bad, and the Ugly
