Atlanta BI fans, please join us in person for the next meeting on Monday, March 4th at 6:30 PM ET. The famous Patrick LeBlanc (Guy in the Cube) will take a deep dive into the Microsoft Fabric ecosystem, from Lakehouse to Warehouses and Power BI, ensuring you can make informed decisions about your data processing needs. Your humble correspondent will help you catch up on Microsoft BI latest. CloudStaff.ai will sponsor the event. For more details and sign up, visit our group page.
Presentation: Navigating Microsoft Fabric – Choosing the Right Workload for Your Needs
Delivery: In-person
Date: March 4
Time: 18:30 – 20:30 ET
Level: Beginner/Intermediate
Food: Pizza and drinks
Agenda:
18:15-18:30 Registration and networking
18:30-19:00 Organizer and sponsor time (events, Microsoft BI latest, sponsor marketing)
19:00-20:15 Main presentation
20:15-20:30 Q&A
Overview: As businesses transition to the cloud and leverage advanced analytics, understanding the nuances of data infrastructure becomes paramount. Microsoft Fabric offers a suite of powerful tools designed to handle various data workloads, but the key to harnessing its full potential lies in understanding which tool to use and when. This session provides a deep dive into the Microsoft Fabric ecosystem, from Lakehouse to Warehouses and Power BI, ensuring that participants can make informed decisions about their data processing needs. We’ll also look at current limitations that will help guide you.
Speaker: Patrick LeBlanc is a currently a Principal Program Manager at Microsoft and a contributing partner to Guy in a Cube. Along with his 15+ years’ experience in IT he holds a Master of Science degree from Louisiana State University. He is the author and co-author of five SQL Server books. Prior to joining Microsoft, he was awarded Microsoft MVP award for his contributions to the community. Patrick is a regular speaker at many SQL Server Conferences and Community events.
Sponsor: CloudStaff.ai
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2024-02-27 08:11:522024-02-27 08:11:52Atlanta Microsoft BI Group Meeting on March 4th (Navigating Microsoft Fabric – Choosing the Right Workload for Your Needs)
Last year my wife and I did a tour of Greece, and we had a blast. Greece, of course, is the place to go if you are interested in ancient history and the origin of democracy. One of the places we visited was Delphi. The ancient Greeks believed it to be the center of the universe. Now not much was left of it except lots of ruins and imagination. But back then it was magnificent. People from all over the world would come to consult with the Oracle of Delphi. She delivered her prophecies from the temple of Apollo, which had three inscriptions, with one of them being “Know thyself”. The practical benefit for the oracle was that if you believed her cryptic prophecy wasn’t fulfilled then your interpretation was wrong. Therefore, the problem was in you because you didn’t know yourself.
How does this translate into BI? I see clients overly excited about Microsoft Fabric/Power BI Premium, believing that bundling features will solve all their issues. But knowing your organization, ask yourself if your users would use all these features to justify the premium price. A case in point: Power BI source control via workspace Git integration: a feature that appear to be created from developers for developers. Kristyna Hughes did a great presentation for our Atlanta BI Group on Monday covering how developers can take the most of this feature.
Given the self-service focus of Power BI, however, I doubt that data analysts would subject themselves to learning Azure DevOps, Visual Studio Code, and Git CI/CD. Yet, Power BI source control has been in demand since the beginning with the most common ask – the ability to roll back changes.
Here is my take to simplify Power BI source control for regular users:
Power BI Premium/PPU/Fabric clients
If you are on Power BI Premium, set up a branch for each workspace that you want to put under source control, and configure the workspaces for Git integration.
Let business users publish changes as usual.
Periodically and as a part of the change management process, the workspace admin approves the changes and commits them to source control. I hope one day Power BI would transparently commit changes to Git as Azure Data Factory does it, without requiring explicit synchronization. Meanwhile, the admin must manually commit.
Someone privileged to Azure DevOps would need to roll back changes if needed. Again, I hope one day history review, compare, and roll back will be baked in Power BI.
Power BI Pro clients
Once this feature is generally available, embrace Power BI Desktop projects.
When significant changes are made, back up report and model.bim json files to some location, such as OneDrive which has built-in version control.
Replace the project files when you need to roll back changes. Again, this “poor man” source control emphasizes simplicity and saves premium licenses.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2024-02-08 14:40:172024-02-08 14:40:17Know Thyself: Power BI Source Control
What a better way to spend a lazy holiday afternoon than to do more Fabric performance testing? In my previous post, I shared my results from a single-threaded ETL load test to gauge the F2 ingest performance and F2 did pretty well (or at least outperformed Azure SQL DB). Will F2 hold as parallelism increases? Throughput testing is especially important for report loads because parallel tasks can run within a report, such as visuals executing DAX queries in parallel, and across reports, such as when concurrent report requests overlap.
I used the artifacts are included in the “Microsoft Dashboard in a Day” for this test and load tested only the first report page.
The Sales fact table in the semantic model has over seven million rows so it represents a good size dataset. Naturally, the more involved the report is and the more data the semantic model has, the more CPU power and parallelism are needed. I used the Microsoft Power BI Dedicated Capacity Load Assessment Tool and configured it to filter the report on different years in order to avoid report caching. I ran four tests for 1, 2, 3 and 4 virtual users with no think time, and each test ran for 10 minutes.
Here are the results:
Users
Total report renders
Renders per user
1
63
1×63
2
100
2×50
3
135
3×45
4
164
4×41
Here are some additional findings:
Within the first minute or so, F2 generates reports fast, presumably because bursting comes into play to let F2 borrow and recruit more CPU resources. As the sustained load continues, Fabric starts scaling back and throttling CPU.
As time goes by, report executions are getting increasingly slower. While during the first minute a report can take 1-2 seconds for example, later it might take as much as 40 seconds to render (users are unlikely to tolerate this). This happens even with one virtual user, presumably because the quarter of the core is insufficient.
I haven’t encountered any errors. All report executions succeeded irrespective of how long they take.
What all these tests mean is that if Fabric is appealing to you, F2 can be a viable option for smaller organizations where report users are expected to run reports sporadically. In case of a sudden load, such as everyone running reports at 8 AM on Monday, Fabric bursting can elevate the pressure for the first minute or so. Of course, you need to weigh in many other factors, such as relenting control to Microsoft, waiting for the technology to mature, avoiding lock-in, evaluating budget (note that viewers would still need at least Power BI Pro individual licenses for capacities lower than F64), and various other considerations I covered in my previous Fabric-related posts.
As inspired by Amir Netz‘s encouragement to partners to test the Fabric F2 capacity performance, I got on a quest to test what it would do to ETL loads for Fabric Warehouse. I must admit that I was skeptical that a quarter of a core would take a warehouse off the ground, but as usual, life proved me wrong and “wrong” is a big understatement of what happened.
After provisioning a Fabric F2 capacity and a warehouse, I settled on the Retail Data Model for World Wide Importers sample star schema dataset consisting of five dimension tables and one fact table. In terms of performance, I was mostly interested in how long it would take for the ADF copy activity to insert all the data (50 million rows) in the fact table. Granted, it’s a limited test but enough to rule out the technology for real-life projects. Then, I compared the performance against Azure SQL Database Serverless running on up to 2 cores and provisioned by the free trial offer that Microsoft has on Azure. To exclude impact on data transfer between regions, both technologies were provisioned on East US 2 data region, which is the region where my Power BI tenant is hosted on.
Much to my surprise, it took less than two minutes to load all 50 million rows in F2, whereas it took 1 hour to load to load 27 million rows to Azure SQL Database before the maximum 30 GB disk space was exhausted! I couldn’t believe it so I ran the test three times to confirm. Surely, bursting helps a lot! Now, throughput would be a different story, but as far as the warehouse is concerned, it doesn’t matter because in most cases, data will be imported in a Power BI semantic model and the warehouse will be out of the picture. As a next step, I plan to test the report throughput to see what concurrent report load would saturate the F2 capacity.
In conclusion, the Fabric lowest capacity F2 ($262.80 monthly cost) could be a viable option for smaller organizations willing to make their foray in the Fabric world. On the downside, we must leave Fabric to marinate for a few months and add needed features, including surrogate keys and MERGE for Warehouse and on-prem connectivity for Azure Data Factory, in order to be in consideration for real-life projects. More tests are needed to gauge the F2 report throughput.
UPDATE 12/24/2023 I was curious how much loading the same dataset from a CSV file would impact performance. It took much longer: 18 minutes. The most significant factor was that loading from CVS requires staging to a data lake although this appears redundant because the CVS file was in a lakehouse in the same Power BI workspace. ADF spent a total of 18 minutes in the two-staged copy (ten minutes to stage the data and eight minutes to load the fact table from the staged copy). Therefore, Parquet outperformed significantly CVS, probably because the Microsoft-provided Parquet file was compressed.
I’ve covered my first impression about Microsoft Fabric in a series of blogs starting with this one. In the recap, I said that certain features might benefit organizations that are already on Power BI Premium because all Fabric features are available in Power BI Premium plans. However, as they stand, features such as Lakehouse Copy to Table (no automated synchronization), ADF pipelines (no connectivity to on-prem data sources), Data Warehouse (missing important T-SQL features), Direct Lake (only available online), are half-baked, thus barring wide-spread Fabric adoption. This newsletter covers a good case for Fabric that I’ve recommended for a large insurer that has invested heavily in Microsoft Dynamics 365 and Power BI Premium. I’ll be in a better position to confirm after a POC with larger datasets so follow my blog for future updates.
The Dynamics Integration Saga
Dynamics Online, aka Dynamics 365, epitomizes the customer’s struggle to export their data hosted in SaaS cloud offerings for analytics or other purposes. Since unfortunately Microsoft doesn’t provide direct access to the Dynamics native storage (Azure SQL Database), which often is the best solution, Dynamics has “compensated” throughout the years by provided the following options:
Requires Fabric licensing; up to 60 min data sync delay; TBD
One of my clients, a large insurance company, has invested heavily in Dynamics 365. They have implemented various Power BI reports that would import millions of rows directly from common CRM entities, such as Account, Opportunity, as well as custom entities, using the OData API. The main struggle has always been that dataset refreshes take hours to complete. Because API calls don’t fold in Power Query, they apply REST operations to select a subset of columns, join tables, and filter data. They rely heavily on Power Query to shape the data which has worked reasonably well.
Dataverse Link to Fabric
Dataverse Link to Fabric looks promising in addressing some of the above pitfalls. Once you set it up, it extracts Dynamics data as Delta tables in a Fabric lakehouse. From there, you can use the SQL endpoint to join and filter tables.
After the initial synchronization, it might take up to 60 minutes to synchronize data changes in Dynamics so not really real-time data access but much better than the current state.
While working through the setup, keep the following in mind:
The Link to Microsoft Fabric menu is found under the Analyze menu in the ribbon and not at the table level as the video shows. That’s because it exports all the tables.
Referring to the comparison table between Fabric Link and Synapse Link, “No copy, no ETL direct integration with Microsoft Fabric” should be read as “No ETL” because the data is still copied. Further, “Data stays in Dataverse” should read as “Data is automatically copied to Fabric lakehouse”.
As far as prerequisites, the most important one is “the workspace you choose to link with Dataverse must be assigned to a premium capacity in the same region as your Dataverse environment” with the emphasis on the “same region”. Not having them in the same region is a show stopper.
Cutting Cost
What if you are not on Power BI Premium and you are on a tight budget? Although I haven’t tested, this approach (suggested by Riccardo Perico) might work because Link to Fabric is available in all fabric capacities:
After the initial synchronization, pause and resume the capacity when not in use, such by using this approach.
Import the data in a Power BI semantic model.
Dataverse Link to Fabric should queue the updates until the capacity is resumed.
Benefits
Again more testing is needed, but at this point I see the following advantages of using the Dataverse Link to Fabric:
CRM data is staged in open file format (Delta Parquet tables) and available for any reporting needs without impacting Dynamics.
No need to use APIs. Instead, you can use SQL to join and filter tables, such as to look up columns or filter data, which is much better than using the API syntax. This will also help you centralize column lookups in SQL views instead of doing this over and over for each report.
Potentially much faster Power BI dataset refreshes
No additional cost to Power BI Premium customers because the Fabric features are available in Power BI Premium.
I might have identified at last a good case for Microsoft Fabric, but I’ll be in a better position to confirm after a POC with larger datasets. Dynamics Online, aka Dynamics 365, epitomizes the customer’s struggle to export their data hosted in SaaS cloud offerings for analytics or other purposes. Since unfortunately Microsoft doesn’t provide direct access to the Dynamics native storage (Azure SQL Database), which often could be the simplest and fastest solution, Dynamics has “compensated” throughout the years by introducing and sunsetting various options:
Requires Fabric licensing; up to 60 min data sync delay; TBD
One of my clients, a large insurance company, has invested heavily in Dynamics 365. They have implemented various Power BI reports that would import millions of rows directly (without data staging) from common CRM entities, such as Account, Opportunity, as well as custom entities, using the OData API. The main struggle has always been that dataset refreshes take hours to complete. Because API calls don’t fold in Power Query, they apply REST operations to select a subset of columns, join tables, and filter data. They rely heavily on Power Query to shape the data which has worked reasonably well.
Dataverse Link to Fabric looks promising in addressing some of the above pitfalls. Once you set it up, it extracts Dynamics data as Delta tables in a Fabric lakehouse. From there, you can use the SQL endpoint to join and filter tables. After the initial synchronization, it might take up to 60 minutes to synchronize data changes in Dynamics so not really real-time data access but much better than the current state.
While working through the setup, keep the following in mind:
The Link to Microsoft Fabric menu is found under the Analyze menu in the ribbon and not at the table level as the video shows. That’s because it exports all the tables.
Referring to the comparison table between Fabric Link and Synapse Link, “No copy, no ETL direct integration with Microsoft Fabric” should be read “No ETL” because the data is still copied. Further, “Data stays in Dataverse” should read “Data is automatically copied to Fabric lakehouse”. Dataverse is just a wrapper on top of Azure SQL Database.
As far as prerequisites, the most important one is “the workspace you choose to link with Dataverse must be assigned to a premium capacity in the same region as your Dataverse environment” with the emphasis on the “same region”. Not having them in the same region is a show stopper.
Again more testing is needed, but at this point I see the following advantages of using the Dataverse Link to Fabric:
CRM data is staged in open file format (Delta Parquet tables) and available for any reporting needs without impacting Dynamics.
No need to use APIs. Instead, you can use SQL to join and filter tables, such as to look up columns or filter data, which is much better than using the API syntax. This will also help you centralize column lookups in SQL views instead of doing this over and over for each report.
Potentially much faster Power BI dataset refreshes
No additional cost to Power BI Premium customers because the Fabric features are available in Power BI Premium.
In a long term bypass importing data and providing users with almost real time (CRM data changes might take up to 60 minutes to synchronize) when the Microsoft DirectLake technology matures. I’m personally very interested in this option but I’ll wait until Power BI Desktop supports it.
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2023-12-07 15:30:462023-12-07 15:30:46A Case for Microsoft Fabric: Dynamics 365 Analytics
Atlanta BI fans, please join us for the next meeting on Monday, December 4th, at 6:30 PM ET. William Rodriguez will review the key Fabric components whilst walking through a full Financial deployment: data engineering with a tiered medallion architecture, data science with forecasting and other advanced analytics, and data analysis with Power BI. Your humble correspondent will help you catch up on Microsoft BI latest. For more details and sign up, visit our group page.
PLEASE NOTE A CHANGE TO OUR MEETING POLICY. WE HAVE DISCONTINUED ONLINE MEETINGS VIA TEAMS. THIS GROUP MEETS ONLY IN PERSON. WE WON’T RECORD MEETINGS ANYMORE. THEREFORE, AS DURING THE PRE-PANDEMIC TIMES, PLEASE RSVP AND ATTEND IN PERSON IF YOU ARE INTERESTED IN THIS MEETING.
Presentation: Financial Modelling in Microsoft Fabric
Delivery: In-person
Date: December 4
Time: 18:30 – 20:30 ET
Level: Intermediate
Food: TBD
Agenda:
18:15-18:30 Registration and networking
18:30-19:00 Organizer and sponsor time (events, Power BI latest, sponsor marketing)
19:00-20:15 Main presentation
20:15-20:30 Q&A
Venue
Improving Office
11675 Rainwater Dr
Suite #100
Alpharetta, GA 30009
Overview: Fabric is a powerful integrated BI platform. This presentation will review they key components whilst walking through a full Financial deployment: data engineering with a tiered medallion architecture, data science with forecasting and other advanced analytics, and data analysis with Power BI.
Speaker: William Rodriguez is the founder and lead consultant of Analytical Ants, an analytics company focused on procuring insights via data engineering, data science, and data analysis. William has led multi-million-dollar construction projects, acted as financial controller managing million-dollar monthly check productions, and built and deployed BI infrastructures at companies large and ‘small’ ($60M Revenue). Academically, he has his master’s in business, two undergraduate business degrees, four active Microsoft certifications, and over 70 accredited SQLBI training hours. William loves spending time with his amazing family and knows that he would be nowhere without Christ.
Sponsor: TBD
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2023-11-28 17:03:382023-11-29 19:48:18Atlanta Microsoft BI Group Meeting on December 4th (Financial Modelling in Microsoft Fabric)
Microsoft Fabric is upon us with a grand fanfare. You can get a good overview of its vision and capabilities by watching the Microsoft Fabric Launch Digital Event (Day 1) and Microsoft Fabric Launch Digital Event (Day 2) recordings. Consultants and experts are extolling its virtues and busy fully aligning with Microsoft. There is a lot of stuff going on in Fabric and I’m planning to cover the technologies I work with and care about in more detail in future posts as Microsoft reveals more what’s under the kimono. This post is about my overall impression on Fabric, in an attempt to cut through the dopamine and adrenaline-infused marketing hype. As always, please feel free to disagree and provide constructive criticism.
The Good
Let’s just say that after 30 years working with Microsoft technologies, I’m very, very skeptical when I hear loaded terms, like “revolutionary”, “one-something”, “never has been done before”, etc. We all witnessed impressive launches for products that wouldn’t last a year. But it looks like this time Microsoft got their act together and put something that may pass the test of time and that I could recommend or use to help clients. As a starter, I’m glad that we’ve finally settled on a common and open storage (delta and Parquet) after years of experimenting with proprietary and open formats (CDM folders anyone?). This common storage has several advantages, including accessibility, portability, and virtualization.
I also like very much that Microsoft doesn’t enforce or propel a specific architecture or data flow pattern. If you want a lakehouse, sure you can have it. Care about medallion file organization? Sure, you can do that. Don’t want a lakehouse but data warehouse if you don’t deal with files and you don’t like a notebook with a blinking cursor? Not a problem. Want to skip staging data as files to the lake and load it directly in the warehouse? Fine. This is very different approach than other vendors take, such as to promote data warehousing on top of lakehouses and/or rule out relational databases whatsoever (read my thoughts on this here).
It’s obvious that a gigantic effort has taken place to unify and in same cases rewrite products, such as Analysis Services and Synapse Data Warehouse, to adhere to this new platform and vision. Basically, Fabric is the focal point of decades of hard work from all Microsoft teams involved in analytics to at least make a complicate data estate easy to access and manage.
The Bad
Going back to the presentation and my skepticism, I wish Microsoft could dialed down on some promises, like “one copy” of data. Anyone who has implemented a data warehouse of a decent complexity knows that data duplication is necessary. Data exists in the source systems, needs to be staged, and then transformed. Right there we have three copies. True, virtualization might help us avoid some data movement scenarios, such as accessing data directly in S3 buckets or importing in a Power BI dataset (for most companies a few extra minutes for refreshing datasets is not an issue).
Speaking of companies, it’s clear that Fabric (and presenters in the videos) targets the needs of large organizations with complex integration scenarios. But for most organizations “Big Data” is a few million rows and most common integration task is analyzing data from one or multiple ERPs. Should they care about Fabric? I guess it would really depend on its value proposition and budgets, but Fabric pricing hasn’t been announced yet. If Fabric is not available in PPU (Premium Per User), it probably would be dead on arrival for smaller organizations, as they can get modern analytics by spending less than $200/month on infrastructure excluding Power BI per-user licenses.
Finally, although presenters highlighted avoiding vendor lock-in as one of the major benefits of Fabric, you’re going to put all your eggs in one basket: Power BI/Fabric. Making Power BI a one-stop destination for analytics makes of course a lot of sense to Microsoft and increases its revenue potential (nothing wrong with revenue if it brings value). But for you Fabric would be a long-term commitment and you better make sure you avoid Microsoft-proprietary features as much as you can, such as Power Query dataflows and Azure Factory dataflows, should one day you decide to divest from Fabric, Power BI, or even Azure. Otherwise, you might find yourself in a similar situation as this client who had to migrate hundreds of Alteryx flows.
The Ugly
Confusion has descended upon the BI land after Microsoft throws and abandons products left and right. In fact, the Fabric documentation has sections to help you choose product, such as Lakehouse, New Synapse data warehouse, Power BI datamart (that one is easy, stay away from it especially if you plan to adopt Fabric). Should we add Synapse Dedicated Pools and Azure SQL Database to the comparison table?
Further, rewriting these engines means that we must go back to square one and wait for features. For example, the new Synapse data warehouse lacks so many T-SQL features and outside my plans for any near-term projects. Just when I thought Synapse SQL dedicated pools were caching up on T-SQL parity, someone moved my cheese… Well, good things happen to those who wait, so let’s give Fabric a year or so.
Atlanta BI fans, please join us for the next meeting on Monday, September 11th, at 6:30 PM ET. Shabnam Waston (BI Consultant and Microsoft MVP) will introduce us to the Lakehouse engine in Microsoft Fabric. Shabnam will also sponsor the meeting. Your humble correspondent will help you catch up on Microsoft BI latest. For more details and sign up, visit our group page.
PLEASE NOTE A CHANGE TO OUR MEETING POLICY. WE HAVE DISCONTINUED ONLINE MEETINGS VIA TEAMS. THIS GROUP MEETS ONLY IN PERSON. WE WON’T RECORD MEETINGS ANYMORE. THEREFORE, AS DURING THE PRE-PANDEMIC TIMES, PLEASE RSVP AND ATTEND IN PERSON IF YOU ARE INTERESTED IN THIS MEETING.
Presentation: Introducing Lakehouse in Microsoft Fabric
Delivery: Onsite
Date: September 11th
Time: 18:30 – 20:30 ET
Level: Beginner to Intermediate
Food: Sponsor wanted
Agenda:
18:15-18:30 Registration and networking
18:30-19:00 Organizer and sponsor time (events, Power BI latest, sponsor marketing)
19:00-20:15 Main presentation
20:15-20:30 Q&A
VENUE
Improving Office
11675 Rainwater Dr
Suite #100
Alpharetta, GA 30009
Overview: Join this session to learn about Lakehouse architecture in Microsoft Fabric. Microsoft Fabric is an end-to-end big data analytics platform that offers many capabilities including data integration, data engineering, data science, data lake, data warehouse, and many more, all in one unified SaaS model. In this session, you will learn how to create a lakehouse in Microsoft Fabric, load it with sample data using Notebooks/Pipelines, and work with its built-in SQL Endpoint as well as its default Power BI dataset which uses a brand-new storage mode called Direct Lake.
Speaker: Shabnam Watson is a Business Intelligence consultant, speaker, blogger, and Microsoft Data Platform MVP with 20+ years of experience developing Data Warehouse and Business Intelligence solutions. Her work focus within the Microsoft BI Stack has been on Analysis Services and Power BI and most recently on Azure Synapse Analytics. She has worked across several industries including Supply Chain, Finance, Retail, Insurance, and Health Care. Her areas of interest include Power BI, Analysis Services, Performance Tuning, PowerShell, DevOps, Azure, Natural Language Processing, and AI. She is a regular speaker and volunteer at national and local user groups and conferences. She holds a bachelor’s degree in computer engineering and a master’s degree in computer science.
Sponsor: Shabnam Watson
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2023-09-05 17:01:182023-09-05 17:01:18Atlanta Microsoft BI Group Meeting on September 11th (Introducing Lakehouse in Microsoft Fabric)
Did I disappoint you? Or leave a bad taste in your mouth? You act like you never had love And you want me to go without
U2
In previous posts, I shared my initial impression of the recently announced Microsoft Fabric and its main engines. Now that we have the Fabric licensing and pricing, I’m ready to wrap up my review with a few parting notes. Here is how I plan to position Fabric to my clients:
Enterprise clients
These clients have complex data integration needs. More than likely, they are already on a Power BI Premium contract and highly-discounted pricing model that is reviewed and renewed annually with Microsoft. Given that Fabric can be enabled on premium capacities, you should definitely consider it selectively when it makes sense. For now, I believe a good case can be made for data lake and lakehouse if that’s your thing.
Now you have an alternative to Databricks and you can standardize BI on one platform and vendor.
I don’t have experience in Databricks to offer more in-depth comparison, but in my opinion the most compelling features to favor Fabric for now are:
No additional cost or Power BI Premium capacity upgrade if you aren’t reaching the workload limits
One platform and one vendor to avoid the blame game when things don’t work
Fast Direct Lake data access for ad-hoc analysis directly on top of files in the lakehouse
Easy data virtualization
If you decide in Fabric’s favor, you’d be wise to reduce dependencies on Microsoft proprietary and bundled features, such as Power Query dataflows and data pipelines insides Fabric (I’d use a stand-alone ADF instance once ADF supports Fabric). Hopefully, bring-your-own-lake will appear on day to circumvent the Fabric OneLake shortcomings.
Small and medium-size clients
Unfortunately, Microsoft didn’t make Fabric available with PPU (premium-per-user) licensing. This would surely put it out of reach for smaller organizations. True, you can purchase a Fabric F2 license for as little as $262/month and run it on a quarter of a core. I didn’t know a quarter of a core existed, but Microsoft did it, although you probably won’t get too far with it for production use (see results from my F2 limited performance tests here). You can opt for a higher SKU, but it would increase your bill and Fabric capacities can’t be auto-paused. For example, a “luxurious” 1 core (F8 plan) will put you in the 1K/month range, plus Power BI Pro licenses for all users (contributors and viewers).
But fear not. There is nothing in Fabric that you desperately need or can’t obtain outside Fabric in a much more cost-effective way.
Expect Microsoft to push Fabric aggressively. However, I believe Fabric has more appeal for large organizations while low-budged simple solutions with Power BI Pro or PPU licensing would likely better address your needs. And your BI solution is still going to be “modern”, whatever that means…
https://prologika.com/wp-content/uploads/2016/01/logo.png00Prologika - Teo Lachevhttps://prologika.com/wp-content/uploads/2016/01/logo.pngPrologika - Teo Lachev2023-07-30 17:28:402024-01-15 15:57:49A First Look at Microsoft Fabric: Recap
I’ve covered my first impression about Microsoft Fabric in a 
