PASS Summit 2017 Day 1

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Day one of the PASS Summit has ended and wow, what a great day! Not only because of the great sessions and awesome keynote, but also because we met many people from the Microsoft product teams and the community. PASS Summit is so much more than an event to learn!

In this first blog post of a series of 3, Dave and I will highlight important keynote announcements, zoom into what the “Industrial Revolution 4.0.” brings us, describe how you can deliver enterprise BI on big data with Azure Analysis Services and tell you why you should attend the focus group sessions in which you can provide direct feedback to the product teams!

Jorg Klein Dave Ruijter


Keynote by Rohan Kumar, General Manager Database Systems

Rohan started by pointing out that Data, Cloud and AI are the most disruptive technologies at the moment. The Microsoft “Modern Data Estate” focuses on hybrid scenarios (on-premises + cloud) and making this as seamless as possible. The cloud-first approach still stands with many new features being added to Azure SQL Database, but enabling hybrid scenarios with SQL Server is just as important as “hybrid is a key principle”. The new release cadence of SQL Server is a clear example of this, SQL Server 2017 came just 16 months after the release of SQL Server 2016.

Some highlights of SQL Server 2017 are that it’s available on both Windows Server and Linux and it can now be part of a Docker container. Automatic query tuning is now available in SQL Server 2017 and Azure SQL Database. SQL Server is the number 1 on OLTP and DW performance. Not only R but also Python is now built-in. Python is very important because many deep learning GPU libraries are Python based.

Migrating on-premises SQL Server based solutions to Azure is easier than ever with the new Database Migration Service. You can streamline SQL Server database migrations to Azure SQL Database using the new Azure SQL Database Managed Instance which really enables lift and shift scenarios. It offers an entire SQL instance with the PaaS benefits.

SQL Server Integration Services in Azure also enables lifting and shifting your on-prem SSIS ETL solutions to Azure. Azure Data Factory v2 provides a managed environment for SSIS execution. SSIS Azure PaaS enables you to pick the number of nodes and node size, hourly priced with no SQL Server license requirements. Next to Azure, SSIS offers the same runtime across Windows and Linux.

Scott Currie went on stage to announce full native BIML support for Azure Data Factory V2. It will be possible to generate gateways, pipelines, datasets, etc. Awesome!

Create ADF Assets BIML

Cristian Wade showed us the NYC taxi dataset demonstration (10bn rows, 10TB) inside Power BI with a Live Connection to the Azure Analysis Services data model (S4 tier if we saw it correctly). Switching to the Azure Portal he casually shows us how easy it now is to scale out your data model to up to 7 read-only instances, using a slider! Great implementation, especially knowing how hard this is to setup on-premises! Christian also announced (Azure) Analysis Services now contains the same connectivity stack (data connectors) as Power BI, making it possible to ‘upgrade’ a Power BI Desktop data model to Azure Analysis Services. Without a doubt his keynote demo was the coolest and most appreciated, judging by the amount of applause.

During the keynote Tobias Ternström announced a new tool called Microsoft SQL Operations Studio. This is a lightweight modern data operations tool for SQL which runs everywhere: Windows, Mac and Linux. Previously known as Project Carbon. It will be available in a few weeks.

Julie Strauss from the Azure SQL Data Warehouse team presented the new compute optimized tier which offers amazing performance when querying tens or hundreds of terabytes of data. It can spin up thousands of compute nodes in seconds.

Riccardo Muti announced a new version of Power BI Report Server which now offers Scheduled Data Refresh, DirectQuery support, and a new REST API for developers. The accompanying Power BI Desktop version is now aligned with the October release of the public Power BI Desktop, and thus including drillthrough functionality!

For more details about SQL Server 2017 and Azure Data Services, check “The ultimate hybrid data platform” article by Microsoft here.

For more details on the new Power BI Report Server release, check the blogpost about it by Christopher Finlan here.


Microsoft BI – An Integrated Modern Solution by Kamal Hathi

Kamal told about the history of the industrial revolution and the fact we are now entering “stage 4.0” which is all about information, and what you do with it. It is driven by big data, AI, machine learning and cloud.

Industrial Revolution

Kim Manis demo’d exploring data around traffic accidents with Power BI. She showed the great thing about Power BI is that it helps you find out if your assumptions and maybe your bias towards the subject are correct. Kim also pointed out that you don’t need to be a data scientist to be able to apply basic data science using Power BI. For instance you don’t need to know exactly how a clustering algorithm or forecasting model works to be able to apply them to your data.

Patrick Baumgartner and Dean Riddle showed how the Seahawks are using Power BI and a custom App to get feedback and insights about each players personal performance. Nice to see this digital transformation at the Seahawks sports team.


Deliver enterprise BI on big data using Azure Analysis Services by Josh Caplan and Christian Wade

Azure Analysis Services models can be used as a layer between big data platforms like HDInsight Spark, Azure Data Lake Store and Azure SQL Data Warehouse on the one hand and visualization tools like Power BI on the other hand.

Often you see Hub and Spoke architectures where Azure SQL Data Warehouse, Azure Data Lake Store and/or HDInsight forms the Hub and the Spokes are formed by Azure Analysis Services. Using a Hub and Spoke architecture, the majority of users only use a fraction of the data which is stored in the spokes on more expensive high performant storage and compute, while the complete data set is still available in the central Hub on cheaper storage.

Christian Wade gave a demo in which he queried a trillion rows using Power BI with amazing performance. “Slice through one trillion rows as a knife through warm butter”, according to Christian. Technology that powered this demo was based on a HDInsight Spark cluster, used as a DirectQuery data source in Azure Analysis Services which was enhanced with a new exiting feature: hybrid in-memory DirectQuery. Amazing!

Microsoft Power BI focus group sessions

Today we also attended two focus group sessions focused on Power BI. These sessions are organized and led in person by (Senior) Program Managers and provide an extra opportunity for us to help shape the Power BI product! We discussed points we have recently ran into with large-scale Power BI deployments and talked about how to further support the Power BI report lifecycle from an enterprise perspective, Audit Log enhancements, Workspace management and ways to further improve the Report authoring experience. Thanks to Adam, Kim, Will, Nikhil,  Catherine, Ewan and Bethany for running these sessions!

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