Blogging from the PASS Summit Keynote #1
6:34 AM PST
I'll be blogging details from the PASS Summit keynote this morning. If you'd rather follow along by video (and I wouldn't hold that against you), there is a live stream of the event here:
People are starting to flow in. I'm going to go "new at the bottom" because I'm sure you're not hitting F5 every four seconds, or you may be reading this after the fact…
Thomas LaRock comes on stage – 50 countries, 2,000 companies represented in this room. Asks for a round of applause for the makers of the best data platform on the planet. There is a PASS Board Q & A on Friday, in 307/308, from 1:00 – 2:15 PM.
First Summit in Chicago in 1999 had 1,200 attendees – this year, 5,899 registrations, the biggest event ever.
He challenges us to get involved, make connections, and grow. Connect. Share. Learn. Go to the Community Zone in 4D. just outside the Exhibit Hall.
Tom thanks partners and sponsors, and suggests you come give vendors a hug in the Exhibit Hall.
The technical portion of the keynote kicks off with a video featuring quotes and thoughts from T.K. "Ranga" Rengarajan (Database / Big Data), Joseph Sirosh (Information Management / Machine Learning), and James Phillips (Azure / BI).
Ranga talks about how data changes our lives, and that there's an opportunity to drive smarter decisions with data. He says that every year, there is 41% more data than the year before.
He talks about capturing and managing data, and that the goal of the Microsoft data platform is to not make compromises (in-memory vs. on-disk, scale-up vs. scale-out, on-premises vs. cloud). Very drawn-out and contrived demo from Pier 1 that demonstrated very cool sharding technology in a very boring way.
- Capture diverse data: DocumentDB, HDInsight (HBase / Apache Storm), APS (formerly known as PDW) / Polybase / Hadoop, Azure Search ("free-wheeling search")
- Achieve elastic scale: SQL Server 2014 has 640 cores / 64 virtual CPUs per VM / 1TB per VM, many more premium SKUs in Azure VMs, Hyper-scale across thousands of DBs in Azure SQL Database
- Maximize performance & availability: Azure SQL DB 99.99% SLA / predictable performance, 2014 investments in In-Memory OLTP, ColumnStore, AlwaysOn
- Simplify with cloud: Hybrid will always be a priority – high effort to make them work seamlessly together
Apparently Ranga grossly misrepresented the way Stack Overflow is using SQL Server technology.
Ranga announces a public preview of SQL Database toward the end of the year – increased T-SQL surface area, large index handling, parallel queries, extended events, and in-memory ColumnStore.
Mike Zwilling gives an all-hands demo of In-Memory and updatable, non-clustered ColumnStore on the same table. And actually shows DDL to create it, including proper schema references. This guy knows the audience.
He previews stretch tables – which allow you to transparently move older data to a cloud database so only your hot data is local, on-prem. Pretty nice (though I hope they also support cold data on some other local storage device). Resources for query processing (a.g. aggregation) against the cold data all happen remotely.
Joesph Sirosh (Information Management / Machine Learning), who came to Microsoft from Amazon, talks about his amazement at the PASS community. Now he wants us to do the wave. Oh boy.
He pitches Azure Data Factory, Azure Stream Analytics, and Azure Machine Learning.
A very energetic Sanjay Soni does another Pier 1 demo – heat map analytics of in-store traffic (using Kinect and PowerMap, of course) to determine "popular" products based on lingering and then real-time activity based on past behavior.
James Phillips (Azure / BI), who started CouchBase before moving to Microsoft two years ago, jokes that to top the wave he'd have to drop cash from the ceiling. Still looking up and waiting.
- Simplify data discovery: Power Query and Power Pivot.
- Deliver faster time to insight: Power BI, Q&A (Natural language query)
- Connect to on-premises: Data Refresh (schedule for Power BI), Interactive Query (Power BI over SSAS)
- Enable data culture: Live dashboards & drill-through (with demo).