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High Performance Analytics with Sunil Agarwal

At Microsoft Ignite 2017, I had planned an interview with Sunil Agarwal, and was very excited about it. Then Sunil asked if he could bring Kevin Farlee. Of course! Then he asked if he could also bring their customer, Aaron Gerdeman from FIS. Even better! :)

In this interview, we chat about SQL Server 2017, Resumable Index Builds, Adaptive Query Processing, Columnstore Indexes, High Availability, Real-time Analytics, Real-time Dashboards and the SQL Tiger Team.

High Performance Analytics with Sunil Agarwal, Kevin Farlee, Aaron Gerdeman

You can learn more in the SQL Server Database Engine Blog, follow Sunil Agarwal on Twitter @S_u_n_e_e_l and follow Kevin Farlee on Twitter @kfarlee.

I’m very happy they all managed to find time to talk to me, hope you enjoy the interview! To learn more, watch Sunil and Aaron’s session Delivering high performance analytics with columnstore index on traditional DW and HTAP workloads from Microsoft Ignite 2017:

Other interviews from Microsoft Ignite 2017

Data Science with Buck Woody
SQL Server 2017 with Bob Ward
Azure Data Factory v2 with Mike Flasko

SQL Server 2017 with Bob Ward

During Microsoft Ignite 2017, I got to interview one of the nicest guys in Microsoft, Bob Ward! :)

In this interview, we chat about SQL Server 2017, SQL Server on Linux, Adaptive Query Processing, Auto Plan Correction and Columnstore Indexes.

SQL Server 2017 with Bob Ward – Microsoft Ignite 2017

You can read all of Bob Ward’s articles on his blog SQL Server According to Bob. Most of his slide decks and demos are published on aka.ms/bobwardms, and you can follow him on Twitter @bobwardms.

I know Bob had a very busy schedule at Microsoft Ignite, so I’m very thankful he was able to spend a few minutes with me! I hope you find this as interesting as I did :) If you want to learn even more, you can watch his session Experience Microsoft SQL Server 2017: The fast and the furious from Microsoft Ignite 2017:

Other interviews from Microsoft Ignite 2017

Data Science with Buck Woody
High Performance Analytics with Sunil Agarwal
Azure Data Factory v2 with Mike Flasko

Data Science with Buck Woody

I got to interview Buck Woody about Data Science at Microsoft Ignite 2017! :)

In this interview, we chat about Microsoft Business Analytics and AI (formerly known as Cortana Intelligence Suite), Artificial Intelligence in Excel, intent-based programming, Predictive Analytics, DevOps for Data Scientists and life-long learning.

Data Science with Buck Woody – Microsoft Ignite 2017

Read all of Buck Woody’s great posts on his blog Backyard Data Science and follow him on Twitter @BuckWoodyMSFT. For more career advice, read his article Your Career is Your Fault on LinkedIn.

Oh, and we did get more coffee after we recorded this :)

I’m so thankful that Buck took some time out of his busy schedule to chat with me, and I hope all of you enjoy this interview. If you want to learn more, watch his full session DevOps for data science from Microsoft Ignite 2017:

Other interviews from Microsoft Ignite 2017

SQL Server 2017 with Bob Ward
High Performance Analytics with Sunil Agarwal
Azure Data Factory v2 with Mike Flasko

Table Partitioning in SQL Server – Partition Switching

This post is part 2 of 2 in the series Table Partitioning in SQL Server
Partition Switching

Inserts, updates and deletes on large tables can be very slow and expensive, cause locking and blocking, and even fill up the transaction log. One of the main benefits of table partitioning is that you can speed up loading and archiving of data by using partition switching.

Partition switching moves entire partitions between tables almost instantly. It is extremely fast because it is a metadata-only operation that updates the location of the data, no data is physically moved. New data can be loaded to separate tables and then switched in, old data can be switched out to separate tables and then archived or purged. All data preparation and manipulation can be done in separate tables without affecting the partitioned table.

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Using a Numbers Table in SQL Server to insert test data (T-SQL Tuesday #65)

T-SQL Tuesday

T-SQL Tuesday #65 is hosted by Mike Donnelly (@SQLMD). There is no specific topic to write about this month, Mike simply wants us to learn something new and then write a blog post to teach it to others. I want to share something that I only recently learned, something I wish I had known about years ago, something that became part of my toolbox as soon as I discovered it: the Numbers Table. It is so simple and solves so many problems that everyone should know about it :)

A Numbers Table (perhaps most known as a Tally Table, sometimes called an Auxiliary Table of Numbers and even referred to as the Swiss Army Knife of SQL Server) is a one-column helper table that contains the numbers 1, 2, 3, 4, 5 and so on all the way up to the-highest-number-you-could-possibly-need.

It can be used to replace slower loops and row-by-row operations with faster set-based operations, generate dates, split strings, find gaps in data sets, expand data sets, insert test data and probably hundreds of other things. There are so many great and detailed articles already published about this topic, so I will stick to the T-SQL Tuesday topic of “Teach Something New” and share the two most recent things I learned: different ways to create a numbers table, and different ways to quickly insert test data by using a numbers table.

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