I traveling thru America’s Renaissance City to present at SQL Saturday #575 in Smithfield, RI. It will be a good time to meet old friends, make new ones and learn something new. I would like the opportunity to thank Bryant University for allowing the two Rhode Island user groups to use their fine campus.
Here are the details behind the first presentation that I gave that day.
Public Preview of SQL on Linux
There was a lot of excitement at the Connect() developer conference in November 2016. Two major announcements were made at the conference.
First, visual studio code now runs on Windows, Linux and Mac. Second, SQL Server v.Next is coming to Linux. This means a developer can
develop code against SQL Server in a Window less environment. If you are really passionate about Linux, join the hundreds downloading and testing this preview release.
1 – Core code deployed for multiple environments.
2 – Installs on Red Hat and Ubuntu flavors of linux.
3 – Generate ssh key.
4 – Deploy standard Red Hat image.
5 – Install core engine and tools on linux.
6 – Connect to engine via sqlcmd.
7 – Open firewall for external access.
8 – Create database on Linux via SSMS in windows.
9 – Load data into table via bcp.
10 – Supports docker (container) images.
11 – Current limitations.
12 – Future road map.
Here are the details behind the second presentation I gave that day.
Effective Data Warehouse Storage Patterns
Many companies start off with a simple data mart for reporting. As the company grows, users become dependent on the data mart for monitoring and making decisions on Key Performance Indicators (KPI).
Unexpected information growth in your data mart may lead to a performance impacted reporting system. In short, your users will be lining up at your cube for their daily reports.
How do you reduce the size of your data mart and speed up data retrieval?
This presentation will review the following techniques to fix your woes.
1 – What is horizontal partitioning?
2 – Database sharding for daily information.
3 – Working with files and file groups.
3 – Partitioned views for performance.
4 – Table and Index partitions.
5 – Row Data Compression.
6 – Page Data Compression.
7 – Programming a sliding window.
8 – What are Federations in Azure SQL?