Personal Development
Steve Jones thinks that a personal development plan is important and talks today a little about how you should build one.
Guidelines for Using Natively-Compiled Stored Procedures in SSIS Packages
As you may know, SQL Server In-Memory OLTP introduced in SQL Server 2014 offers great performance improvements for ETL processes. In this tip we cover techniques you need to know about various behaviors of SQL Server In-Memory OLTP depending on the options you select.
Minimal Meetings
Too many meetings happen in software teams. Steve Jones says that when scheduling meeting, you should be aware of the cost, and only include those people that need to be there.
Templates and teamwork
SQL Server expert David Poole discusses how teams can work together and share templates in Management Studio.
Explaining The SQL Server 2014 Analysis Services Data Mining Model Lift Chart
In this tip, Dallas Snider explains how to interpret the Lift Chart found on the Mining Accuracy tab of a SQL Server 2014 Analysis Services Data Mining structure.
SSIS 2012 Projects: Deployment Configurations and Monitoring
The Project Deployment Model introduced in SSIS 2012 speeds up the deployment of database projects in which there may be hundreds of SSIS packages per project. Not only that, but deployments can be configured differently for each environments such as test and staging, and there are now ways of monitoring the status and performance of packages and of versioning the SSIS Catalog.
Consolidating Again and Again and Again
This editorial was originally published on November 12, 2009. It is being re-run as Steve is on holiday. Virtualization is touted as a great way to save money, but it's a one time event. Once you've consolidated a server, you can't do it again. However consolidation isn't necessarily the same and Steve Jones tells us why.
Using SQL Server Stored Procedures in SSIS Data Flow Sources
A technique to deal with lack of metadata for stored procedures when used with SSIS.
Building an Automated Database Deployment Pipeline
Data and databases are historically ignored or given a low priority within the processes of ALM and DevOps. This situation needs to change and the primary point of the changes is within the database professional part of the team.
Blogs
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Forums
We Are Eating Our Own Seed Corn
Comments posted to this topic are about the item We Are Eating Our Own...
Before Using AI with Business Data, Read This
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Designing SQL Server ETL Pipelines That Don't Break at Scale
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Question of the Day
Detecting Deadlocks Quickly
In the Database Engine, when a deadlock is detected, what does the detection interval shrink to (in time)?
See possible answers