Sifiso W. Ndlovu

Understanding the Impact of NOLOCK and WITH NOLOCK Table Hints in SQL Server

June 6, 2017 by

Every once in a while, SQL Server database administrators find themselves in disagreements with their application developer counterparts – particularly when it comes to some of the latter’s Transact SQL (T-SQL) developmental practices. One of my first observations when I joined my current employer is that almost all T-SQL scripts written by application developers uses the NOLOCK table hint. However, from the interactions that I have had with these esteemed developers it doesn’t seem like they understand how the NOLOCK table hint works. Furthermore, although they seem to be aware of a distinction between NOLOCK and the WITH NOLOCK table hint, they again do not seem to comprehend how the two differ from one another. In this article, I explore the internal workings of the NOLOCK table hint and examine the implications of omitting the WITH keyword.

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Timothy Smith

SQL Server Database Architecture and Audits for Enhanced Security

June 5, 2017 by

This year, digital security has risen as a top concern for many people, especially after the recent security compromises with Cloudflare in February and ransomware in May. Throughout the last two years, we’ve also seen the rise of sim-swapping where a hacker is able to extract a user’s cell phone data and compromise all emails and two-factor authentication. Unfortunately, I expect these security issues to continue and cause compromises for user’s data while negatively impacting companies involved.

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Thomas LeBlanc

Initial Attributes and Measures in SSAS Multidimensional Cubes

June 2, 2017 by

Connecting to tables in SQL Server Analysis Service (SSAS) databases is easy. Maybe too easy. The learning curve for developing in a Multidimensional Cube is steep, although a Tabular Model has lessened this curve. The power of encapsulating the business logic of aggregations and analytics into an Analysis Service database is too great not to embrace Analysis Services in an enterprise environment.

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Ahmad Yaseen

Compression and decompression functions in SQL Server 2016

June 2, 2017 by

The concept of data compression is not a new on for SQL Server Database Administrators , as it is was introduced the first time in SQL Server 2008. In that SQL Server version, you were able to configure the compression at the row and page levels on the table, index, indexed view or the partition. The row and page level compression is not the best choice in all cases, as it does not work well on the Binary Large Objects (BLOB) datatypes, such as the videos, images and text documents.

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Koen Verbeeck

Analysis Services (SSAS) Multidimensional Design Tips – Creating Dimensions

June 1, 2017 by

In the previous article, Analysis Services (SSAS) Multidimensional Design Tips – Data Source View and Cubes, we discussed best practices for SSAS Multidimensional cubes and data source views. In this article, we continue the series with design tips for creating dimensions as the subject. As with the previous article, most tips are suited for SSAS 2008 (most likely 2005 as well) to 2016 and later versions. Analysis Services Tabular is not covered in this article.

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Samir Behara

Microsoft Build Conference 2017 – Recap for SQL Developers

May 29, 2017 by

The annual developer Microsoft Build Conference was held at the Washington State Conference Center in Seattle during May 10-12, 2017. The event had over 5,000 attendees and received a lot of love from the technical community. There were a number of announcements made during this 3-day conference, and in this article I will recap my learnings from a SQL Developer perspective. In the Data Platform, there were a number of new innovations, products and capabilities announced and a lot of emphasis was on using data to fundamentally transform your business. There was focus around serving Artificial Intelligence with Data, which seemed to me to be the future of Data Platform.

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Susantha Bathige

Understanding Skewed Data in SQL Server

May 22, 2017 by

Introduction

I recently did some research to analyze skewed data distribution in SQL Server. This article is the outcome of my analysis to share with SQL Server community.

SQL Server understands its data distribution using statistics. The SQL Server query optimizer then uses the statistics to calculate estimated row counts when executing the queries submitted by users. The accuracy of estimated row count is crucial to get optimal execution plans. The SQL Server query optimizer is a complex mathematical component and it does a decent job to create better execution plans during a very short period of time.

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David Alcock

Monitoring SQL Server with Dynamic Management Objects – Requests

May 17, 2017 by

In my last post, Monitoring SQL Server with dynamic management objects – Sessions and connections, I introduced the concept of using T-SQL queries to monitor SQL Server using Dynamic Management Views. The article demonstrated how we can use two views, namely sys.dm_exec_sessions and sys.dm_exec_connections to view activity on our instance of SQL Server and we achieved this by utilising some of the functionality available to us within T-SQL like joins, aliases and functions, all of which helped us develop a query to return monitoring information to us.

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