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Featured Database Articles

Feature Database Articles

MS SQL

Getting Started with Database Engine Tuning Advisor in SQL Server – Part 2 03/23/2015

Arshad Ali demonstrates how you can use the command line interface to tune SQL queries and how you can use SQL Server Profiler to capture the workload for tuning with Database Engine Tuning Advisor.

Introduction to Automating Deployment of SQL Server in Azure IaaS Virtual Machines 03/05/2015

In general, Microsoft Azure provides two types of SQL Server based relational data services, Azure SQL Database Platform-as-a-Service (PaaS) and deploying a SQL Server instance into an Azure Infrastructure-as-a-Service (IaaS) virtual machine. There are obvious implications in regards to the management overhead associated with IaaS-based solutions. Marcin Policht reviews methods that allow you to minimize this overhead, focusing in particular on deployment tasks.

Using the ROLLUP, CUBE, and GROUPING SETS Operators 03/02/2015

Greg Larsen discusses the ROLLUP, CUBE and GROUPING SETS operators. These operators are used with the GROUP BY clause and allow you to create subtotals, grand totals and superset of subtotals. Read on to find out more about these additional GROUP BY operators.

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Oracle

CBO, Analytic functions and Cardinalities in Oracle 11.2 03/12/2015

In Oracle 11.2 using analytic functions can generate 'interesting' cardinality values that are far larger than they should be.  Read on to see just how far off those values can be.

My Oracle Cup Overflows 02/23/2015

Overflow data in an index-organized table is usually put in its own tablespace.  Sometimes it isn't; read on to see what overflow data is and how to change where it's located.

Oracle: MERGE 'Monkey-business' 02/12/2015

Odd errors can result in odd 'solutions', and Oracle has one for the MERGE statement.  Read on to see what it is and what it fixes.

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MS Access

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DB2

Exploding the Myths of Big Data 03/16/2015

As big data application success stories (and failures) have appeared in the news and technical publications, several myths have emerged about big data. This article explores a few of the more significant myths, and how they may negatively affect your own big data implementation.

Another Look at Tuning Big Data Queries 02/16/2015

Most large organizations have implemented one or more big data applications. As more data accumulates internal users and analysts execute more reports and forecasts, which leads to additional queries and analysis, and more reporting. The cycle continues: data growth leads to better analysis, which generates more reporting. Eventually the big data application swells with so much data and querying that performance suffers. How to avoid this?

Managing the Big Data Technical Staff 01/20/2015

Big data is everywhere, and most large IT enterprises have installed one or more big data applications. These applications provide fast access to large stores of data, usually customer or sales data. Your technical staff that supports these applications and the systems that analyze and consume the data didn't exist ten years ago. Who are these new IT professionals, and how should you manage them?

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