Featured Database Articles
With the new temporal table feature, SQL Server 2016 internally manages two tables--a base table, which contains the latest data and a history table, which contains the history of changes. Read on to learn about this new feature, how it works, how to create a new table or enable the feature for an existing table.
With the new security policy feature in SQL Server 2016 you can restrict write operations at the row level by defining a block predicate. Read on to learn why a block predicate is important when you implement row level security using SQL Server 2016.
One of more common concerns among database administrators who consider migrating their estate to Azure SQL Database is their ability to efficiently manage the migrated workloads. In particular, the absence of the SQL Server Agent introduces the challenge of identifying a means to perform ad-hoc and scheduled automated management tasks across multiple databases. Fortunately, recently introduced Elastic Database jobs provide a convenient and efficient way to address this concern.
Sometimes it's good to re-think how to write a query; set operations can provide performance benefits over 'straight SQL'. Read on to see an example of this in action.
Deletes may be more 'expensive' than the Oracle optimizer reports; read on to see why.
There may be times when you need to recover a single table and flashback isn't configured and the recycle bin is turned off. Using RMAN in Oracle 12c it's possible to restore and recover a single table. Read on to see how it's done.
Business Intelligence (BI) has matured over the past two decades. The next few years will be critical for the information technology staff, as they attempt to integrate and manage multiple, diverse hardware and software platforms. This article addresses how to meet this need, as users demand greater ability to analyze ever-growing mountains of data, and IT attempts to keep costs down.
Some companies have been slow to acquire big data applications. They discovered that modern hardware platforms and database management systems were more than adequate for most of their business analytics needs. Such needs share several common attributes, including analytics run against operational systems, where the analytics logic and engine were close to the object data. This meant that companies could avoid complex and high-volume data movement and extract-transform-load (ETL) strategies while executing queries against already existing, well-tuned databases. In this article we introduce the concepts of strategic and tactical analytics, and how best to support these methods with your current IT infrastructure.
With promises of incredibly fast queries, many IT shops implemented one or more big data applications in combination with high-performance hardware and software suites. However, few IT enterprises followed the appropriate data governance means and methods of ensuring data quality. What ensued was data of dubious quality being loaded into these applications, calling into question the results. In this article we review data quality methods and metrics for loading big data applications.