December 2015

Subscribe to the online version of Database Trends and Applications magazine. DBTA will send occasional notices about new and/or updated DBTA.com content.

Trends and Applications

It is often said that the only constant is change. For data executives and professionals, the coming year will only bring a lot more of it. Developments as diverse as cloud, big data, real time, NoSQL, analytics, and the Internet of Things (IoT) will continue to reshape enterprise data operations and opportunities as we know them. Here are 16 trends that will shape the enterprise data landscape in 2016.

There's no question that the pace of data movement has quickened dramatically in recent years. This calls for new strategies for integrating data at the speed of business. That is the challenge as companies increasingly rely on data analytics in their decision making. In a new survey, a majority of managers and professionals (57%) state their business leaders now rely heavily on analytics in their day-to-day decision making. The survey, covering 303 data managers and professionals and conducted by Unisphere Research, a division of Information Today, Inc., finds that organizations are employing a range of new strategies and approaches to improve the speed of data delivery and integration. The survey, among members of the Independent Oracle Users Group (IOUG), and sponsored by Oracle, included respondents from organizations of all sizes and across various industries.

The modern business landscape is a fast-moving, ever-changing, highly competitive environment. For companies to outpace the competition and build upon innovation, they must embrace a modern data architecture. It is necessary that this new architecture support today's new requirements such as mobile integration and advanced digital marketing.

Columns - Big Data Notes

It's commonly asserted—and generally accepted—that the era of the "one-size-fits-all" database is over. We expect that enterprises will use a combination of database technologies to meet the distinct needs created by various application architectures.

Columns - Database Elaborations

Our data models, in reflecting a specific business, must accurately portray the essence of each business. The unique reality within each organization drives the shape of every data model. The logical meaning of each data element originates with what is actually done and how it is accomplished within that particular organization.

Columns - DBA Corner

As a DBA, establishing a reasonable backup schedule for your databases can be a challenging project. It requires you to balance two competing demands: the need to take image copy backups frequently enough to assure reasonable recovery time, and the need to not interrupt daily business. The DBA must be capable of balancing these two objectives based on usage criteria and the capabilities of the DBMS.

Columns - Quest IOUG Database & Technology Insights

Moving infrastructure, databases, or software into the cloud is no longer a bleeding edge decision. Many organizations have implemented this successfully with great benefits, and more continue to do so. It was not that long ago that we started learning about cloud technologies and capabilities. Technologists listened to webinars and read about the possibilities of such a paradigm shift with cynicism. It sounded great, but what about the practicalities, cost, and risk? The only organizations that seemed to embrace this new landscape were technology companies, while the rest of us stood on the sidelines watching and, on occasion, snickering. We thought nothing would ever replace our data centers. It appears we were wrong … it's time to embrace the paradigm shift.

Columns - SQL Server Drill Down

In addition to StretchDB and AlwaysEncrypted, there are two more exciting features in the works for SQL Server 2016: dynamic data masking and row-level security. In the case of these two features, they'll be released first to the cloud platform (Azure SQL Database) and, later, to the on-premises version of SQL Server.

Columns - Next-Gen Data Management

Database performance tuning is a complex but extremely important task. However, it can be difficult to effectively optimize databases when there are other "fires" to put out, limited resources, and an increasing number of databases to look after. But that doesn't mean it's impossible, especially with the right approach.