January 2016

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Trends and Applications

Today, the success of many startups hinges upon the ability to gain insights from rapidly growing data. Yet startups and smaller businesses often don't have the resources to hire a full-scale data science team, especially considering the painful data scientist shortage that's making it difficult for even large enterprises to find qualified candidates. Here are three approaches companies can adopt to deal with their big and complex data analytics challenges in 2016.

Recent shifts are driving the adoption of a number of technologies and tools, including containers, which are garnering big attention from investors. The primary advantage of containers is allowing applications to look uniform as they cross between non-production and production environments, and between on-premise and cloud. However, containers on their own, while critical to speeding adoption of DevOps and hybrid cloud deployment, are not sufficient.

Exponential data growth is hitting organizations of all sizes hard. It's not enough to merely add more capacity; recovery point objectives must be met, and time is money when it comes to data recovery. The simple truth is that to be effectively managed, adequately protected and completely recovered, your data size must be shrunk.

Columns - Applications Insight

The development of a functional and practical quantum computing system has been "pending" for some decades now, but there are some real signs that this technology may become decisive soon. The implications of cryptography are encouraging major government investment - both the U.S. and China, in particular, are heavily investing in quantum computing technology. The arms race to develop functional quantum computing has begun.

Columns - Database Elaborations

Data modelers must look at the big picture of an organization's data ecosystem to ensure additions and changes fit in properly. Simultaneously, each data modeler must be focused on the minute details, adhering to naming standards, domain rules, data type practices, still remaining ever vigilant for instilling consistency across everything they do. And while focused on all of the above, their efforts must culminate in a practical model that serves the individual project's requirements while also being implementable, maintainable, and extensible.

Columns - DBA Corner

If you are a working DBA, the actual work you do these days is probably significantly different than it was when you first began work as a DBA. So is the term DBA really accurate any longer? Or has the job grown into something more?

Columns - SQL Server Drill Down

If you're into data and databases and you have not heard the term "machine learning," may I suggest that you're not reading enough? This technology is hot and hyped, largely because it is the secret ingredient in many successful Big Data projects.

MV Community

Entrinsik has formed a partnership with Technology Advisors, Inc., a global business and technology consulting company specializing in the development of customer relationship management (CRM) processes, working with technology solutions, including SugarCRM, Act-On, DocuSign, Infor, Microsoft Dynamics, SalesFusion, and Zendesk.

MultiValue technology, which celebrated its 50th anniversary in 2015, remains an important part of the data management landscape. Here, MultiValue vendors offer their thoughts on the outlook for MultiValue in the future and share predictions 2016.

Rocket Software has announced a new version of Rocket Discover, a self-service data preparation, visualization, and discovery solution for business users. Discover version 1.5 contains new features that make it easier for end users to display data insights and allow for organizations to make better business decisions with the help of their data.