Enterprise software development teams have historically had trouble ensuring the code that runs well on a developer's machine also runs well in production. DevOps has promoted more collaboration between developers and IT operations. Data scientists and data science teams face similar challenges, which DevOps concepts can help address.
Cloud computing sometimes defies economic analysis. The public cloud, in particular, is associated with abundance rather than scarcity, one of the key concepts of economics. But while the cloud creates efficiencies, it does not eliminate constraints or the need to choose between competing goods. One important task for IT teams today is to understand those options more clearly.
Click to learn more about authoráKen Hosac. The Internet of Things (IoT) is much more than just connecting devices to the Internet and Cloud, it?s about generating new business insights, automating business and production processes and accelerating innovation cycles. The vast array of IoT implementations are difficult to comprehend, as they can encompass everything from [?]
Modern ethos is that all data is valuable, should be stored forever, and that machine learning will one day magically find the value of it. You?ve probably seen that EMC picture about how there will be 44 zettabytes of data by 2020? Remember how everyone had Fitbits and Jawbone Ups for about a minute? Now Jawbone is out of business. Have you considered this ?all data is valuable? fad might be the corporate equivalent? Maybe we shouldn?t take a data storage company?s word on it that we should store all data and never delete anything.
While the public cloud continues to grow at the expense of on-premises data centers, not everything that moves to the cloud stays there. Some data comes back, for a variety of reasons. And while apps are moving to the cloud at a rapid clip, data is not.
Click to learn more about authoráAnil Parmar. An estimated 2.7 million job postings for Data Analytics and science are projected in the United States by 2020. With more and more companies understanding the importance of Big Data as a useful source for gaining insights and making informed decision- the demand for Data Analytic specialists who [?]
Last week, the hybrid cloud landscape changed significantly. At the Microsoft Ignite conference, Microsoft and several hardware partners announced availability of the long-awaited Azure Stack. Think of it as a configurable rack of hardware that has a version of the Azure public cloud on it.
Before shedding any light on how useful Big Data proves to be for businesses, let?s just take a quick detour to what Big Data is, and its mechanization. Big Data is a large set of structured and unstructured data. Its complexity and extensiveness do not allow the conventional data processing... Read more ╗
Click to learn more about authoráHoala Greevy. You?ll find dozens of products out there calling themselves Data Loss Prevention (DLP). And, while such technology may be part of your solution, data loss prevention is a full-time and full-blown strategic approach to protect your data. There are at least five reasons your organization needs data loss [?]
AWS primarily and Azure, of late, dominate today?s discussions around storage, backup and compute power. A quick glance at headlines from technology journalists, and a reader can glean a common coverage theme that ties these writers together ? the ongoing discussion around the benefits of going all-in on the public cloud. However, in most cases technology journalists are writing about larger corporations, or big name installations, which may or may not reflect the actual trends taking place in the marketplace, especially at mid-size companies and organizations experiencing a growth spurt.
Hypothetical: You need to set up the IT infrastructure (email, file sharing, etc.) for a new company. No restrictions. No legacy application support necessary. How would you do it? What would that ideal IT infrastructure look like?