Powerful IT doesn’t have to be complicated. Hyperconvergence puts your entire virtualized infrastructure and advanced data services into one integrated powerhouse. Deploy HCI on an intelligent fabric that can scale with your business and you can hyperconverge the entire IT stack. This guide will help you: Understand the basic tenets of hyperconvergence and the software-defined data center; Solve for common virtualization roadblocks; Identify 3 things modern organizations want from IT; Apply 7 hyperconverged tactics to your existing infrastructure now.
When a pharmaceutical company discovered its risks under the new Patient Protection and Affordable Care Act, it turned to Collaborative to comb and consolidate its data. The result: compliance and insight into new business opportunities, too, through a company-wide business data warehouse and enhanced business intelligence.
Published By: Quantum
Published Date: Jan 24, 2017
Is your organization ready to take the plunge into in-house video production? The benefits can be substantial, but making the move requires some preparation. The IT infrastructure you use for enterprise applications might not be able to meet the rigorous requirements of video production. And you might not want video production teams to use resources from your existing infrastructure, since doing so could affect the performance of other applications. Whether you’re just getting started with in-house video or ramping up production, consider these five best practices for building an IT environment optimized for video work. The right approach to IT is essential for developing efficient collaborative workflows and maximizing the value of your video content.
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data.
Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results.
Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets.
Oracle has a better way. Download this whitepaper to f
In some cases, adopting cloud IoT platform may make more sense where required processes, communication costs and cloud costs meet sufficient total cost of ownership against deploying MDC. Additionally, in situations that an end-user organization already has a secure room or a modular data center solution where infrastructure can be housed and/or the amount of infrastructure involved may be too small to benefit from power/cooling advantages of being housed in an MDC, the organization may not see a need for an MDC. An MDC is nothing more than a smaller form of a modular data center, and a number of providers have entered the modular data center solutions space in the past. These modular data center solution providers came into the market with high expectations for growth and ROI only to find that high sales were not forthcoming due to limited use cases, so many exited the space.
Datacenters are the factories of the Internet age, just like warehouses, assembly lines, and machine shops were for the industrial age. Over the course of the past several years, riding the wave of modernization, datacenters have become the heart and soul of the financial industry, which each year invests over $480 billion in datacenter infrastructure of hardware, software, networks, and security and services.
Companies today increasingly look for ways to house multiple disparate forms forms of data under the same roof, maintaining original integrity and attributes. Enter the Hadoop-based data lake. While a traditional on-premise data lake might address the immediate needs for scalability and flexibility, research suggests that it may fall short in supporting key aspects of the user experience. This Knowledge Brief investigates the impact of a data lake maintained in a cloud or hybrid infrastructure.
Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
IDC believes that this emerging environment is to date still highly undefined, even as
businesses must make critical decisions. Should businesses develop in-house or use VARs,
systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some
hybrid form? Can they use existing infrastructure, or do AI applications and deep learning
require new servers with new capabilities? We believe that many of these questions can be
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
Implementing a multi-tiered cloud strategy offers flexibility for protection required for workloads and cost-savings of inexpensive cloud services. Learn how to execute a unified, infrastructure to enable organizations to make the best of cloud.
As IT managers urgently seek to reduce the fixed costs associated with running their in-house fax servers, cloud-based faxing emerges as a highly effective tool for combating the unpredictability of fluctuating infrastructure costs.
Data centers are large, important investments that, when properly designed, built, and operated, are an integral part of the business strategy driving the success of any enterprise. Yet the central focus of organizations is often the acquisition and deployment of the IT architecture equipment and systems with little thought given to the structure and space in which it is to be housed, serviced, and maintained. This invariably leads to facility infrastructure problems such as thermal “hot spots”, lack of UPS (uninterruptible power supply) rack power, lack of redundancy, system overloading and other issues that threaten or prevent the realization of the return on the investment in the IT systems.
Data centers are large, important investments that when properly designed, built and operated, are an integral part of the business strategy driving the success of any enterprise, yet the central focus of organizations is often the acquisition and deployment of the IT architecture equipment and systems, with little thought given to the structure and space in which it is to be housed, serviced and maintained. This invariably leads to facility infrastructure problems, such as thermal hot spots, lack of UPS, rack power, lack of redundancy, system overloading and other issues that threaten or prevent the realization of the return on the investment in the IT systems.