Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202

The explosion of Big Data represents an opportunity to leverage trending attitudes in the marketplace to better segment and target customers, and enhance products and promotions. Success requires establishing a common business rationale for harnessing social media and determining a maturity model for sentiment analysis to assess existing social media capabilities.

There are some surprisingly straightforward reasons behind the glitches, delays, and cost-overruns that can bedevil data warehouse initiatives. ...The first is simply confusing expectations with requirements. But four other troublemakers can also lead to big problems for developers, IT departments, and organizations seeking to maximize the business value of information.

This guide prepares decision-makers to choose servers that meet their current needs, while building a flexible, reliable, scalable infrastructure to handle future requirements.

What’s wrong with enterprise IT today? Most IT leaders have a ready answer: infrastructure that’s too expensive, inflexible, and difficult to manage. To solve these problems, Dell designed a platform that offers more choice, reduces complexity, and excels at scalability. Read more in this whitepaper!

The paper discusses VRTX and FX as innovation proof points for Dell’s compute infrastructure vision. Learn more by downloading this whitepaper!

Learn to bridge traditional and software-defined workloads on a single modular IT platform with this whitepaper.

This informative guide explores the importance of infrastructure convergence and outlines the key benefits of this strategy, including: - Enhanced data center efficiency - Simplified systems management - And more

Download this infographic to see how you can protect and control your environment while still supporting business-critical initiatives such as BYOD, big data and cloud computing. This infographic will help you make the case for a solution that keeps you a step ahead of security challenges and allows you to enable the business, not inhibit it.

Former Intel CEO Andy Grove once coined the phrase, “Technology happens.” As true as Grove’s pat aphorism has become, it’s not always good news. Twenty years ago, no one ever got fired for buying IBM. In the heyday of customer relationship management (CRM), companies bought first and asked questions later. Nowadays, executives are being enlightened by the promise of big data technologies and the role data plays in the fact-based enterprise. Leaders in business and IT alike are waking up to the reality that – despite the hype around platforms and processing speeds – their companies have failed to established sustained processes and skills around data.

As big data shifts away from a more theoretical concept (only adopted by those on the leading edge), the fun can really begin. How do you prepare for more information than you’ve ever collected before? How can you manage this information with the same standards you applied in the past? These are questions that are causing both IT and business sides to start actively preparing for – and implementing – big data.

If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time. SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.

Big data evolution: forging new corporate capabilities for the long term is an Economist Intelligence Unit report, sponsored by SAS. It explores how far along companies are on their data journey and how they can best exploit the massive amounts of data they are collecting.

Enterprises are leveraging advancements in what IDC calls “3rd Platform” technologies — cloud, Big Data, mobility, and social — to create new business opportunities and gain competitive advantage. These trends are putting more pressure on IT organizations to transform their datacenter operations to better support business initiatives aimed at reducing costs, increasing revenue, and strengthening customer relationships. This has driven increased demand for converged or integrated systems that provide the tools needed to reduce capital costs, improve operational efficiencies and, ultimately, increase agility within the datacenter.

This assessment is composed of a core set of comparative questions, and the option to be assessed in any of three key areas: computing economics, service delivery and business performance. After a half-decade of cost cutting and shrinking IT budgets, the compute infrastructure that powers the enterprise now is typically inefficient, slow and not optimized for business outcomes. It is better suited to the economic realities of 2010 rather than the rigors of the application workloads, delivery models & business expectations of today driven by cloud, mobility, security and big data megatrends. As a result, there is a significant gap between what businesses expect from technology and what IT can deliver.

An IDG Connect survey of 300 enterprise organization decision makers involved in hardware investment decisions reveals the challenges and opportunities that lay between the old style of IT characterized by cost-cutting and infrastructure silos, with the new style of IT driven by the technology trends of Mobility, Cloud and Big Data. These trends have created a significant increase in business expectations that will press IT organizations to rethink their economics, service delivery and business performance. This paper highlights voice-of-the-IT-buyer research results for insight on the challenges and opportunities for IT organizations to drive innovation, transformation and improved delivery against business expectations.

An IDG Connect survey of 300 enterprise organization decision makers involved in hardware investment decisions reveals the challenges and opportunities that lay between the old style of IT characterized by cost-cutting and infrastructure silos, with the new style of IT driven by the technology trends of Mobility, Cloud and Big Data. These trends have created a significant increase in business expectations that will press IT organizations to rethink their economics, service delivery and business performance. This paper highlights voice-of-the-IT-buyer research results for insight on the challenges and opportunities for IT organizations to drive innovation, transformation and improved delivery against business expectations. Intel, the Intel logo, Xeon, and Xeon Inside are trademarks or registered trademarks of Intel Corporation in the U.S. and/or other countries.

This assessment is composed of a core set of comparative questions, and the option to be assessed in any of three key areas: computing economics, service delivery and business performance. After a half-decade of cost cutting and shrinking IT budgets, the compute infrastructure that powers the enterprise now is typically inefficient, slow and not optimized for business outcomes. It is better suited to the economic realities of 2010 rather than the rigors of the application workloads, delivery models & business expectations of today driven by cloud, mobility, security and big data megatrends. As a result, there is a significant gap between what businesses expect from technology and what IT can deliver.

For small and midsize businesses, the realities of a dynamic marketplace and ever-changing customer expectations pose continual challenges and opportunities. Big Data, the cloud and mobility are changing the way information moves and connections are made across the organization, offering productive potential while promising competitive advantage. But adoption of these advanced technologies will require a transformation in the capacities, functions and methods of IT. Download this white paper to learn more.

While just about everyone is writing about how IT and the businesses it serves need to be transformed, the actual industry answers to both digital and IT transformation remain unclear at best. Are transformational initiatives all about analytics and big data? Or are they about the move to cloud in all its varieties? Support for mobile? More agile ways of working and developing software? Or are they actually all about crafting teams to promote more proactive dialog between the business and IT? The truth is, of course, digital and IT transformation depend on all of the above and more. They also depend on a resilient infrastructure that’s easily adapted to changing business priorities without requiring long hours spent on maintenance, updates, and addressing problems of service availability. But making all this work clearly and cohesively is far beyond the purview of almost any solution today—whether from a software management perspective or from a hardware infrastructure perspective.

Databases are often the driving force behind a company’s mission-critical work. They power online stores, confidential records, and customer management systems, so a solution that sustains high levels of database work can be a big advantage as your company grows. We found that the Dell EMC™ VxRail™ P470F hyperconverged system with VMware® vSAN™ could allow you to do more database work than the HPE Hyper Converged 380 (HC 380) with StoreVirtual VSA. The four-node Dell EMC solution processed more orders with faster response times, so more users can fulfill requests quicker—whether they’re placing orders in a store, accessing databases of client info, or adding to company records.

In a recent report, Aberdeen's research suggests that Hadoop usage could be a catalyst for an enhanced and well-rounded data strategy. Read on to find out more.

Organizations today collect a tremendous amount of data and are bolstering their analytics capabilities to generate new, data-driven insights from this expanding resource. To make the most of growing data volumes, they need to provide rapid access to data across the enterprise. At the same time, they need efficient and workable ways to store and manage data over the long term. A governed data lake approach offers an opportunity to manage these challenges. Download this white paper to find out more.

Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.

As easy as it is to get swept up by the hype surrounding big data, it’s just as easy for organizations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt. However, given big data’s power to transform business, it’s critical that organizations overcome these challenges and realize the value of big data. Download now to find out more.