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Published By: Datastax     Published Date: Aug 27, 2018
"Part of the “new normal” where data and cloud applications are concerned is the ability to handle multiple types of data models that exist in the application and persist each in a single datastore. This data management capability is called a “multi-model” database. Download this free white paper and explore the multi-model concept, its rationale, and how DataStax Enterprise (DSE) is the only database that can help accelerate building and powering distributed, responsive and intelligent cloud applications across multiple data models"
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
" For any business that wants to successfully compete in today’s digital economy, it is not a question of if but rather how much of their business will be done with cloud applications. A cloud application is one with many endpoints including browsers, mobile devices, and/or machines that are geographically distributed. The application is intensely transactional (high velocity reads and/or writes), always available, and instantaneously responsive no matter the number of users or machines using the application. Download this free white paper and explore how DataStax customers are delivering real-time value at epic scale with their cloud applications. Explore the core database requirements that make businesses successful with cloud applications, which include continuous availability, linear scale, and geographic distribution."
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
Today’s enterprises continue to differentiate themselves via their cloud applications. But differentiation is getting harder and harder to accomplish. To stand out, you need a flexible, nimble, scalable, always-on data platform that can deliver powerful, game-changing, customer-facing applications. Read this white paper to learn how DataStax Enterprise delivers comprehensive data management through a secure, operationally simple platform built on the best distribution of Apache Cassandra™.
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Datastax
Published By: Datastax     Published Date: Aug 27, 2018
In this eBook, we’ll take a look at why DataStax and Azure combine to make the ideal hybrid operational cloud database for the modern application needs of many of our large enterprise customers. The eBook explains how digital disruptors like Microsoft, Komatsu, and IHS Markit are leveraging the DSE+Azure hybrid cloud database to build game-changing applications built for the Right-Now Economy.
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Datastax
Published By: Datastax     Published Date: Aug 28, 2018
Today’s enterprises continue to differentiate themselves via their cloud applications. But differentiation is getting harder and harder to accomplish. To stand out, you need a flexible, nimble, scalable, always-on data platform that can deliver powerful, game-changing, customer-facing applications. Read this white paper to learn how DataStax Enterprise delivers comprehensive data management through a secure, operationally simple platform built on the best distribution of Apache Cassandra™.
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Datastax
Published By: Datastax     Published Date: Aug 28, 2018
In this eBook, we’ll take a look at why DataStax and Azure combine to make the ideal hybrid operational cloud database for the modern application needs of many of our large enterprise customers. The eBook explains how digital disruptors like Microsoft, Komatsu, and IHS Markit are leveraging the DSE+Azure hybrid cloud database to build game-changing applications built for the Right-Now Economy.
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Datastax
Published By: Datastax     Published Date: Nov 02, 2018
In this eBook, we’ll take a look at why DataStax and Azure combine to make the ideal hybrid operational cloud database for the modern application needs of many of our large enterprise customers. The eBook explains how digital disruptors like Microsoft, Komatsu, and IHS Markit are leveraging the DSE+Azure hybrid cloud database to build game-changing applications built for the Right-Now Economy.
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Datastax
Published By: Datastax     Published Date: Nov 02, 2018
Today’s data volume, variety, and velocity has made relational database nearly obsolete for handling certain types of workloads. But it’s also put incredible strain on regular NoSQL databases. The key is to find one that can deliver the infinite scale and high availability required to support high volume, web-scale applications in clustered environments. This white paper details the capabilities and uses case of an Active Everywhere database
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Datastax
Published By: Datastax     Published Date: Dec 27, 2018
This paper examines the challenges banks face when creating a 360-degree view of every customer interaction, what database requirements the lines of business (LOBs) should look into, and use cases where retail banking LOBs can benefit from leveraging DataStax Enterprise, the data management platform purpose-built to power cloud applications.
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Datastax
Published By: Datastax     Published Date: Jan 07, 2019
Digital disruptors are giving customers the information they want, when, where, and how they want it, resulting in a fundamental shift in customer expectations and how enterprises deliver value. As enterprises move towards adopting these modern applications and achieving data autonomy, the data layer and cloud infrastructure they run on can make a huge impact. In this eBook, we’ll take a look at why DataStax and Azure combine to make the ideal data layer for contextual, always on, real-time, distributed, and scalable applications.
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Datastax
Published By: OneLogin     Published Date: Oct 24, 2017
Corporate data spreads across an ever-growing number of applications. Users (employees, contractors, partners, and customers) access those applications over a wide range of devices. Those devices take different forms: desktops, laptops, tablets, smartphones, smartwatches. Each device may use a different operating system. The locations from where people access your data can be on-premises or off, and in any number of places around the globe. Data, users, apps, devices, locations—the sheer number of permutations and combinations is mind-boggling. This complex nature of today’s IT environment opens security gaps and exposes your business to undue risk. To illustrate, try to envision all the permutations and possible entry points for risk in your organization. Imagine that you have 400 users, each using 25 apps. When you multiply those together, that’s 10,000 potential access permissions to manage. Access permissions change as users come and go, roles change, new apps are added, and
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OneLogin
Published By: Red Hat     Published Date: Jan 02, 2018
Organizations are at a strategic crossroads. According to IDC analysts,1 two-thirds of CEOs will center their corporate strategies around digital transformation initiatives. The goal of digital transformation is only partly to make existing functions more effective. The greater goal is to be able to do new things and use existing data in new, better ways. Yet, 72% of current IT spending2—and the focus of IT resources—is on maintaining existing systems. This creates tension between what needs to be done today and what should be done for the future. Middle-tier applications, according to IDC,3 are the core of a digital transformation strategy because they provide data integration, messaging, and application programming interface (API) management. Middle-tier applications also provide a platform for application development and management that can handle traditional enterprise applications and cloud-native, distributed applications. Specifically, a Java™ EE-based application platform can
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Red Hat
Published By: IBM     Published Date: Jul 02, 2018
Cloud has evolved from a technological innovation to an integral part of business. Companies in every industry are investing in Digital Transformation initiatives to evolve and grow; often, cloudbased platforms are foundational elements of these transformations, as businesses increasingly seek the flexibility and agility to roll out new software services in days or weeks, versus months or years. As Digital Transformation initiatives unfold, one key challenge is to modernize the data center to facilitate rapid delivery of new applications and services—while still ensuring that existing missioncritical applications remain high performing, available, and secure. Another challenge relates to new requirements for accelerating the analysis of organizational data to near real time, much faster than previously possible with earlier incarnations of Business Intelligence (BI). Agile businesses are demanding faster access to the information contained within operational and business data stores to
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IBM
Published By: IBM     Published Date: Jul 02, 2018
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
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IBM
Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM
Published By: IBM     Published Date: Jul 05, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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IBM
Published By: Visier     Published Date: Jan 25, 2019
John Schwarz founded Visier to address what he saw as the major failing of business intelligence and big data analytics. He had a front row seat in this market while leading Business Objects, the largest global business intelligence provider (acquired by SAP). John and co-founder Ryan Wong’s vision was to completely reinvent the approach to analytics, providing instant and complete, domain-specific applications to business leaders, answering their important strategic questions and leading them to adopt best management practices. Their applied business analytics project is working. Today, more than a hundred blue chip companies have selected Visier as their people strategy platform and are achieving incredible results. And that’s just the beginning.
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Visier
Published By: IBM     Published Date: Jun 25, 2018
Vast resources of data are increasingly available, but the sheer volume can overwhelm human capability. By implementing the cognitive system of IBM Watson Discovery into their infrastructure, businesses can extract deeper and more accurate insights by efficiently identifying, collecting and curating structured and unstructured data. Watson Discovery, also capable of creating content collections and custom cognitive applications, can transform organizational processes to extend proprietary content and expert knowledge faster and at greater scales. Read more to learn how Watson Discovery can keep your organization evolving ahead of the competition. Click here to find out more about how embedding IBM technologies can accelerate your solutions’ time to market.
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IBM
Published By: TeamQuest     Published Date: Sep 05, 2014
TeamQuest Director of Market Development Dave Wagner and Chris Lynn, Safeway's Capacity Manager and Performance Analyst, cover the application of automatic, exception-oriented analytics to a wide variety of IT and business metrics in order to simultaneously optimize service performance and IT cost. Multiple conceptual approaches are shared, including pros and cons. Most of the presentation includes real examples by which Safeway has integrated performance, capacity, business, and power data into an automated optimization process spanning 1000s of servers and virtual servers and their applications.
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automated analytics, automated optimization, it cost, power data
    
TeamQuest
Published By: Microsoft     Published Date: Feb 15, 2017
Learn how to take care of the information and applications that are the lifeline to your business.
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data, storage, back up, disaster recovery, business continuity, applications
    
Microsoft
Published By: MarkLogic     Published Date: Nov 07, 2017
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Read this eBook, discover the 5 steps to getting smart about semantics, and learn how by using semantics, leading organizations are integrating disparate heterogeneous data faster and easier and building smarter applications with richer analytic capabilities.
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MarkLogic
Published By: Citrix     Published Date: Jun 15, 2018
The world of IT is undergoing a digital transformation. Applications are growing fast, and so are the users consuming them. These applications are everywhere—in the datacenter, on virtual and/or microservices platforms, in the cloud, and as SaaS. More and more apps are now being moved out of datacenters to a cloud-based infrastructure. In order for an optimized and secure delivery of these applications, IT needs specific network appliances called Application Delivery Controllers (ADCs). These ADCs come in hardware, virtual, and containerized form factors, and are sized by Network Administrators based on the current and future usage of applications. The challenge with this is that it’s hard to foresee sizing or scalability requirements for these ADCs since users are constantly increasing, and applications are consistently evolving, as well as moving out of datacenters. Complicating matters, most ADCs are fixed-capacity network appliances that provide zero or minimum expansion capability
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Citrix
Published By: BlueArc Corporation     Published Date: Mar 31, 2008
BlueArc’s Titan 3000 Series is designed to meet the requirements of today’s sophisticated enterprise data centers and vertical applications with new levels of storage performance, scalability and reliability. Titan is the first storage solution that consolidates and manages up to 4 petabytes of data in a single storage pool.
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titan, tiered storage, storage, bluearc, storage system
    
BlueArc Corporation
Published By: BlueArc Corporation     Published Date: Apr 24, 2008
BlueArc’s Titan Architecture creates a revolutionary step in file servers by creating a hardware-based file system that can scale throughput, IOPS and capacity well beyond conventional software-based file servers. With its ability to virtualize a massive storage pool of up to 4 petabytes of usable, tiered storage, Titan can scale with growing data requirements and provide a competitive advantage for business processes by consolidating applications while ensuring optimal performance.
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bluearc, storage, titan
    
BlueArc Corporation
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Today, as IT departments struggle to design and implement solutions capable of managing exponential data growth with strict requirements for application scale and performance, many of them are turning to in-memory data grids (IMDGs).
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it departments, data growth, managing data growth, application scale, application performance, in-memory data grids, imdgs, big data, data volume, data velocity, data variability, data management, data collection, data processing, data scaling, data storage systems, data access, data solutions, data challenges, management tooling
    
Red Hat, Inc.
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