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Published By: Ataccama     Published Date: Feb 26, 2019
Machine learning is a powerful tool for the transformation of data management, and with increasing amounts of data in an organization’s possession, it is more vital than ever. Learn how Ataccama leverages cutting-edge machine learning techniques to automate manual and time-consuming tasks and optimize performance. By developing AI-powered data cataloging and master data management solutions, we can help stem the tide of data chaos and ensure that your data is orderly, correct, and easy to find.
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Ataccama
Published By: MEGA International     Published Date: Mar 07, 2019
The effectiveness of agile processes is often jeopardized because the architecture and organizational pre-requisites of agility are neglected. This White Paper proposes a new architecture framework, the Agile Architecture Framework (AAF), that meets the needs of the digital enterprise. It develops a vision that uniquely combines: • Methods for decomposing the system into loosely-coupled services and autonomous teams • Alignment mechanisms rooted in business strategy • Architecture patterns that leverage the latest software innovations • Results from large enterprises that started their agile-at-scale journey several ago This proposed architecture approach will enable organizations at all scales to better realize the Boundaryless Information Flow™ vision achieved through global interoperability in a secure, reliable, and timely manner.
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MEGA International
Published By: TopQuadrant     Published Date: Mar 21, 2015
Data management is becoming more and more central to the business model of enterprises. The time when data was looked at as little more than the byproduct of automation is long gone, and today we see enterprises vigorously engaged in trying to unlock maximum value from their data, even to the extent of directly monetizing it. Yet, many of these efforts are hampered by immature data governance and management practices stemming from a legacy that did not pay much attention to data. Part of this problem is a failure to understand that there are different types of data, and each type of data has its own special characteristics, challenges and concerns. Reference data is a special type of data. It is essentially codes whose basic job is to turn other data into meaningful business information and to provide an informational context for the wider world in which the enterprise functions. This paper discusses the challenges associated with implementing a reference data management solution and the essential components of any vision for the governance and management of reference data. It covers the following topics in some detail: · What is reference data? · Why is reference data management important? · What are the challenges of reference data management? · What are some best practices for the governance and management of reference data? · What capabilities should you look for in a reference data solution?
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data management, data, reference data, reference data management, top quadrant, malcolm chisholm
    
TopQuadrant
Published By: Cambridge Semantics     Published Date: May 11, 2016
With the explosive growth of Big Data, IT professionals find their time and resources squeezed between managing increasingly large and diverse siloed data stores and increased user demands for timely, accurate data. The graph-based ANZO Smart Data Manager is built to relieve these burdens by automating the process of managing, cataloging and governing data at enterprise scale and security. Anzo Smart Data Manager allows companies to truly understand their data ecosystems and leverage the metadata within it.
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Cambridge Semantics
Published By: AT&T     Published Date: Sep 11, 2014
The age of Big Data is upon us. Storage costs are going down, and data analytics is becoming more capable and more user-friendly. Even your auto mechanic will be storing a petabyte of data soon. Big Data will give businesses new insights and help improve operations. With these new tools come questions about how to use them. But your mechanic knows more about fixing a transmission than developing a Hadoop cluster, and similar concerns hold true for larger enterprises. Businesses everywhere are looking for guidance.
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AT&T
Published By: iCEDQ     Published Date: Feb 05, 2015
The demand for using data as an asset has grown to a level where data-centric applications are now the norm in enterprises. Yet data-centric applications fall short of user expectations at a high rate. Part of this is due to inadequate quality assurance. This in turn arises from trying to develop data-centric projects using the old paradigm of the SDLC, which came into existence during an age of process automation. SDLC does not fit with data-centric projects and cannot address the QA needs of these projects. Instead, a new approach is needed where analysts develop business rules to test atomic items of data quality. These rules have to be run in an automated fashion in a business rules engine. Additionally, QA has to be carried past the point of application implementation and support the running of the production environment.
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data, data management, data warehousing, data quality, etl testing, malcolm chisholm
    
iCEDQ
Published By: AnalytixDS     Published Date: May 04, 2018
The General Data Protection Regulation (GDPR) is a regulation by which the European Parliament, the Council of the European Union and the European Commission intend to strengthen and unify data protection for all individuals within the European Union (EU). It also addresses the export of personal data outside the EU. The General Data Protection Regulation (GDPR) will go into effect from May 25 2018, making organizations accountable for personal data protection including how and where data is stored and how it is processed within the organization. Get ready for the most comprehensive governance and automation platform in the industry.
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AnalytixDS
Published By: WhereScape     Published Date: Mar 16, 2016
Industry expert Wayne Eckerson provides an overview of the emerging data warehouse automation market and outlines the value of using automation tools for developing data warehouses, data marts, analytical environments and big data platforms. Eckerson details WhereScape’s architecture—which enables a data-driven approach to automation. Eckerson also discusses how agility and automation together encourage iterative development and closer collaboration between business and IT.
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WhereScape
Published By: WhereScape     Published Date: Aug 18, 2016
Data Vault 2.0 leverages parallel database processing for large data sets and provides an extensible approach to design that enables agile development. WhereScape provides data warehouse automation software solutions that enable Data Vault agile project delivery through accelerated development, documentation and deployment without sacrificing quality or flexibility.
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WhereScape
Published By: WhereScape     Published Date: Oct 20, 2017
Put IT on Automatic: Cloud Data Warehousing Has Arrived by Eric Kavanagh of The Bloor Group Download this white paper to better understand the value the cloud offers IT teams developing data infrastructure, and how automation can be used to not only accelerate time to value, but to tackle quality control, compliance and developer productivity. Sponsored by WhereScape. To learn more about WhereScape automation, visitwww.wherescape.com"
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WhereScape
Published By: Octopai     Published Date: Sep 01, 2018
For many BI professionals, every task can feel like MISSION IMPOSSIBLE. All the manual mapping required to sort out inconsistencies in data and the lack of tools to simplify and shorten the process of finding and understanding data leaves BI groups frustrated and slows down the business. This whitepaper examines the revolutionary impact of automation on the cumbersome manual processes that have been dragging BI down for so long. • Data correction vs process correction • Root-cause analysis with data lineage: reverse-tracing the data flow • Data quality rules and data controls • Automated data lineage mapping
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Octopai
Published By: Deloitte Process Robotics     Published Date: May 04, 2018
Deloitte Process Robotics (DPR) solutions use a lightweight approach to train ‘bots’ that automate repetitive tasks of medium complexity without changes to existing process or IT infrastructure. With ever-growing repositories of unanalyzed and underutilized data, organizations require highly flexible and scalable enterprise data management (EDM) processes, DPR makes it possible for organizations to adopt comprehensive yet affordable EDM processes in the Big Data Era, helping organizations transform data into strategic assets through the automation of capabilities.
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Deloitte Process Robotics
Published By: Wave Computing     Published Date: Jul 06, 2018
This paper argues a case for the use of coarse grained reconfigurable array (CGRA) architectures for the efficient acceleration of the data flow computations used in deep neural network training and inferencing. The paper discusses the problems with other parallel acceleration systems such as massively parallel processor arrays (MPPAs) and heterogeneous systems based on CUDA and OpenCL, and proposes that CGRAs with autonomous computing features deliver improved performance and computational efficiency. The machine learning compute appliance that Wave Computing is developing executes data flow graphs using multiple clock-less, CGRA-based System on Chips (SoCs) each containing 16,000 processing elements (PEs). This paper describes the tools needed for efficient compilation of data flow graphs to the CGRA architecture, and outlines Wave Computing’s WaveFlow software (SW) framework for the online mapping of models from popular workflows like Tensorflow, MXNet and Caffe.
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Wave Computing
Published By: Sqrrl Data, Inc.     Published Date: Jun 02, 2014
With the dissolution of the “trusted zone”, Data-Centric Security is a key enabler for Big Data applications. Sqrrl's Enterprise is a NoSQL database that is built with a Data-Centric Security implementation that includes cell-level security labeling and enforcement, encryption at rest, encryption in motion, an automated data labeling engine, a security policy specification engine, custom secure search indexing, and an audit facility.
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Sqrrl Data, Inc.
Published By: Cisco     Published Date: Jan 02, 2019
The network is the foundation of robust security, and the critical network security element is the firewall. For that reason, Cisco has been committed to delivering a next-generation firewall that can stop threats at the edge and focus on security efficacy. Those efforts are paying off in substantial momentum, and market observers are taking note. Cisco has been named a leader in the 2018 Gartner Magic Quadrant for Enterprise Network Firewalls. Beginning with our world-class threat-intelligence organization, Talos - the Cisco NGFW stands out from the competition. It goes beyond prevention and gives visibility into potentially malicious file activity across users, hosts, networks, and infrastructure. It saves you time and enables automation using our integrated architecture. No other firewall vendor have the strength and breadth of networking and security capabilities that Cisco offers. Learn More about it by downloading Gartner’s 2018 Magic Quadrant for Enterprise Network Firewalls.
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security, enterprise network, firewall, cisco, gartner, magic quadrant
    
Cisco
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
Managing infrastructure has always brought frustration, headaches, and wasted time. That’s because IT professionals have to spend their days, nights, and weekends dealing with problems and manually tuning their infrastructure. Traditional monitoring and support are too far removed from infrastructure, resulting in an endless cycle of break-fix-tune-repeat. Infrastructure powered by artificial intelligence, however, can overcome the limitations of humans and traditional tools. This white paper explores how HPE InfoSight with its recommendation engine paves the path for an autonomous data center your Hybrid Cloud World.
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Hewlett Packard Enterprise
Published By: Dell EMC     Published Date: Feb 14, 2019
Technology is quickly moving to the forefront as organizations undertake digital and IT transformation projects that enable strategic differentiation in a world where users are leveraging applications and data in new ways. The reality is, most organizations were not born digital but instead have legacy business processes, applications, and infrastructure that require modernization and automation. Read this executive summary from Dell and Intel® to learn why businesses must embark on IT transformation to modernize and automate their legacy infrastructure and prime themselves to achieve their digital business goals. Intel Inside®. Powerful Productivity Outside.
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Dell EMC
Published By: Zendesk     Published Date: Jan 04, 2019
Seus clientes eles entendem mais de tecnologia do que nunca e preferem a abordagem "faça você mesmo" para resolver seus problemas e responder às suas próprias dúvidas. Anos de pesquisas feitas pelo ICMI confirmaram que os clientes preferem resolver seus problemas por conta própria e usando seus canais favoritos. Além disso, os clientes só procuram interações diretas quando esgotam todas as opções de autoatendimento. Essa informação se baseia em dados da American Express, que descobriu que 48% dos consumidores preferem falar com um representante do atendimento ao cliente para lidar com problemas complexos, mas apenas 16% preferem esse mesmo contato para resolver problemas simples. O objetivo desse documento é simples: queremos ajudá-lo a criar uma base de conhecimento, uma comunidade e um portal do cliente completos. E você pode fazer tudo isso usando a Central de Ajuda do Zendesk Guide.
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Zendesk
Published By: Zendesk     Published Date: Jan 04, 2019
Quando sua empresa começa um novo capítulo, seja mudando de mercado ou lançando novos produtos e recursos, o momento é ótimo para expandir as operações de atendimento ao cliente de maneira inteligente. Sabemos que, se disponível, os clientes preferem usar a base de conhecimento para se ajudarem. Um relatório do Gartner estima que os Diretores de informática podem reduzir os custos com suporte em 25% ou mais quando uma rotina adequada de gestão de conhecimento é implementada. Se você estava esperando o momento certo para mergulhar de cabeça no autoatendimento, este white paper provará que você e seus agentes já fazem tudo o que precisam para oferecer autoatendimento excelente todos os dias.
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Zendesk
Published By: Zendesk     Published Date: Jan 04, 2019
No mercado mundial de softwares de suporte ao cliente, a Zendesk mais uma vez é reconhecida como líder no Quadrante Mágico do Gartner de 2018 para Centros de Relacionamento com Clientes de CRM. Todos os anos, o Gartner realiza uma análise minuciosa dos prestadores de serviços no setor de aplicativos de atendimento e suporte ao cliente. O relatório do Quadrante Mágico do Gartner para Centros de Relacionamento com Clientes de CRM oferece informações valiosas para líderes de empresas em busca de soluções tecnológicas para interagir e engajar seus clientes. Novamente, a Zendesk pode ser encontrada no relatório de 2018 no quadrante Líder, que consideramos um reflexo do sucesso de nossos 125.000 clientes, incluindo empresas como Airbnb, Tesco e a Universidade do Tennessee. O ano passado incluiu um número de marcos significativos para nós, incluindo o lançamento de recursos de inteligência artificial aprimorados para autoatendimento, com uma taxa de execução que ultrapassou US$ 500 milhões
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Zendesk
Published By: IBM APAC     Published Date: Mar 06, 2019
Achieve superior control and performance across multicloud environments with IBM Multicloud Manager. With a multicloud strategy, it can become time-consuming, expensive and difficult to manage environments as you contend with scattered visibility, security and workloads across multiple Kubernetes clusters and clouds. IBM Multicloud Manager integrates all your environments in a single view that gives you optimal control over how you see, govern and automate everything.
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IBM APAC
Published By: Avi Networks     Published Date: Mar 06, 2019
OpenShift-Kubernetes offers an excellent automated application deployment framework for container-based workloads. Services such as traffic management (load balancing within a cluster and across clusters/regions), service discovery, monitoring/analytics, and security are a critical component of an application deployment framework. Enterprises require a scalable, battle-tested, and robust services fabric to deploy business-critical workloads in production environments. This whitepaper provides an overview of the requirements for such application services and explains how Avi Networks provides a proven services fabric to deploy container based workloads in production environments using OpenShift- Kubernetes clusters.
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Avi Networks
Published By: Avi Networks     Published Date: Mar 06, 2019
Modern application architectures such as microservices are changing the way that modern enterprises run their infrastructure. Enterprises have become application-centric, investing significant effort and resources on continuous delivery goals and DevOps practices to achieve automation of routine IT and operations tasks. And now with the emergence of containerized applications, it is critical to re-evaluate how application services are provided across data centers and multiple cloud environments.
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Avi Networks
Published By: Avi Networks     Published Date: Mar 06, 2019
Software-defined architectures have transformed enterprises to become more application-centric. With application owners seeking public-cloud-like simplicity and flexibility in their own data centers, IT teams are under pressure to reduce wait times to provision applications. Legacy load balancing solutions force network architects and administrators to purchase new hardware, manually configure virtual services, and inefficiently overprovision these appliances. Simultaneously, new infrastructure choices are also enabling IT teams to re-architect applications into autonomous microservices from monolithic or n-tier constructs. These transformations are forcing organizations to rethink load balancing strategies and application delivery controllers (ADCs) in their infrastructure.
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Avi Networks
Published By: Intapp     Published Date: Jan 09, 2019
Intapp Time provides superior business intelligence thatchangesyour firm’sfundamental relationship with time.Thisunified suite of applications gives timekeepers access to time data and capture wherever they are: in the office, on a mobile device, online and offline.It is user-centric, offering a completely automated option while fullysupporting hands-on tracking—contemporaneous or reconstructionist.Intapp Time helps your business mine time data to reveal new sources of revenue, inform staff decisions, increase project efficiency, and reduce time leakage.
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business, business intelligence, time, tax, time for tax, intapp, applications, time data, automation, reporting, timekeeping, audit, accounting, consulting, professional services, active time capture, passive time capture, time tracking
    
Intapp
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