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Published By: DATAVERSITY     Published Date: Jul 06, 2015
The growth of NoSQL data storage solutions have revolutionized the way enterprises are dealing with their data. The older, relational platforms are still being utilized by most organizations, while the implementation of varying NoSQL platforms including Key-Value, Wide Column, Document, Graph, and Hybrid data stores are increasing at faster rates than ever seen before. Such implementations are causing enterprises to revise their Data Management procedures across-the-board from governance to analytics, metadata management to software development, data modeling to regulation and compliance. The time-honored techniques for data modeling are being rewritten, reworked, and modified in a multitude of different ways, often wholly dependent on the NoSQL platform under development. The research report analyzes a 2015 DATAVERSITY® survey titled “Modeling NoSQL.” The survey examined a number of crucial issues within the NoSQL world today, with focus on data modeling in particular.
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DATAVERSITY
Published By: Adaptive     Published Date: May 10, 2017
Enterprise metadata management and data quality management are two important pillars of successful enterprise data management for any organization. A well implemented enterprise metadata management platform can enable a successful data quality management at the enterprise level. This paper describes in detail an approach to integrate data quality and metadata management leveraging the Adaptive Metadata Manager platform. It explains the various levels of integrations and the benefits associated with each.
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Adaptive
Published By: TopQuadrant     Published Date: Jun 01, 2017
This paper presents a practitioner informed roadmap intended to assist enterprises in maturing their Enterprise Information Management (EIM) practices, with a specific focus on improving Reference Data Management (RDM). Reference data is found in every application used by an enterprise including back-end systems, front-end commerce applications, data exchange formats, and in outsourced, hosted systems, big data platforms, and data warehouses. It can easily be 20–50% of the tables in a data store. And the values are used throughout the transactional and mastered data sets to make the system internally consistent.
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TopQuadrant
Published By: CA Technologies     Published Date: Apr 24, 2013
Using ERwin Data Modeler & Microsoft SQL Azure to Move Data to the Cloud within the DaaS Lifecycle by Nuccio Piscopo Cloud computing is one of the major growth areas in the world of IT. This article provides an analysis of how to apply the DaaS (Database as a Service) lifecycle working with ERwin and the SQL Azure platform. It should help enterprises to obtain the benefits of DaaS and take advantage of its potential for improvement and transformation of data models in the Cloud. The use case introduced identifies key actions, requirements and practices that can support activities to help formulate a plan for successfully moving data to the Cloud.
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CA Technologies
Published By: MapR Technologies     Published Date: Aug 04, 2018
Legacy infrastructures simply cannot handle the workloads or power the applications that will drive business decisively forward in the years ahead. New infrastructure, new thinking and new approaches are in the offing, all driven by the mantra 'transform or die.' This book is meant for IT architects; developers and development managers; platform architects; cloud specialists; and big data specialists. For you, the goal is to help create a sense of urgency you can present to your CXOs and others whose buy-in is needed to make essential infrastructure investments along the journey to digital transformation.
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MapR Technologies
Published By: AnalytixDS     Published Date: Feb 28, 2015
With future business intelligence solutions clearly evolving from data that comes from highly efficient and well behaved systems, to data that comes from the extended enterprise where data is not necessarily so well structured and behaved - Organizations are forced into a more collaborative mode of operation with their core infrastructure being adapted from the consumer space, and to the extent possible, conformed to their existing repositories. This whitepaper attempts to address various challenges consumers face while managing enormous data sets within the context of this complex scenario. Further, we’ll try to answer the question: Is Big Data Governance really that different from traditional data governance initiatives? Finally, we’ll see how AnalytiX™ Mapping Manager™ can help organizations accelerate the development and deployment of a successful Big Data/ Business Intelligence platform and accelerate delivery of all sorts of data – structured, semi-structured as well as unstruc
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big data, big data governance, data governance, analytixds
    
AnalytixDS
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: Expert System     Published Date: Mar 19, 2015
Establishing context and knowledge capture In today’s knowledge-infused world, it is vitally important for organizations of any size to deploy an intuitive knowledge platform that enables delivery of the right information at the right time, in a way that is useful and helpful. Semantic technology processes content for meaning, allowing for the ability to understand words in context: it allows for better content processing and interpretation, therefore enabling content organization and navigation, which in turn increases findability.
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enterprise data management, unstructured data, semantic technology, expert system
    
Expert System
Published By: Ontotext     Published Date: Dec 21, 2015
Learn how semantic technologies make any content intelligent and turn it into revenue for your publishing business There is a smarter, cost-effective way for publishers to create, maintain and reuse content assets with higher accuracy. It is called dynamic semantic publishing. Putting Semantic Technologies at Work for the Publishing Industry An efficient blend of semantic technologies, dynamic semantic publishing enables powerful experiences when it comes to publishers’ main stock of trade: processing and representing information.
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Ontotext
Published By: Reltio     Published Date: Jan 20, 2017
If you invested in master data management (MDM), you are part of an elite association of those who have been able to afford the time, effort and resources to deploy what has characteristically been a tool, and discipline reserved for only the largest enterprises. Feedback from top industry analysts and companies that transitioned from legacy MDM to modern data management platforms, led to the compilation of a list of 10 warning signs you can use as a handy guide. If one or more of these signs get your attention, it warrants a serious conversation with your current provider about these issues, and how they compare to modern offerings available today.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Modern Master Data Management (MDM) is more than an extension of your data governance strategy. See how Reltio is taking MDM to the next level with its data platforms in AWS and Google Cloud.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Big data is growing faster than the capabilities available to manage and analyze it. Get this vendor comparison to learn how a modern master data management platform will help you to achieve better outcomes.
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Reltio
Published By: Reltio     Published Date: Nov 16, 2018
Explore this 31-criteria, Forrester Wave Report on MDM platforms and vendors. You'll discover an evaluation of 12 vendors including leader Reltio with modern Master Data Management.
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Reltio
Published By: Snowflake Computing     Published Date: Feb 27, 2017
Snowflake’s cloud-built data warehouse delivers the performance, concurrency, simplicity and affordability needed to store and analyze all of an organization’s data in one location. Snowflake combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud. Find out more at snowflake.net.
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Snowflake Computing
Published By: Finch Computing     Published Date: Apr 26, 2016
FinchDB is not just a database, not just an analytics engine and not just a search tool. It’s all three. All together. All in-memory. It’s a new, enabling platform technology built on an IP portfolio of 25 unique inventions, and suited for multiple high-volume, high-stakes use cases. While other big data solutions are answers-oriented, FinchDB enables users to ask better questions of their data. Because better questions must come before better answers.
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Finch Computing
Published By: Datawatch     Published Date: Apr 06, 2018
Enterprises are focusing on becoming ever more data-driven, meaning that it is simply unacceptable to allow data to go to waste. Yet, as the amount of data businesses collect and control continues to increase exponentially, many organizations are failing to derive enough business value from their data. Companies are feeling the pressure to extract maximum value from all of their data, both defensive and offensive. Defensive analytics are the “plumbing aspects” of data management that must be captured to mitigate risk and establish a basic understanding of business performance. Offensive analytics build on defensive analytics and support overarching business objectives, strategic initiatives and long-term goals using predictive models. In this whitepaper, you will learn how to address many challenges, including streamlining operational reporting, delivering insight and providing a single, unified platform for everyone.
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Datawatch
Published By: Attunity     Published Date: Sep 21, 2018
Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It provides an end-to-end platform that can collect, curate, analyze, and act on data in real-time, on-premises, or in the cloud with a drag-and-drop visual interface. This book offers you an overview of NiFi along with common use cases to help you get started, debug, and manage your own dataflows.
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Attunity
Published By: Attunity     Published Date: Oct 19, 2018
Change data capture (CDC) technology can modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems. To realize these benefits, enterprises need to understand how this critical technology works, why it’s needed, and what their Fortune 500 peers have learned from their CDC implementations. This book serves as a practical guide for enterprise architects, data managers and CIOs as they enable modern data lake, streaming and cloud architectures with CDC. Read this book to understand: ? The rise of data lake, streaming and cloud platforms ? How CDC works and enables these architectures ? Case studies of leading-edge enterprises ? Planning and implementation approaches
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Attunity
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: graphgrid     Published Date: Oct 02, 2018
Whether it’s for a specific application, optimizing your existing operations, or innovating new customer services, graph databases are a powerful technology that turn accessing and analyzing your data into a competitive advantage. Graph databases resolve the Big Data limitations and free up data architects and developers to build amazing solutions that predict behaviors, enable data driven decisions and make insightful recommendations. Yet just as cars aren’t functional with only engines, graph databases require surrounding capabilities including ingesting multi-source data, building data models that are unique to your business needs, ease of data interaction and visualization, seamless co-existence with legacy systems, high performance search capabilities, and integration of data analysis applications. Collectively, this comprehensive data platform turns graph capabilities into tangible insights that drive your business forward.
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graphgrid
Published By: EnterpriseDB     Published Date: Sep 02, 2014
This technical paper from EnterpriseDB reviews and illustrates Postgres’ NoSQL capabilities in the context of Postgres’ robust relational competencies. It describes performance tests that demonstrate that Postgres is a superior platform for handling most NoSQL workloads.
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white paper, nosql, database, enterprisedb, postgres
    
EnterpriseDB
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
Published By: Cisco EMEA     Published Date: Mar 08, 2019
The Cisco Meeting and TeamCollaborationExperienceThe workplace has changed and today themost agile workforces outperform traditional setups. But the reality of modern business life is, ifyou want a culture of innovation, you have tomake it yourself.Teams need a workplace that’s focussed oninnovation and speed. Introducing Cisco WebexTeams, a platform that helps teams to do it all.Essential kit for forward-thinking smallbusinesses.
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Cisco EMEA
Published By: Cisco EMEA     Published Date: Mar 08, 2019
The Cisco Meeting and Team Collaboration Experience The workplace has changed and today the most agile workforces outperform traditional set ups. But the reality of modern business life is, if you want a culture of innovation, you have to make it yourself. Teams need a workplace that’s focussed on innovation and speed. Introducing Cisco Webex Teams, a platform that helps teams to do it all. Essential kit for forward-thinking small businesses.
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Cisco EMEA
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
With the maturing of the all-flash array (AFA) market, the established market leaders in this space are turning their attention to other ways to differentiate themselves from their competition besides just product functionality. Consciously designing and driving a better customer experience (CX) is a strategy being pursued by many of these vendors.This white paper defines cloud-based predictive analytics and discusses evolving storage requirements that are driving their use and takes a look at how these platforms are being used to drive incremental value for public sector organizations in the areas of performance, availability, management, recovery, and information technology (IT) infrastructure planning.
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Hewlett Packard Enterprise
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