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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: Embarcadero     Published Date: Oct 21, 2014
Metadata defines the structure of data in files and databases, providing detailed information about entities and objects. In this white paper, Dr. Robin Bloor and Rebecca Jowiak of The Bloor Group discuss the value of metadata and the importance of organizing it well, which enables you to: - Collaborate on metadata across your organization - Manage disparate data sources and definitions - Establish an enterprise glossary of business definitions and data elements - Improve communication between teams
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data, data management, enterprise data management, enterprise information management, metadata, robin bloor, rebecca jozwiak, embarcadero
    
Embarcadero
Published By: MapR Technologies     Published Date: Aug 01, 2018
How do you get a machine learning system to deliver value from big data? Turns out that 90% of the effort required for success in machine learning is not the algorithm or the model or the learning - it's the logistics. Ted Dunning and Ellen Friedman identify what matters in machine learning logistics, what challenges arise, especially in a production setting, and they introduce an innovative solution: the rendezvous architecture. This new design for model management is based on a streaming approach in a microservices style. Rendezvous addresses the need to preserve and share raw data, to do effective model-to-model comparisons and to have new models on standby, ready for a hot hand-off when a production model needs to be replaced.
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MapR Technologies
Published By: Paxata     Published Date: Nov 29, 2016
Every organization looks for ways to reduce costs and run more efficiently. In fact, those are key drivers for the mainstream adoption of Hadoop and self-service BI tools. And while we can now collect and store more data than ever before, and we have enabled every information worker into a data-hungry analyst, not much consideration has been paid to the cost - including time and effort - of preparing data. Download this report to learn more about the hidden cost of data preparation.
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Paxata
Published By: Paxata     Published Date: Mar 21, 2017
Every organization looks for ways to reduce costs and run more efficiently. In fact, those are key drivers for the mainstream adoption of Hadoop and self-service BI tools. And while we can now collect and store more data than ever before, and we have enabled every information worker into a data-hungry analyst, not much consideration has been paid to the cost - including time and effort - of preparing data. Download this report to learn more about the hidden cost of data preparation.
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Paxata
Published By: VoltDB     Published Date: Jul 09, 2015
What is fast data? It's data in motion, and it creates Big Data. But handling it requires a radically different approach. Download the Fast Data Stack white paper from VoltDB. Learn how to build fast data applications with an in-memory solution that’s powerful enough for real-time stateful operations.
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data, data management, data stack, bug data, voltdb, database, nosql
    
VoltDB
Published By: VoltDB     Published Date: Feb 12, 2016
The need for fast data applications is growing rapidly, driven by the IoT, the surge in machine-to-machine (M2M) data, global mobile device proliferation, and the monetization of SaaS platforms. So how do you combine real-time, streaming analytics with real-time decisions in an architecture that’s reliable, scalable, and simple? In this report, Ryan Betts and John Hugg from VoltDB examine ways to develop apps for fast data, using pre-defined patterns. These patterns are general enough to suit both the do-it-yourself, hybrid batch/streaming approach, as well as the simpler, proven in-memory approach available with certain fast database offerings.
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VoltDB
Published By: Reltio     Published Date: Feb 12, 2016
Reltio delivers reliable data, relevant insights and recommended actions so companies can be right faster. Reltio Cloud combines data-driven applications with modern data management for better planning, customer engagement and risk management. IT streamlines data management for a complete view across all sources and formats at scale, while sales, marketing and compliance teams use data-driven applications to predict, collaborate and respond to opportunities in real-time. Companies of all sizes, including leading Fortune 500 companies in healthcare and life sciences, distribution and retail rely on Reltio.
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Reltio
Published By: Silwood Technology     Published Date: Mar 02, 2016
Ever since organisations started to implement packaged software solutions to solve business problems and streamline their processes there has been a need to access their data for the purposes of reporting and analytics, integration, governance, master data and more. Information Management projects such as these rely on data professionals being able to understand the underlying data models for these packages in order to be able to answer the critical question “Where’s the data?”. Without this knowledge it is impossible to ensure accuracy of data or timely delivery of projects. In addition the lack of discovery tools designed to meet this challenge has meant that performing this task has commonly been frustrating, time-consuming and fraught with risk. This white paper offers insight into why the traditional methods are not effective and how an innovative software product from Silwood Technology provides a faster and more effective approach to solving the problem.
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Silwood Technology
Published By: Looker     Published Date: Mar 15, 2016
Data centralization merges different data streams into a common source through unified variables. This process can provide context to overly-broad metrics and enable cross-platform analytics to guide better business decisions. Investments in analytics tools are now paying back a 13.01:1 return on investment (ROI), with increased returns when these tools integrate with three or more data sour- ces. While the perks of centralization are obvious in theory, the quantity and variety of data available in today’s landscape make this difficult to achieve. This report provides a roadmap for how to connect systems, data stores, and institutions (both technological and human). Learn: • How data centralization enables better analytics • How to redefine data as a vehicle for change • How the right BI tool eliminates the data analyst bottleneck • How to define single sources of truth for your organization • How to build a data-driven (not just data-rich) organization
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Looker
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: IDERA     Published Date: Nov 07, 2017
Data modeling is all about data definition but has a much wider impact on the data of your organization. Quality data definition impacts how data is produced and directly impacts how the data is or will be used throughout an organization. That means that we must proactively govern the process of how we define data, to establish a common understanding across the team. In this whitepaper, Robert Seiner describes how data modeling is a form of data governance and provides insights on the three actions of governing data.
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IDERA
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: 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: TopQuadrant     Published Date: Jul 18, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited.   Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data.     Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: TopQuadrant     Published Date: Aug 01, 2016
With information streaming in from more varied sources and at a faster pace than ever before, organizations are having an increasingly difficult time deriving accurate meaning from their data. Data governance systems that were once able to organize and process enterprise information are becoming too slow and limited. Semantic information management makes it easier to reconcile data from different sources by compiling and organizing information about that data, its metadata. By connecting all kinds of data and metadata in a more accessible way, semantic information systems empower users, data stewards and analysts to unlock and use the true meaning and value of their organization’s data. Learn more about the challenges in the evolving data landscape and how a semantic approach can help.
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TopQuadrant
Published By: DATAVERSITY     Published Date: Jan 23, 2013
No business likes to throw money out the window, or in the case of the modern day enterprise, down the electronic data stream. But, that is exactly what businesses all over the world are doing every day if they don’t have control of their data. This paper is sponsored by: ASG.
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white paper, dataversity, asg, metadata, business management, data, data management
    
DATAVERSITY
Published By: ASG     Published Date: Feb 05, 2013
No business likes to throw money out the window, or in the case of the modern day enterprise, down the electronic data stream. But, that is exactly what businesses all over the world are doing every day if they don’t have control of their data.
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white paper, dataversity, asg, metadata, business management, data, data management
    
ASG
Published By: MarkLogic     Published Date: Jun 16, 2013
The primary issue discussed within this paper boils down to two disparate database reliability models: ACID vs BASE. The first (ACID) has been around for some 30+ years, is a proven industry standard for SQL-centric and other relational databases, and works remarkably well in the older, yet still extant, world of vertical scaling. The second (BASE) has only recently gained popularity over the past 10 years or so, especially with the rise of social networking, Big Data, NoSQL, and other leviathans in the new world of Data Management. BASE requirements rose out of a need for ever-expanding horizontally scaled distributed networks, with non-relational data stores, and the real-time availability constraints of web-based transaction processing. While there are now more crossovers and negotiations between the two models, they essentially represent two competing groups, with Brewer’s CAP Theorem acting as the referee in the middle forcing tough decisions on each team.
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data, data management, unstructured data, nosql, database, acid, base, database transactioning
    
MarkLogic
Published By: VMware     Published Date: Oct 02, 2018
Digital disruption is fundamentally changing IT. Today’s organizations are under more pressure than ever to innovate fast and offer a superior experience to every customer. In this white paper, we explore the advantages that a modernized data center can bring for IT organizations seeking to keep pace in a dynamic environment, and how a software-defined approach can help move them forward. Real-world examples showcase how VMware is enabling IT teams to develop future-proof strategies with a foundation that is ready for cloud environments as well as global expansion and customer acquisitions. Submit the form to read this latest whitepaper to discover the advantages and how you could develop a future-proof strategy with VMware.
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VMware
Published By: VMware     Published Date: Oct 12, 2018
With the benefits quickly stacking up, it’s easy to understand why Gartner stated HCI (Hyper-Converged Infrastructure) as one of the hottest trends in data centre infrastructure. HCI is intended to reduce infrastructure complexity and cost, whilst enhancing scalability, agility and operational efficiency. This consolidated infrastructure enables organizations to leverage the software layer by using low cost commodity hardware, while reducing concerns around vendor lock-in, to form a seamless software- defined IT infrastructure environment well suited to today’s IT challenges. Simple to use and manage, without specialists and more cost-effective than most traditional solutions, it’s easy to understand why more organisations are making the move from traditional architecture to Hyper-Converged Infrastructure. Submit the form to view the infograph to discover the benefits and whether this solution is right for you.
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VMware
Published By: VMware     Published Date: Oct 12, 2018
Since Hyper Converged Infrastructure (HCI) emerged as a breakthrough technology, it has continued to gain taction as it has truly delivered on its promise. It has helped organizations optimize resources, reduce complexity, lower costs, increase agility and accelerate development cycles, as well as provide a seamless path to hybrid cloud. These are just a few of the key benefits causing IT leaders pay close attention to HCI and look at ways to use it to power key initiatives such as digital transformation. As IT leaders continue to embrace HCI and the market is expected to grow at a compound annual rate of 42% through 2023, the future is happening now. Submit the form to read our latest whitepaper and discover 5 powerful HCI case studies around Business critical applications, Hybrid Cloud/Multicloud, Disaster recovery, Edge computing, Container and App Development.
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VMware
Published By: Vena Solutions     Published Date: Oct 29, 2018
As digitization drives business at ever-faster speeds, CFOs recognize the need to keep pace. They understand the importance of financial planning and analysis (FP&A) solutions that allow their finance teams to develop budgets and forecasts quickly and accurately. They need confidence in their numbers and the decisions they drive. But selecting the right FP&A software is only half the battle.
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fp&a software, fp&a, financial planning and analysis, fp&a solutions, financial planning, financial analysis, fp&a process, fp&a implementation, finance software implementation, financial software implementation, enterprise financial software, financial systems, vena solutions
    
Vena Solutions
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