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Published By: graphgrid     Published Date: Oct 02, 2018
Whether itís 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 arenít 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: Alation     Published Date: Jan 06, 2017
90% of the time that is spent creating new reports is recreating information that already exists. Without a way to effectively share prior work and identify verified data sources, analysts and other data consumers lack shared context on how to apply data to analytic inquiries and business decision making. Time is wasted tracking down subject matter experts and trying to unearth tribal knowledge. Leading analytic organizations in retail, healthcare, financial services and technology are using data catalogs to help their analysts find, understand and use data appropriately. What are the 5 critical capabilities of a data catalog? Learn more here:
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Alation
Published By: Alation     Published Date: Jan 06, 2017
90% of the time that is spent creating new reports is recreating information that already exists. Without a way to effectively share prior work and identify verified data sources, analysts and other data consumers lack shared context on how to apply data to analytic inquiries and business decision making. Time is wasted tracking down subject matter experts and trying to unearth tribal knowledge. Leading analytic organizations in retail, healthcare, financial services and technology are using data catalogs to help their analysts find, understand and use data appropriately. What are the 5 critical capabilities of a data catalog? Learn more here:
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Alation
Published By: Adlib Software     Published Date: Feb 09, 2018
In financial services, contracts often exist in highly dispersed formats, with jurisdictional complexities and risk aspects that change over timeóresulting in high levels of risk. Learn how to transform contracts into actionable, defensible assets with a robust contract intelligence solution.
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Adlib Software
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 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: Cloudant - an IBM Company     Published Date: Jun 01, 2015
Whether you're a DBA, data scientist or developer, you're probably considering how the cloud can help modernize your information management and analytics strategy. Cloud data warehousing can help you get more value from your data by combining the benefits of the cloud - speed, scale, and agility - with the simplicity and performance of traditional on-premises appliances. This white paper explores how a cloud data warehouse like IBM dashDB can reduce costs and deliver new business insights. Readers will learn about: - How data warehousing-as-a-service helps you scale without incurring extra costs - The benefits of in-database analytics in a cloud data warehouse - How a cloud data warehouse can integrate with the larger ecosystem of business intelligence tools, both on prem and off prem
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nosql, ibm, dashdb, database, cloud
    
Cloudant - an IBM Company
Published By: Melissa Data     Published Date: Mar 23, 2017
In this eBook published by Melissa, author David Loshin explores the challenges of determining when data values are or are not valid and correct, how these values can be corrected, and how data cleansing services can be integrated throughout the enterprise. This Data Quality Primer eBook gives an overview of the five key aspects of data quality management (data cleansing, address data quality, address standardization, data enhancement, and record linkage/matching), as well as provides practical aspects to introduce proactive data quality management into your organization.
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Melissa Data
Published By: AnalytixDS     Published Date: May 09, 2016
This paper seeks to provide insight into how AnalytiX Data Services can address many of the data related issues that come with combining disparate source data as is often the case in mergers and acquisitions. It will cover some of the best features and functionality offered by AnalytiX Data Servicesí flagship product AnalytiX Mapping Manager, which have specific capabilities that are of high value in this scenario.
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AnalytixDS
Published By: Alation     Published Date: Mar 15, 2016
curation (noun): The act of organizing and maintaining a collection (such as artworks, artifacts, or data). Data curation is emerging as a technique to support data governance, especially in data-driven organizations. As self-service data visualization tools have taken off, sharing the nuances and best practices of how to use data becomes ever more critical. Analysts at companies from eBay to Safeway and Square are scaling their data knowledge through curation techniques. What are the 4 steps to successful data curation? Find out here:
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data stewardship, self-service analytics, data curation, data governance
    
Alation
Published By: Amazon Web Services     Published Date: Apr 04, 2016
Amazon DynamoDB is a fully managed, NoSQL database service. Many workloads implemented using a traditional Relational Database Management System (RDBMS) are good candidates for a NoSQL database such as DynamoDB. This whitepaper details the process for identifying these candidate workloads and planning and executing a migration to DynamoDB.
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Amazon Web Services
Published By: Snowflake Computing     Published Date: Apr 19, 2016
Data warehouse as a service brings scalability and flexibility to organizations seeking to deliver data to all users and systems that need to analyze it. The ability to access and analyze data is the critical foundational element for competing in new and old industries alike. Yet, a recent survey of IT executives finds that most are still strugglingó and frustrated ó with widely used data analytics tools. Find out what your peers are saying, and see how your data analytics environment compares.
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Snowflake Computing
Published By: Profium     Published Date: Mar 28, 2017
Profium Sense is an AI powered graph database which has unique features such as triggered query evaluation and ability to change rules in runtime. With support for open standards, it provides a reliable backbone for your next-generation digital services.
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Profium
Published By: Alteryx     Published Date: May 24, 2017
Spreadsheets are a mainstay in almost every organization. They are a great way to calculate and manipulate numeric data to make decisions. Unfortunately, as organizations grow, so does the data, and relying on spreadsheet-based tools like Excel for heavy data preparation, blending and analysis can be cumbersome and unreliable. Alteryx, Inc. is a leader in self-service data analytics and provides analysts with the ability to easily prep, blend, and analyze all data using a repeatable workflow, then deploy and share analytics at scale for deeper insights in hours, not weeks. This paper highlights how transitioning from a spreadsheet-based environment to an Alteryx workflow approach can help analyst better understand their data, improve consistency, and operationalize analytics through a flexible deployment and consumption environment.
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Alteryx
Published By: Dataiku     Published Date: Feb 01, 2018
A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. But what does running a POC mean in practice specifically for data science? POCs should prove not just that a solution solves one particular, specific problem, but that the solution in question will provide widespread value to the company: that it's capable of bringing a data-driven perspective to a range of the business's strategic objectives. Get the 7 steps to running an efficient POC in this white paper.
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Dataiku
Published By: Dataiku     Published Date: Feb 19, 2018
A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. But what does running a POC mean in practice specifically for data science? POCs should prove not just that a solution solves one particular, specific problem, but that the solution in question will provide widespread value to the company: that it's capable of bringing a data-driven perspective to a range of the business's strategic objectives. Get the 7 steps to running an efficient POC in this white paper.
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Dataiku
Published By: Bitwise     Published Date: Apr 30, 2018
Organizations that adopt an enterprise data lake model for real-time, self-service and advanced analytics require a fresh approach and outlook to develop a Data Governance strategy as Hadoop changes the way that organizations ingest and store data, as well as how business partners access and use data. This paper outlines pillars for Hadoop Data Governance and Security that provide a framework that can be applied to any company.
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Bitwise
Published By: graphgrid     Published Date: Oct 02, 2018
Whether itís 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 arenít 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.
Tags : 
    
graphgrid
Published By: Data Blueprint     Published Date: Apr 02, 2014
Organizations maintain data-based assets in hopes of successfully employing them in support of strategy. In an attempt to provide valued products and/or services, a customer relationship management (CRM) strategy should attempt to improve what is known about the wants and needs of existing customers. An organization may desire to transfer its inventory to its suppliers and to only play the role of transaction broker. A third strategy might be to use data to obtain significant efficiencies from productions/operations, ensuring a low cost advantage.
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data, data management, data value, return on investment, white paper
    
Data Blueprint
Published By: Cambridge Semantics     Published Date: Apr 03, 2014
A new approach to rapid, high-quality data integration, data services, and data governance.
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white paper, data, data mangement, enterprise information management, cambridge semantics, semantic technology
    
Cambridge Semantics
Published By: Spectrum Enterprise     Published Date: Oct 10, 2018
Migrate your organizationís voice service to our cloud with Hosted Voice, a fully managed, comprehensive and customized solution with unified communication and collaboration features. Our solutions include full technical support and best-in-class IP based phones.
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Spectrum Enterprise
Published By: BigCommerce     Published Date: Oct 16, 2018
Businesses who have lived through the evolution of the digital age are well aware that weíve experienced a generational shift in technology. The rise of software as a service (SaaS), cloud, mobile, big data, the Internet of Things (IoT), social media, and other technologies have disrupted industries and changed customersí expectations. In our always-on, buy anything anywhere world, customers want their shopping experiences to be personalized, dynamic, and convenient. As a result, many businesses are trying to reinvent themselves. Success in a fast-paced economy depends on continually adapting and innovating. Companies have to move quickly to keep up; thereís no time for disjointed technologies and old systems that donít serve the customer-obsessed mentality needed to thrive in the digital age.
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BigCommerce
Published By: Cisco EMEA     Published Date: Nov 08, 2018
Enterprise IT is changing. Itís evolving from a rigid, static, manually configured and managed architecture to one where connectivity is dynamic, application services are on demand, and processes are automated. Enterprise networking is evolving along with IT. This has been evident in the past several years in initiatives such as enterprise digitization and as-a-service consumption models, as well as their enablers, including BYOD, IoT and cloud. Add to this, all of the security implications of each initiative. The purpose of this paper is to assess the switching requirements for next-generation campus networks incorporating wired switches, wireless LANs and WAN routers in an intuitive, intent-based network supporting cloud, mobility, IoT and digitization, with pervasive security.
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Cisco EMEA
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