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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: 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: Pentaho     Published Date: Jul 23, 2014
Pentaho Analytics for MongoDB will teach you MongoDB and Pentaho integration points and developer skills needed to create turnkey analytic solutions that deliver insight and drive value for your organization.
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nosql, ebook, pentaho, analytics, business intelligence, mongodb
    
Pentaho
Published By: Access Sciences     Published Date: Sep 07, 2014
Few organizations have fully integrated the role of the Data Steward due to concerns about additional project complexity, time away from other responsibilities or insufficient value in return. The principles of the Agile methodology (whether or not Agile is followed for projects) can offer guidance in making the commitment to designating and empowering the Data Steward role. By placing insightful people in a position to connect innovators, respond to change and spur development aligned with business activities, organizations can expect to see a more efficient and effective use of their information assets.
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Access Sciences
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: 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: Neo Technology     Published Date: Feb 15, 2018
By itself, data offers finite value. But when connected, its value is infinite. Discover how enterprise organizations such as Airbnb, eBay and Telia used connected data and graph technology in order to create a sustainable competitive advantage. This white paper shows business leaders how to take advantage of data relationships with graph technology.
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Neo Technology
Published By: Experian     Published Date: Mar 30, 2017
Businesses today recognize the importance of the data they hold, but a general lack of trust in the quality of their data prevents them from achieving strategic business objectives. Nearly half of organizations globally say that a lack of trust in their data contributes to increased risk of non-compliance and regulatory penalties (52%) and a downturn in customer loyalty (51%). To be of value to organizations, data needs to be trustworthy. In this report, you will read about the findings from this unique study, including: · How data powers business opportunities · Why trusted data is essential for performance · Challenges that affect data quality · The current state of data management practices · Upcoming data-related projects in 2017
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Experian
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: 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: IDERA     Published Date: Feb 06, 2017
Data modeling can provide tangible economic benefits, which are best shown by quantifying the traditional benefits of data modeling. In this whitepaper, Tom Haughey discusses how to calculate the return on investment (ROI) of data modeling by assessing the economic value of real data modeling benefits, such as improved requirements definition, reduced maintenance, accelerated development, improved data quality and reuse of existing data assets. Download this whitepaper to learn how to: - Describe the value proposition of data modeling - Assess the economic value of data modeling benefits - Learn three methods to calculate data modeling ROI
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IDERA
Published By: MariaDB     Published Date: Apr 02, 2018
Learn how to use JSON functions for semi-structured data This white paper explains step-by-step how to support semi-structured data with JSON functions, introduced in MariaDB Server 10.2, using a practical use case with sample data and queries for everything from creating, reading and querying JSON documents to enforcing data integrity with check constraints and functions. You will learn how to: • Create, read and update JSON documents • Index and query JSON documents • Enforce data integrity with JSON documents • Combine relational data and JSON documents • Return JSON documents as relational data • Return relational data as JSON documents
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MariaDB
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: graphgrid     Published Date: Oct 19, 2018
Graph databases are about to catapult across the famous technology adoption chasm and land in start-ups, enterprises and government agencies across the globe. The adoption antibodies are subsiding as the power of natively connected data becomes fundamental to any organization looking for data-driven insights across operations, suppliers, and customers. Moore’s Law increases in storage capacity and processing power can no longer keep up with the pace of data expansion, yet how companies structure and analyze their data ultimately will impact their ability to compete. Unstructured, disconnected data is useless. Graph databases will rapidly jump from niche use cases to a transformative IT technology as they enable turning the data you collect into actionable insights. Data will become the single most differentiating asset for your organization.
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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: Adaptive     Published Date: Jan 24, 2013
Data Governance and Metadata Management are two closely associated Data Management Capabilities which organizations must address in order to truly turn their data into Information Assets.
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data, data management, data governance, metadata, adaptive, dataversity, white paper
    
Adaptive
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: Spectrum Enterprise     Published Date: Mar 01, 2019
The scalability of its EP-LAN lets MMC Corp seize new opportunities without adding infrastructure. For example, Scales and Trusler are looking at virtual desktops or virtual desktop image [VDI] files for some offices and even job sites. “We’ll probably have to scale some bandwidth internally for that,” Trusler notes, “but if we do the VDI internally or we do it with an external third party, it doesn’t really matter… because we can get them on that EP-LAN network and we can get the bandwidth that we need… quickly.” EP-LAN is scalable. In most cases, adding additional services at a specific customer location can easily be turned up by Spectrum Enterprise remotely. Choosing a fiber EP-LAN over MPLS not only met the challenge to connect MMC Corp locations: it created an IT platform that continues to scale to support rapid expansion and innovation.
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Spectrum Enterprise
Published By: Hitachi Vantara     Published Date: Mar 08, 2019
In a perfect world, downtime would be a thing of the past, however, as organizations continue their digital transformation journeys, more data assets are being created—generating, in turn, higher availability demands. Delivering on availability service levels is not just a technical responsibility, but also a business imperative extending well beyond IT. The consequences of failing to meet service levels can be dire and costly. Read this white paper to learn how the right tools can minimize downtime.
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Hitachi Vantara
Published By: Sage People     Published Date: Jan 04, 2019
Do you know your people as well as you know your customers? Your people’s expectations and the way they work is changing. Employees are more diverse, mobile and technologically-savvy than ever before. HR processes are changing from focusing on transactions to knowing and engaging people. Just as sales and marketing teams use data to develop actionable and informed insights about their customers, you need to do the same in HR to know your people. Everything, from attracting and keeping the best talent, to creating better workplace experiences and increasing employee engagement and productivity, depends on smarter decisions. These in turn rely on more actionable insights. These are only possible through accurate HR data and analytics. They are vital to address the people challenges you face, so you can make smarter decisions. Discover in this guide how to improve visibility of your workforce with data-driven and actionable insights. Ultimately, it will help you know your people
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Sage People
Published By: Sage People     Published Date: Jan 31, 2019
The way we work has completely transformed. New technology is changing how, where and when we work. In this new landscape, businesses face challenges around growth, talent acquisition and productivity. Employers need to embrace new technology to get ahead in this new world of work, and put people at the heart of their strategy. However, HR and People leaders are in fierce competition for that all-important slice of budget and that makes building the strongest business case for technology investment vital. This guide is designed to help HR and People leaders like you get the financial support you need. You’ll get practical, effective tips on: • Understanding and explaining the true benefits of investing in a new HR system and likely return on investment • Positioning HR as a leader of change throughout your business • Ensuring your HR vision fits in with the business strategy • Getting management and key stakeholder buy-in • Building the strongest business case and the most powerful el
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Sage People
Published By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state, governmental, decisions, data management
    
Aberdeen
Published By: Sage EMEA     Published Date: Jan 29, 2019
SagecommissionedForresterConsultingtoconducta TotalEconomicImpact™(TEI)studytoexaminethe potentialreturnoninvestment(ROI)organizationsmay realizebydeployingits Enterprise Management solutionas part of Sage Business Cloud.Thepurpose ofthisstudyistoprovidereaders withaframework to evaluatethepotentialfinancialimpactof Enterprise Managementwithintheir organizations. Tobetter understandthebenefits,costs,andrisks associatedwithaninvestmentinEnterprise Management,Forrester conducted in-depth interviews withtwoEnterprise Managementcustomers. For a brief description of each customer, see the Analysis section. According toSage,Enterprise Managementis an integratedand globalenterprise business management solution for purchasing, manufacturing, inventory, sales, customer service,and financial management. Formoredetails ontheEnterprise Management solution,seeAppendix A. For this TEI study, Forrester has created a compositeOrganizationto illustrate the quantifiable benefits and costs of investing i
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Sage EMEA
Published By: Red Hat     Published Date: Feb 25, 2019
Red Hat can help you deliver 348% ROI and achieve agile, high-performing infrastructures Linux® has become the standard operating system for cloud infrastructure as well as the preferred delivery vehicle for modern applications. This is, in part, thanks to it being reliable environment that offers scale, security, and robust application support. Red Hat® Enterprise Linux expands on this trust and credibility by offering a supported, hardened, enterprise environment that delivers on more efficient operational costs, better reliability and availability, and better scalability. These translate into a better return on investment (ROI) for our enterprise customers. IDC’s study, “The Business Value of Red Hat Enterprise Linux,” interviewed 12 organizations to see how they’re using Red Hat Enterprise Linux to support their business operations. These organizations reported that Red Hat provides a cost-effective, efficient, and reliable operating environment. There’s a lot to gain with Red H
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Red Hat
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