quality data

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IDC Whitepaper: Big Data, Bad Data, Good Data - The Link Between Information Governance and Big Data

Published By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management
    
IBM

DevOps For Dummies

Published By: IBM     Published Date: Aug 30, 2017
DevOps (short for development and operations), like most new approaches, is only a buzzword for many people. Everyone talks about it, but not everyone knows what it is. In broad terms, DevOps is an approach based on lean and agile principles in which business owners and the development, operations, and quality assurance departments collaborate to deliver software in a continuous manner that enables the business to more quickly seize market opportunities and reduce the time to include customer feedback. Indeed, enterprise applications are so diverse and composed of multiple technologies, databases, end-user devices, and so on, that only a DevOps approach will be successful when dealing with these complexities. Opinions differ on how to use it, however. Some people say that DevOps is for practitioners only; others say that it revolves around the cloud. IBM takes a broad and holistic view and sees DevOps as a business-driven software delivery approach  — an approach that takes a new or en
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devops, ibm, quality assurance, end-user devices, customer engagement
    
IBM

Magic Quadrant for Data Quality Tools

Published By: IBM     Published Date: Oct 17, 2017
The data quality tools market continues to show strong revenue growth, driven by cost, process optimization and digital business initiatives. Applying data quality tools to existing and emerging business scenarios will enable data and analytics leaders to deliver greater business value.
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IBM

Turn Your Customers into Brand Champions

Published By: Reputation.com     Published Date: Oct 02, 2017
1.Meet the new consumer The migration to mobile and social media will challenge — and change — everything we know about consumer marketing. 2. Who owns your brand? Brand equity can no longer be bought. Online reviews now generate total market transparency for location-based businesses. Reviews tilt the balance of branding power away from companies and into the hands of customers. 3. The battle for brick-and-mortar customers is won or lost on the social web. To win, marketers must actively enlist customers as online advocates. Those who scale online review volume and quality will be rewarded with higher search visibility and more business at street level. 4. “Dark data” provides priceless operational insights Vast amounts of unstructured, unmined sentiment data on social media provides feedback about the customer experience that you can filter using thematic analysis and use to improve operations at the national or location level. 5. Business implications Online reputation stands betwee
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Reputation.com

Moving from Continuous Accounting to Risk Intelligent RPA

Published By: Trintech EMEA ABM Pilot     Published Date: Nov 03, 2017
Over the past few years, terms such as: ‘Modern Finance,’ ‘Continuous Accounting’ and ‘Robotic Process Automation’ have all created buzz across the finance industry. These have been launched as a response to the challenges facing finance around attracting and retaining high quality employees, the rising risks due to the difficulty in certifying accurate data, today, and the expectation that finance has a role in driving the business forward.
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account reconciliation, accounting automation, finance shared services, finance transformation program, finance transformation strategy, financial close, financial close process, reconciliation software
    
Trintech EMEA ABM Pilot

Tell Your Story! With Killer Reports and Dashboards

Published By: IBM     Published Date: Jun 04, 2018
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust. Watch this webinar to learn: • How you can more effectively communicate with data. • What constitutes an intuitive and highly navigable report • How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time. • Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
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data analysis, data analytics, dashboards
    
IBM

The value of knowing: Build a trusted analytics foundation

Published By: IBM     Published Date: Jul 09, 2018
As the information age matures, data has become the most powerful resource enterprises have at their disposal. Businesses have embraced digital transformation, often staking their reputations on insights extracted from collected data. While decision-makers hone in on hot topics like AI and the potential of data to drive businesses into the future, many underestimate the pitfalls of poor data governance. If business decision-makers can’t trust the data within their organization, how can stakeholders and customers know they are in good hands? Information that is not correctly distributed, or abandoned within an IT silo, can prove harmful to the integrity of business decisions. In search of instant analytical insights, businesses often prioritize data access and analysis over governance and quality. However, without ensuring the data is trustworthy, complete and consistent, leaders cannot be confident their decisions are rooted in facts and reality
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IBM

Enterprise data warehouse optimization

Published By: Group M_IBM Q418     Published Date: Oct 15, 2018
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data. Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
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Group M_IBM Q418

Energy Resilience: Building The Business Case

Published By: Centrica Business Solutions     Published Date: Aug 14, 2018
The energy landscape has become increasingly complex. Globally, we’re relying less on centralized, steady power sources – such as gas-fired and coal-fired power stations – and more on mixed, locally-distributed renewable energy supplies including solar, wind, tidal and battery. While this is positive for the environment and carbon emissions, it makes balancing power grids a much more complex task. Power quality and reliability becomes more variable in output, while demand for power continues to increase steadily. But when it comes to energy resilience, many organizations simply don’t know where to start. What solutions are available? Which are the best ones for their specific situation and physical premises? What will be their return on investment? Is it simply the cost of doing business, or is there actually a business case? The guide will give you the tools and data to build your understanding and quantify the benefit for your organization.
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energy, resilience, building, business, energy
    
Centrica Business Solutions

Gartner Magic Quadrant for Data Quality Tools

Published By: Group M_IBM Q119     Published Date: Jan 08, 2019
The discipline of data quality assurance ensures that data is "fit for purpose" in the context of existing business operations, analytics and emerging digital business scenarios. It covers much more than just technology. It includes program management, roles, organizational structures, use cases and processes (such as those for monitoring, reporting and remediating data quality issues). It is also linked to broader initiatives in the field of enterprise information management (EIM), including information governance and master data management (MDM)
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Group M_IBM Q119

Uncover the story hidden in your data Four ways IBM Watson Health is uniquely positioned to help you

Published By: Group M_IBM Q2'19     Published Date: May 28, 2019
Amid the rising costs of healthcare, employers and health plans are under increasing pressure to produce fast insights from their data to help drive business decisions, identify opportunities to reduce cost, improve care quality and generate reports for diverse stakeholders. But these professionals often lack the time, resources and analytic expertise necessary to integrate and interpret the massive amounts of disparate data available to them.
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Group M_IBM Q2'19

The journey to AI and business-ready data begins with information architecture

Published By: Group M_IBM Q4'19     Published Date: Sep 27, 2019
Data is multiplying rapidly in quantity and variety for enterprises of all kinds. In multicloud environments, a range of data sources is exponentially increasing the stream of incoming information, from the Internet of Things and social media, to mobile devices, virtual reality implementations and optical tracking. While organizations are readily investing in artificial intelligence (AI), most haven’t done due diligence to understand their data or ensure the quality of data needed to benefit from AI solutions. In many organizations, their data is inaccessible, unreliable, or non-compliant with data privacy and protection rules.
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Group M_IBM Q4'19

A guide to optimizing digital marketing performance through better data.

Published By: Claravine     Published Date: Jan 03, 2019
Marketers have long struggled with the simple task of knowing which marketing spend is truly effective, and how to optimize that spend. At the heart of the issue lies the challenge of ensuring the data quality and consistency exists to make decisions based on real intelligence. Why is this a problem? First, effective tracking is reliant on the consistent, complete application of campaign tracking codes and associated metadata, which has traditionally been a manual, ungoverned process. Adding to this complexity has been the dramatic expansion of digital marketing point solutions, and the disparate teams expected to execute across each of these channels and geographies. The result is what you would expect—highly inaccurate, incomplete, and inconsistent data that must be manually cleaned before reporting is possible. Fortunately a solution exists. Progressive marketing leaders are implementing Digital Experience Data Management (DXDM), ensuring the rich, consistent insights critical to ma
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Claravine

Ability to Build Hyper-Scale Data Centers at Hyper-Speed Helps Eliminate IT Expansion Risk

Published By: CyrusOne     Published Date: Jul 05, 2016
In June 2016, CyrusOne completed the Sterling II data center at its Northern Virginia campus. A custom facility featuring 220,000 square feet of space and 30 MW of power, Sterling II was built from the ground up and completed in only six months, shattering all previous data center construction records. The Sterling II facility represents a new standard in the building of enterpriselevel data centers, and confirms that CyrusOne can use the streamlined engineering elements and methods used to build Sterling II to build customized, quality data centers anywhere in the continental United States, with a similarly rapid time to completion.
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cyrusone, data, technology, productivity, engineering, best practices, business analytics, business intelligence
    
CyrusOne

9 Reasons to Retire Your "Homegrown" ERP Software Solution Before It's Too Late

Published By: Epicor     Published Date: Aug 02, 2012
Risk-averse distributors may feel that the safest and simplest IT strategy is to stay with their existing "homegrown" enterprise resource planning (ERP) solution. But just as sticking your money under the mattress offers no protection against inflation, maintaining an outdated system can rob you of a distinct competitive advantage. Modern ERP systems offer so much more in terms of data access, technology advances, and standard operating procedures. And obtaining a solution from a leading ERP provider ensures that industry best practices and the experiences of other distributors and end users have been built in. Check out this new paper and learn more about the advantages of an integrated ERP over your homegrown system.
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white paper, homegrown, erp software, erp software solution, data management, data quality, data duplication, data knowledge
    
Epicor

Data Management: What You Need to Know and Why

Published By: SAS     Published Date: Sep 19, 2018
We are offering this second edition resource as a business oriented, working guide to core data management practices. In this ebook you will find easy to digest resources on the value and importance of data preparation, data governance, data integration, data quality, data federation, streaming data, and master data management.
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SAS

Agile Enterprise Metadata Management

Published By: MarkLogic     Published Date: Mar 29, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools. MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.
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enterprise, metadata, management, organizations, technology, tools, mark logic
    
MarkLogic

Agile Enterprise Metadata Management

Published By: MarkLogic     Published Date: May 07, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools. MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.
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agile, enterprise, metadata, management, organization
    
MarkLogic

Guaranteeing Storage Performance with SolidFire Quality of Service

Published By: NetApp     Published Date: Sep 19, 2017
This SolidFire definitive guide provides an overview on storage Quality of Service and its importance in the Next-Generation Data Center.
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netapp, database performance, flash storage, data management, cost challenges, solidfire, service
    
NetApp

On Demand Replay: Cost Visibility Across the Episode of Care

Published By: Oracle     Published Date: Feb 21, 2018
To reduce risk and cost, as well as better serve individuals and populations, visibility across the entire episode of care is essential. Oracle’s Cost Effective Healthcare solution combines cost, quality and clinical data to analyze root causes and variations. Our customers are transforming to more competitive, financially viable healthcare organizations using Oracle’s secure, modern Cloud solution. During this webinar, you’ll learn: Reduce cost by analyzing episode of care outliers Alleviate risk due to clinical variations and value-based contracts Lessen IT cost with a consolidated, secure Cloud Platform Understand the tangible business value our healthcare customers are realizing
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Oracle

How To Successfully Select An ERP System In Eight Simple Steps

Published By: Epicor Software Corporation     Published Date: Apr 12, 2017
An Enterprise Resource Planning (ERP) system is a series of software applications or modules that collects data from your sales, purchasing, finance, inventory, supply chain, manufacturing and quality functions into a common database so that your company can share the information, coordinate activities and collaborate. If you’re looking for your first ERP system or looking to upgrade from an existing system, the evaluation, selection and implementation process is a long-term strategic decision for your organization.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Epicor Software Corporation

Improving Data Preparation for Business Analytics

Published By: Alteryx, Inc.     Published Date: Sep 06, 2017
From small organizations using spreadsheets and visual discovery tools to large enterprises trying to improve data quality and delivery, data preparation difficulties are a major concern. Download your complimentary copy of the full report so you can tackle your data preparation challenges.
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Alteryx, Inc.

Applied Pressure: The Strains on an Ailing Implantable Medical Device Supply Chain

Published By: UPS     Published Date: Sep 05, 2017
Our active and actively aging population is the dichotomy fueling significant growth for implantable medical devices. Innovations focused on mobility, engagement and quality of life are directly targeting this growing population. The implantable medical device industry is poised to capitalize on these unique needs, while simultaneously meeting unprecedented cost pressures. It is time for manufacturers to seek expertise in inventory management and logistics for greater visibility, control and profitability. For implantable medical device manufacturers to be as active and healthy as the patients they serve, their future depends on the ability to differentiate products — not only by price, but through cost, service and documented outcomes. New trends in personal health tracking keep patients moving, and data collection will similarly improve the health of your business.
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medical devices, inventory management, logistics, clinical outcomes data, ups
    
UPS

Manufacturing Intelligence for the Next Industrial Revolution (Infographic)

Published By: TIBCO Software     Published Date: Sep 12, 2018
By processing real-time data from machine sensors using artificial intelligence and machine learning, it’s possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield. Read about our top data science best practices for becoming a smart manufacturer.
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inter-company connectivity, real-time tracking, automate analytic models, efficient analytics, collaboration
    
TIBCO Software

Manufacturing Intelligence: Keep Your Processes Under Control

Published By: TIBCO Software     Published Date: Feb 01, 2019
The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and no need to rework faulty products. To satisfy the customer demand behind this trend, manufacturers must move quickly to new production models. Quality assurance is the key area that IT must support. At the same time, the traceability of products becomes central to compliance as well as quality. Traceability can be achieved by interconnecting data sources across the factory, analyzing historical and streaming data for insights, and taking immediate action to control the entire end-to-end process. Doing so can lead to noticeable cost reductions, and gains in efficiency, process reliability, and speed of new product delivery. Additionally, analytics helps manufacturers find the best setups for machinery.
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data, product, manufacturers, manufacturing, processes, technologies, analysis, quality
    
TIBCO Software
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