data quality

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By: IBM     Published Date: Jul 06, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality, data integration, data center
     IBM
By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. 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.
Tags : ibm, idc, big data, data, analytics, information governance, knowledge management, data management, data center
     IBM
By: IBM     Published Date: Oct 13, 2016
Data quality and master data management in a hybrid environment
Tags : ibm, mdm, big data, ibm infosphere, knowledge management, enterprise applications, business technology
     IBM
By: IBM     Published Date: Jan 27, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, as discussed in “The truth about information governance and the cloud,” most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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     IBM
By: Oracle     Published Date: Jul 31, 2017
Consolidation in the healthcare industry has reached a record pace. The volume of organizational change has generated solid templates and best practices for change management. In addition, technological advances provide opportunities for sophisticated data analytics and systems integrations. By identifying and taking advantage of these technologies, healthcare organizations can increase the odds of successful integrations that result in greater agility decrease their cost base, and improve the quality of care they provide.
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     Oracle
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.
Tags : ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management, business technology
     IBM
By: IBM     Published Date: May 23, 2017
This paper is on impact of the new features now available with version 11.1. It covers the use of DB2 within hybrid cloud environments.
Tags : encryption, application development, operating system, market intelligence, data governance, data migration, data quality, ibm
     IBM
By: IBM     Published Date: Aug 23, 2017
Banks today are continuously challenged to meet rigorous regulatory requirements. They must implement strict governance programs that enable them to comply with a wide variety of regulations stemming from the financial crisis that began in 2007, including the DoddFrank Act, Basel Committee on Banking Supervision regulations, the General Data Protection Regulation (GDPR), the Revised Payment Services Directive (PSD2) and the revised Markets in Financial Instruments Directive To keep pace with regulatory changes, many banks will need to reapportion their budgets to support the development of new systems and processes. Regulators continually indicate that the banks must be able to provide, secure and deliver high-quality information that is consistent and mature.
Tags : risk mitigation, data aggregation, risk reporting, banking
     IBM
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
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)."
Tags : data analysis, data analytics, dashboards
     IBM
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
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
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
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
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
By: Group M_IBM Q4'19     Published Date: Sep 27, 2019
Data quality tools are vital for digital business transformation, especially now that many have emerging features like automation, machine learning, business-centric workflows and cloud deployment models. This Magic Quadrant assesses 15 vendors to help you make the best choice for your organization.
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     Group M_IBM Q4'19
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
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.
Tags : cyrusone, data, technology, productivity, engineering
     CyrusOne
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.
Tags : white paper, homegrown, erp software, erp software solution, data management, data quality, data duplication, data knowledge, business technology
     Epicor
By: BMC ESM     Published Date: Aug 20, 2009
Automating your data center can improve operational efficiency and give you control over service quality, security, and business agility, while simultaneously reducing risk and costs.
Tags : data center, operational efficiency, service, security, business agility, automation, bmc, esm, virtualization, it infrastructure, it management, enterprise applications
     BMC ESM
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
By: MarkLogic     Published Date: Mar 29, 2018
It’s your golden opportunity: Rapidly integrate and harmonize data silos. Enhance drug discovery. Achieve faster time to insight. Get to market faster — all with less cost than you think. Explore how Life Sciences organizations can accelerate Real World Evidence (RWE) in a comprehensive and cost efficient manner. Download this white paper to learn about challenges, solutions and most importantly — how to equip your organization for success.
Tags : manufacturers, organizations, integration, optimization, data, quality
     MarkLogic
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.
Tags : enterprise, metadata, management, organizations, technology, tools, mark logic
     MarkLogic
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.
Tags : agile, enterprise, metadata, management, organization
     MarkLogic
By: VMware     Published Date: May 10, 2017
What is a digital workspace and what does it take to create one? If we break it down, the workspace is a portal for end users into all of their apps and online services that they canseamlessly and securely access across devices and locations. But what makes the workspace of today different from the desktop or mobile device of the past? And how can you move forward with delivering a digital workspace? Download this solution brief to learn how VMware® Workspace™ ONE™is designed to deliver a digital workspace that integrates device management, application delivery, and identity management into a single platform on your terms, via your data center, in the cloud, or through a combination of the two. This workspace can be accessed by your end users across devices and locations and be centrally secured and supported to streamline management and improve the quality of services you deliver across the entire organization.
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     VMware
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