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Published By: Trillium Software     Published Date: Dec 17, 2015
Digital business and disruptive technologies continue to fuel solid growth in the data quality tools market, alongside traditional cost reduction and process optimization efforts. This Magic Quadrant will help CIOs, chief data officers and information leaders find the best vendor for their needs.
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Trillium Software
Published By: DATAVERSITY     Published Date: Nov 05, 2014
Ask any CEO if they want to better leverage their data assets to drive growth, revenues, and productivity, their answer will most likely be “yes, of course.” Ask many of them what that means or how they will do it and their answers will be as disparate as most enterprise’s data strategies. To successfully control, utilize, analyze, and store the vast amounts of data flowing through organization’s today, an enterprise-wide approach is necessary. The Chief Data Officer (CDO) is the newest member of the executive suite in many organizations worldwide. Their task is to develop and implement the strategies needed to harness the value of an enterprise’s data, while working alongside the CEO, CIO, CTO, and other executives. They are the vital “data” bridge between business and IT. This paper is sponsored by: Paxata and CA Technologies
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chief data officer, cdo, data, data management, research paper, dataversity
    
DATAVERSITY
Published By: SAP     Published Date: May 19, 2016
SAP® solutions for enterprise information management (EIM) support the critical abilities to architect, integrate, improve, manage, associate, and archive all information. By effectively managing enterprise information, your organization can improve its business outcomes. You can better understand and retain customers, work better with suppliers, achieve compliance while controlling risk, and provide internal transparency to drive operational and strategic decisions.
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SAP
Published By: First San Francisco Partners     Published Date: Mar 13, 2015
A Data Governance Organization and its structure should be defined to align with your company’s organizational hierarchy and resources. Finding the right people to assign to data governance requires an understanding of both the functional and the political role of governance within your organization. This paper highlights some best practices in putting the right resources behind the required roles.
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data governance, data governance resources, data governance organization
    
First San Francisco Partners
Published By: First San Francisco Partners     Published Date: Jun 01, 2016
A Data Governance Organization and its structure should be defined to align with your company’s organizational hierarchy and resources. Finding the right people to assign to data governance requires an understanding of both the functional and the political role of governance within your organization. This paper highlights some best practices in putting the right resources behind the required roles.
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First San Francisco Partners
Published By: Couchbase     Published Date: Dec 04, 2014
Interactive applications have changed dramatically over the last 15 years. In the late ‘90s, large web companies emerged with dramatic increases in scale on many dimensions: · The number of concurrent users skyrocketed as applications increasingly became accessible · via the web (and later on mobile devices). · The amount of data collected and processed soared as it became easier and increasingly · valuable to capture all kinds of data. · The amount of unstructured or semi-structured data exploded and its use became integral · to the value and richness of applications. Dealing with these issues was more and more difficult using relational database technology. The key reason is that relational databases are essentially architected to run a single machine and use a rigid, schema-based approach to modeling data. Google, Amazon, Facebook, and LinkedIn were among the first companies to discover the serious limitations of relational database technology for supporting these new application requirements. Commercial alternatives didn’t exist, so they invented new data management approaches themselves. Their pioneering work generated tremendous interest because a growing number of companies faced similar problems. Open source NoSQL database projects formed to leverage the work of the pioneers, and commercial companies associated with these projects soon followed. Today, the use of NoSQL technology is rising rapidly among Internet companies and the enterprise. It’s increasingly considered a viable alternative to relational databases, especially as more organizations recognize that operating at scale is more effectively achieved running on clusters of standard, commodity servers, and a schema-less data model is often a better approach for handling the variety and type of data most often captured and processed today.
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database, nosql, data, data management, white paper, why nosql, couchbase
    
Couchbase
Published By: ASG     Published Date: Apr 02, 2014
This Case Study focuses on a highly successful data lineage project between ASG Software Solutions and a major global financial institution. The initial project which began in 2011 with the primary goal of achieving greater control, awareness, and ownership over the institution’s data assets due to new regulatory and federal audit controls. As the project progressed and the positive relationship between ASG and the Bank deepened, all stakeholders involved began to see much broader potential for the entire project than originally envisioned.
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metadata, data, data management, white paper, case study
    
ASG
Published By: ASG     Published Date: May 08, 2017
One Chief Data Officer’s Story of Creating a Data-Centric Organization: ASG Enterprise Data Intelligence and American Fidelity Assurance
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ASG
Published By: Splice Machine     Published Date: Nov 16, 2014
Organizations are now looking for ways to handle exploding data volumes while reducing costs and maintaining performance. Managing large volumes and achieving high levels of concurrency on traditional scale up databases, such as Oracle, often means purchasing expensive scale-up hardware. In this white paper, learn about the different options and benefits of scale out solutions for Oracle database users.
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splice machine, oracle, oracle database, database, hadoop, nosql, white paper, data, data management, dataversity
    
Splice Machine
Published By: CMMI Institute     Published Date: Sep 03, 2014
To drive strategic insights that lead to competitive advantage, businesses must make the best and smartest use of today’s vast amount of data. To accomplish this, organizations need to apply a collaborative approach to optimizing their data assets. For organizations that seek to evaluate and improve their data management practices, CMMI® Institute has developed the Data Management Maturity (DMM)? model to bridge the perspective gap between business and IT. Download the white paper Why is Measurement of Data Management Maturity Important? to enable you to: - Empower your executives to make better and faster decisions using a strategic view of their data. - Achieve the elusive alignment and agreement between the business and IT - Create a clear path to increasing capabilities
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white paper, enterprise data management, data model, data modeling, data maturity model, cmmi institute
    
CMMI Institute
Published By: Melissa Data     Published Date: Oct 27, 2014
Noted SQL Server MVP and founder/editor of SSWUG.org, Stephen Wynkoop shares his take on the challenge to achieve quality data and the importance of the “Golden Record” to an effective data quality regiment. Wynkoop explores the different approaches to achieving the Golden Record - which involves collapsing duplicate records into a single version of the truth – the one single customer view (SCV), and Melissa Data’s unique approach that takes into consideration the actual quality of the contact data as the basis of survivorship.
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data, data management, melissa data, data quality
    
Melissa Data
Published By: Skytree     Published Date: Nov 23, 2014
Critical business information is often in the form of unstructured and semi-structured data that can be hard or impossible to interpret with legacy systems. In this brief, discover how you can use machine learning to analyze both unstructured text data and semi- structured log data, providing you with the insights needed to achieve your business goals.
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log data, machine learning, natural language, nlp, natural language processing, skytree, unstructured data, semi-structured data, data analysis
    
Skytree
Published By: Neo Technology     Published Date: Jun 28, 2015
The future of Master Data Management is deriving value from data relationships which reveal more data stories that become more and more important to competitive advantage as we enter into the future of data and business analytics. MDM will be about supplying consistent, meaningful views of master data and being able to unify data into one location, especially to optimize for query performance and data fit. Graph databases offer exactly that type of data/performance fit. Use data relationships to unlock real business value in MDM: - Graphs can easily model both hierarchical and non-hierarchical master data - The logical model IS the physical model making it easier for business users to visualize data relationships - Deliver insights in real-time from data relationships in your master data - Stay ahead of the business with faster development Download and read the white paper Your Master Data Is a Graph: Are You Ready? to learn why your master data is a graph and how graph databases like Neo4j are the best technologies for MDM.
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database, nosql, graph database, big data, master data management, mdm
    
Neo Technology
Published By: Trillium Software     Published Date: Apr 10, 2017
For the 11th consecutive year, the Gartner Magic Quadrant for Data Quality Tools1 research report positions Trillium Software as a leader in the Data Quality Software industry. Data Quality is vital to ensuring trust in your data-driven, decision making business processes. Confidence is the result of a well thought out and executed data quality management strategy and is critical to remaining competitive in a rapidly and ever-changing business world. The 2016 Gartner Magic Quadrant for Data Quality Tools report is a valuable reference, providing the latest insights into the strengths and cautions of leading vendors. Access the report to learn how a leading data quality solution can help you achieve your long-term strategic objectives.
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Trillium Software
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: 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: BackOffice     Published Date: Apr 22, 2018
The success of a business is increasingly influenced by how effectively it utilizes data within strategic decision making & operations. But when a business views its critical data simply as a byproduct of business processes, and doesn’t value it as a business asset, it increases the risk of not being able to achieve its desired outcomes.
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BackOffice
Published By: IO-Tahoe     Published Date: May 14, 2018
The “silver lining” in GDPR compliance efforts is a creation of transparency and trust with customers, many of whom have layers of concern and trepidation over how all companies they do business with are handling their data. GDPR compliance efforts offer a chance to clear this air, between organizations and their customers, in a way that’s beneficial to both sides. In Io-Tahoe’s eBook, we explore the obligatory components of GDPR compliance, and the mindset most appropriate to achieving it. We also investigate opportunistic facets of establishing comprehensive protection policy around personal or sensitive data. We look at the prospect of GDPR compliance through the exploration of several “mandates”. Download the e-book to find out more on the eight mandates and the dividends beyond.
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IO-Tahoe
Published By: Experian     Published Date: Nov 03, 2015
It is critically important for businesses today to leverage data as a strategic asset, instead of allowing it to become an obstacle. As more and more organizations are trying to make smarter, data-driven decisions, they are discovering that their data management strategy may not be as mature as it needs to be. One major shift we are seeing is the implementation of a Chief Data Officer. Experian Data Quality recently conducted a research study of more than 250 Chief Information Officers (CIOs) and Chief Data Officers (CDOs) in the US about their data management practices, and the explosion of the CDO role. Key insights in the report include: - Tips for overcoming typical data challenges within your organization - The changing data management landscape and its affect on the CIO - The new and growing need for the CDO - And more!
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Experian
Published By: birst     Published Date: Jan 21, 2013
This Dive Deep analyst report looks at the process of building an environment for what can be aptly termed Agile Business Analytics.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
birst
Published By: birst     Published Date: Feb 22, 2013
The demand for business intelligence is strong and growing. For the past several years, BI has been repeatedly named as the top priority by Chief Information Officers (CIO) in Gartner’s annual CIO survey.
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white paper, dataversity, birst, business intelligence, cloud, cloud computing, analytics, data, data management
    
birst
Published By: Data Blueprint     Published Date: Jul 15, 2013
The role of the chief data officer (CDO) is relatively new across the organizational landscape – 70% of current CDO positions were created in the last year alone! The past decade has seen a combination of events, forcing organizations to consider this increasingly important role.
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Data Blueprint
Published By: Semarchy     Published Date: Aug 18, 2016
David Loshin reexamines the way we ingest, manage, consume, and transform data into actionable information and intelligence. Read how this industry expert makes the case for data governance with an unconventional business-first focus. The conventional wisdom on data governance proposes hierarchies, operating models, and processes for data policy definition and implementation. Unfortunately, poorly-designed and minimally-planned data governance processes are ineffective because they are bureaucratic and overwhelming. This is especially true when processes are imposed by fiat, take a long time, and don't result in any short-term improvement in information value. But proper data governance is a critical success factor for master data management! In this paper, we examine the motivations for coupling data governance with master data management and consider how to evolve data policies and processes to position master data management for success.
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Semarchy
Published By: SAP     Published Date: Jul 23, 2018
New market forces are creating unprecedented pressure for companies to move faster, with greater agility, and change in response to new threats and opportunities. Companies that are embracing a new approach built on Intelligent Cloud ERP are gaining valuable advantages — such as boosting profits, growing faster, entering new markets, and disrupting their industries. Learn how Intelligent Cloud ERP empowers you to leverage the opportunities presented by changes to how we work, collaborate and achieve success in this practical, actionable overview.
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SAP
Published By: SAP     Published Date: Jul 23, 2018
Leading companies are making digital transformation a reality put data and intelligence at the center of their future. They are building new capabilities, skills, and technology, and evolving their culture to transform into an ‘Intelligent Enterprise’ and achieve the aforementioned outcomes. These companies are not only delivering short-term value to shareholders, but are also positioned to thrive and transform their industry. Explore how SAP can help you navigate the journey to the Intelligent Enterprise.
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SAP
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