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Published By: Syncsort     Published Date: Feb 21, 2019
With data lakes offering the means to capture, store and utilize a broad array of internal, third party and external data from a variety of sources, organizations of all types are ready to gain greater and better insights. While this promise of Big Data and improved visibility is substantial, data is pretty much useless if it can’t be trusted. The only way to be certain that your data governance policies are consistently followed and enforced is to ensure data quality across your IT systems. Download this white paper with Information Management, Discover the Value of Data Quality for Data Governance Success, to learn more about empowering your data governance program with quality data.
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Syncsort
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: DATAVERSITY     Published Date: Nov 20, 2015
The competitive advantages realized from a dependable Business Intelligence and Analytics (BI/A) are well documented. Everything from reduced business costs and increased customer retention to better decision making and the ability to forecast opportunities have been observed outcomes in response to such programs. The implementation of such a program remains a necessity for any growing or mature enterprise. The establishment of a comprehensive BI/A program that includes traditional Descriptive Analytics along with next generation categories such as Predictive or Prescriptive Analytics is indispensable for business success.
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data, data management, analytics, business intelligence, data science
    
DATAVERSITY
Published By: Innovative Systems     Published Date: Feb 21, 2019
From years of data quality initiatives, hundreds of case studies, and research by industry experts, a number of common data quality success factors have emerged. This paper discusses key characteristics of data quality initiatives and provides actionable guidelines to help make your project a success, from conception through implementation and tracking your ROI. Readers will learn how to: • Quantify the effect of poor data quality on the organization • Prioritize projects for faster ROI • Gain buy-in, from employees through senior management
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Innovative Systems
Published By: DATAVERSITY     Published Date: Jun 14, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate, if needed) the strategic and tactical business drivers every enterprise needs for market success. This paper is sponsored by: ASG, DGPO and DebTech International.
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data, data management, data governance, data steward, dataversity, research paper
    
DATAVERSITY
Published By: Stardog Union     Published Date: Jul 27, 2018
When enterprises consider the benefits of data analysis, what's often overlooked is the challenge of data variety, and that most successful outcomes are driven by it. Yet businesses are still struggling with how to query distributed, heterogeneous data using a unified data model. Fortunately, Knowledge Graphs provide a schema flexible solution based on modular, extensible data models that evolve over time to create a truly unified solution. How is this possible? Download and discover: • Why businesses should organize information using nodes and edges instead of rows, columns and tables • Why schema free and schema rigid solutions eventually prove to be impractical • The three categories of data diversity including semantic and structural variety
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Stardog Union
Published By: Adaptive     Published Date: May 10, 2017
Enterprise metadata management and data quality management are two important pillars of successful enterprise data management for any organization. A well implemented enterprise metadata management platform can enable a successful data quality management at the enterprise level. This paper describes in detail an approach to integrate data quality and metadata management leveraging the Adaptive Metadata Manager platform. It explains the various levels of integrations and the benefits associated with each.
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Adaptive
Published By: Embarcadero     Published Date: Jan 23, 2015
There are multiple considerations for collaborating on metadata within an organization, and you need a good metadata strategy to define and manage the right processes for a successful implementation. In this white paper, David Loshin describes how to enhance enterprise knowledge sharing by using collaborative metadata for structure, content, and semantics.
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data, data management, metadata, enterprise information management, data modeling, embarcadero
    
Embarcadero
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: AnalytixDS     Published Date: Feb 28, 2015
With future business intelligence solutions clearly evolving from data that comes from highly efficient and well behaved systems, to data that comes from the extended enterprise where data is not necessarily so well structured and behaved - Organizations are forced into a more collaborative mode of operation with their core infrastructure being adapted from the consumer space, and to the extent possible, conformed to their existing repositories. This whitepaper attempts to address various challenges consumers face while managing enormous data sets within the context of this complex scenario. Further, we’ll try to answer the question: Is Big Data Governance really that different from traditional data governance initiatives? Finally, we’ll see how AnalytiX™ Mapping Manager™ can help organizations accelerate the development and deployment of a successful Big Data/ Business Intelligence platform and accelerate delivery of all sorts of data – structured, semi-structured as well as unstruc
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big data, big data governance, data governance, analytixds
    
AnalytixDS
Published By: Trillium Software     Published Date: Mar 29, 2016
We are living in a new age in which your business success depends on access to trusted data across more systems and more users faster than ever before. However, your business information is often incomplete, filled with errors, and beyond the reach of people who need it. Whether you’re responsible for technology or information strategy, you need to enable your business to have real-time access to reliable information. Otherwise, your company will be left behind. Download Trillium’s whitepaper, “How to Succeed in the New Age of Data Quality”, to learn how you can create a successful data quality strategy.
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Trillium Software
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: T4G     Published Date: Mar 15, 2017
About to embark on an advanced analytics project? Or have already started and things aren’t going as planned? This white paper will share our approach to ensure you set up for success. We will discuss aspects of data strategy and data stewardship, and why they are so important. We will outline the benefits of having a solid data strategy and how to start the data strategy conversation within your organization. We will then outline how a project’s entry point (the initial impetus for the project) impacts the scope and approach for the project. And will show you how to avoid missteps and gaps that can lead to less than stellar results or wasted effort. The white paper will touch on the importance of understanding your business drivers and how to use them as your guide to get the most out of your data driven decision making projects. Our proven approach will help ensure a successful start on your advanced analytics journey.
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T4G
Published By: Infogix     Published Date: May 04, 2018
Over the last few years, the term “data governance” has evolved to more prominence, concurrently with big data. While organizations understand the need for governance around big data, the implementation of a successful data governance solution continues to remain elusive as organizations grapple with what exactly data governance is. This whitepaper provides a concise definition of data governance and offers some key considerations for a successful data governance solution.
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Infogix
Published By: Syncsort     Published Date: Jul 17, 2018
In most applications we use today, data is retrieved by the source code of the application and is then used to make decisions. The application is ultimately affected by the data, but source code determines how the application performs, how it does its work and how the data is used. Today, in a world of AI and machine learning, data has a new role – becoming essentially the source code for machine-driven insight. With AI and machine learning, the data is the core of what fuels the algorithm and drives results. Without a significant quantity of good quality data related to the problem, it’s impossible to create a useful model. Download this Whitepaper to learn why the process of identifying biases present in the data is an essential step towards debugging the data that underlies machine learning predictions and improves data quality.
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Syncsort
Published By: Syncsort     Published Date: Oct 25, 2018
In most applications we use today, data is retrieved by the source code of the application and is then used to make decisions. The application is ultimately affected by the data, but source code determines how the application performs, how it does its work and how the data is used. Today, in a world of AI and machine learning, data has a new role – becoming essentially the source code for machine-driven insight. With AI and machine learning, the data is the core of what fuels the algorithm and drives results. Without a significant quantity of good quality data related to the problem, it’s impossible to create a useful model. Download this Whitepaper to learn why the process of identifying biases present in the data is an essential step towards debugging the data that underlies machine learning predictions and improves data quality.
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Syncsort
Published By: birst     Published Date: Jan 21, 2013
This white paper discusses why Big Data matters – and analyses a tiered approach and strategy to launch a successful Big Data initiative.
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big data, white paper, analytics, data management
    
birst
Published By: Embarcadero     Published Date: Apr 02, 2014
IT professionals in organizations developing an enterprise data modeling program may feel overwhelmed at the scope and complexity of initiating new methods, tools, and techniques. Whether their organization is just starting out or experienced in enterprise data modeling efforts, there are certain pitfalls that can become obstacles to success. This paper looks at the benefits of an effective enterprise data modeling effort and discusses seven common mistakes that organizations can make in developing enterprise data models.
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Embarcadero
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: DATAVERSITY     Published Date: Jun 17, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate,if needed) the strategic and tactical business drivers every enterprise needs for market success.
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research paper, data, data management, data governance, data steward
    
DATAVERSITY
Published By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
Published By: TIBCO Software     Published Date: Mar 15, 2019
On-demand Webinar 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 the need to rework faulty products. Watch this webinar to learn how TIBCO’s Smart Manufacturing solutions can help you overcome these challenges. You will also see a demonstration of TIBCO technology in action around improving yield and optimizing processes while also saving costs. What You Will Learn: Applying advanced analytics & machine learning / AI techniques to optimize complex manufacturing processes How multi-variate statistical process control can help to detect deviations from a baseline How to monitor in real time the OEE and produce a 360 view of your factory The webinar also highlights customer case studies from our clients who have already successfully implemented process optimization models. Speakers:
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TIBCO Software
Published By: IBM APAC     Published Date: Mar 06, 2019
A multicloud world is quickly becoming the new normal for many enterprises. Learn how the multicloud world is changing the face of IT. Understanding cloud environments and making decisions about multicloud management can be complex. IBM has identified ten key pain points and related best practices that help organizations successfully navigate these transformations.
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IBM APAC
Published By: Red Hat     Published Date: Feb 25, 2019
Business-critical applications need a platform that is proven to be stable. Red Hat®Enterprise Linux® frees you to deliver meaningful business results through technology by providing exceptional reliability and military-grade security. With a Red Hat Enterprise Linux Server subscription, you gain access to the industry's most extensive ecosystem of partners, customers, and experts that supports and accelerates your success. Read the datasheet to learn more.
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Red Hat
Published By: Larsen & Toubro Infotech(LTI)     Published Date: Mar 20, 2019
How can your organization extract maximum value from Artificial Intelligence? In order to embed AI into your ERP processes, there are a number of parallel initiatives to consider. Our whitepaper explores those in detail, giving you an early roadmap for success. Download Complete Whitepaper.
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Larsen & Toubro Infotech(LTI)
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