processes

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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: First San Francisco Partners     Published Date: Sep 03, 2014
This white paper discusses how awareness, ownership and accountability are key to activating and engaging people to adopt new data governance initiatives and the related policies and processes. It provides you with information on how your organization can ensure that the data stewards adopt the new data governance policies and processes.
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data, data management, data governance, data governance program
    
First San Francisco Partners
Published By: First San Francisco Partners     Published Date: Mar 03, 2017
Getting people successfully through a new enterprise information management (EIM) initiative requires a focus on the change’s impact to your organization’s data culture, processes and policies.
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First San Francisco Partners
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: MarkLogic     Published Date: Aug 04, 2014
The Age of Information and the associated growth of the World Wide Web has brought with it a new problem: how to actually make sense of all the information available. The overarching goal of the Semantic Web is to change that. Semantic Web technologies accomplish this goal by providing a universal framework to describe and link data so that it can be better understood and searched holistically, allowing both people and computers to see and discover relationships in the data. Today, organizations are leveraging the power of the Semantic Web to aggregate and link disparate data, improve search navigation, provide holistic search and discovery, dynamically publish content, and complete ETL processes faster. Read this white paper to gain insight into why Semantics is important, understand how Semantics works, and see examples of Semantics in practice.
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data, data management, whitepaper, marklogic, semantic, semantic technology, nosql, database, semantic web, big data
    
MarkLogic
Published By: CA Technologies     Published Date: Feb 25, 2016
As combinations of both internal and externally-imposed business policies imply dependencies on managed data artifacts, organizations are increasingly instituting data governance programs to implement processes for ensuring compliance with business expectations. One fundamental aspect of data governance involves practical application of business rules to data assets based on data elements and their assigned values. Yet despite the intent of harmonizing data element definitions and resolution of data semantics and valid reference values, most organizations rarely have complete visibility into the metadata associated with enterprise data assets.
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CA Technologies
Published By: Paxata     Published Date: Apr 02, 2014
Why Sift Through Data Landfills? Better business insight comes from data - but data is often dirty, incomplete and complicated. As any analyst would admit, what passes for data science is more like janitorial work. Find out why that is - and how you can avoid the painful, manual and error-prone processes that have bogged down the analytics process for 30 years.
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data, data management, big data, white paper, paxata, analytics
    
Paxata
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: 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: Silwood Technology     Published Date: Mar 02, 2016
Ever since organisations started to implement packaged software solutions to solve business problems and streamline their processes there has been a need to access their data for the purposes of reporting and analytics, integration, governance, master data and more. Information Management projects such as these rely on data professionals being able to understand the underlying data models for these packages in order to be able to answer the critical question “Where’s the data?”. Without this knowledge it is impossible to ensure accuracy of data or timely delivery of projects. In addition the lack of discovery tools designed to meet this challenge has meant that performing this task has commonly been frustrating, time-consuming and fraught with risk. This white paper offers insight into why the traditional methods are not effective and how an innovative software product from Silwood Technology provides a faster and more effective approach to solving the problem.
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Silwood Technology
Published By: Alteryx     Published Date: May 24, 2017
Spreadsheets are a mainstay in almost every organization. They are a great way to calculate and manipulate numeric data to make decisions. Unfortunately, as organizations grow, so does the data, and relying on spreadsheet-based tools like Excel for heavy data preparation, blending and analysis can be cumbersome and unreliable. Alteryx, Inc. is a leader in self-service data analytics and provides analysts with the ability to easily prep, blend, and analyze all data using a repeatable workflow, then deploy and share analytics at scale for deeper insights in hours, not weeks. This paper highlights how transitioning from a spreadsheet-based environment to an Alteryx workflow approach can help analyst better understand their data, improve consistency, and operationalize analytics through a flexible deployment and consumption environment.
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Alteryx
Published By: Syncsort     Published Date: Jan 04, 2018
The term Big Data doesn’t seem quite “big enough” anymore to properly describe the vast over-abundance of data available to organizations today. As the volume and variety of Big Data sources continue to grow, the level of trust in that data remains troublingly low. Read on and discover how a strong focus on data quality spanning the people, processes and technology of your organization will help keep your data lake pristine.
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Syncsort
Published By: Octopai     Published Date: Sep 01, 2018
For many BI professionals, every task can feel like MISSION IMPOSSIBLE. All the manual mapping required to sort out inconsistencies in data and the lack of tools to simplify and shorten the process of finding and understanding data leaves BI groups frustrated and slows down the business. This whitepaper examines the revolutionary impact of automation on the cumbersome manual processes that have been dragging BI down for so long. • Data correction vs process correction • Root-cause analysis with data lineage: reverse-tracing the data flow • Data quality rules and data controls • Automated data lineage mapping
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Octopai
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: Deloitte Process Robotics     Published Date: May 04, 2018
Deloitte Process Robotics (DPR) solutions use a lightweight approach to train ‘bots’ that automate repetitive tasks of medium complexity without changes to existing process or IT infrastructure. With ever-growing repositories of unanalyzed and underutilized data, organizations require highly flexible and scalable enterprise data management (EDM) processes, DPR makes it possible for organizations to adopt comprehensive yet affordable EDM processes in the Big Data Era, helping organizations transform data into strategic assets through the automation of capabilities.
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Deloitte Process Robotics
Published By: First San Francisco Partners     Published Date: May 19, 2014
Master data management (MDM) is about people and process; it is not about technology. Implementing MDM technology alone will not address operational and business process challenges. Rather, “mastering” data involves people taking action through established data policies and processes. Data Governance ensures that data in the MDM hub is of high quality and can be trusted by business users. Lacking Data Governance, organizations do not have consistent data definitions or know what constitutes a data problem, who is accountable, what decisions need to be made, or how to escalate and resolve issues.
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white paper, master data management, first san francisco partners, kelle o'neal, dataversity, data governance, mdm, master data management white paper, data governance white paper
    
First San Francisco Partners
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.
Tags : 
research paper, data, data management, data governance, data steward
    
DATAVERSITY
Published By: Ted Hills     Published Date: Mar 29, 2016
NoSQL database management systems give us the opportunity to store our data according to more than one data storage model, but our entity-relationship data modeling notations are stuck in SQL land. Is there any need to model schema-less databases, and is it even possible? In this short white paper, Ted Hills examines these questions in light of a recent paper from MarkLogic on the hybrid data model. Ted Hills has been active in the Information Technology industry since 1975. At LexisNexis, Ted co-leads the work of establishing enterprise data architecture standards and governance processes, working with data models and business and data definitions for both structured and unstructured data. His book, NoSQL and SQL Data Modeling, was recently released by Technics Publications (http://technicspub.com).
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Ted Hills
Published By: TIBCO Software GmbH     Published Date: Jan 15, 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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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Whether you know it as Industry 4.0, the 4th Industrial Revolution, or Smart Industry, Manufacturing is going through a deep transformation, with changes that are centered around digitalization. While most industries are already on this digitalization path, the disruption is more visible and pronounced in manufacturing because it is expanding virtual data and processes into environments that have been fundamentally about physical products. This transformation has already started, and its impact is expected to be massive. Technical, economic, and social changes are expected across the whole manufacturing ecosystem, with jobs shifting from offshoring back to nearshoring. Strong technology elements driving this digital revolution include 3D printing, robotizing and automation, smart factory with IoT and machine learning, and supply chain digitization. Their impact is profound.
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TIBCO Software GmbH
Published By: TIBCO Software GmbH     Published Date: Jan 22, 2019
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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TIBCO Software GmbH
Published By: Sage     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
Published By: Sage     Published Date: Jan 04, 2019
The General Data Protection Regulation (GDPR) is the new legal framework that will come into effect on the 25th of May 2018 in the European Union. EU regulations have direct effect in all EU member states, meaning the GDPR replaces the current Data Protection Directive and applies to all EU member states. The GDPR’s focus is the protection of personal data. In fact, GDPR is one of the biggest shakeups ever seen affecting how data relating to an individual should be handled—and it affects not just companies but any individual, corporation, public authority, agency or other body that processes the personal data of individuals based in the EU. As gatekeepers and processors of personal data, HR and People teams have a crucial role to play in preparing for this step change. The rules on how data is kept and used will become much more stringent, and it’s vital that HR and People teams become more transparent, communicating to employees exactly how their data is processed. In a world wh
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Sage
Published By: Rubrik EMEA     Published Date: Jan 04, 2019
Rubrik Cloud Data Management is a single, unified software platform to manage your physical, virtual, and cloud data. With Rubrik, enterprises can drastically simplify their data protection processes, automate workflows, and migrate data to the cloud. The results are powerful: faster recoveries, easier management, no forklift upgrades, and hard dollars saved for other projects. Organizations pursuing cloudfirst policies can use Rubrik to archive to the cloud, create cloud DR capabilities, or perform cloud-native backup. And with Rubrik’s Polaris SaaS platform, it has never been easier to unify data across data centers and clouds, simplifying operations and governance. DATA
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Rubrik EMEA
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