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data governance

Results 126 - 150 of 196Sort Results By: Published Date | Title | Company Name
By: Oracle     Published Date: Apr 22, 2014
This document focuses on the trends that are driving decision-making on cloud including the growing connection between cloud, mobility, and data; cloud services governance and integration; and continuing development of cloud ecosystems among vendors.
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cloud services, trends, cloud services, oracle, customer interaction service, customer relationship management, customer satisfaction, customer service
    
Oracle
By: Collibra     Published Date: May 24, 2018
This report, developed by The Economist Intelligence Unit and sponsored by Collibra, draws on a survey of more than 500 business executives.
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collibra, data governance, governance, data, intelligence, trends, business activity monitoring, business intelligence
    
Collibra
By: SAP     Published Date: Mar 24, 2011
The list of initiatives that are data-enabled-indeed, data-intensive-vary from company to company, from industry to industry. But the common denominator is an increasing awareness that these and other programs can't succeed without clean, meaningful, and available information. In this white paper, Baseline Consulting's Jill Dyché discusses how the data conversation is changing from philosophical questioning to hard-core tactics, from "What do we need?" to "Where do we start?" It covers the most common reasons for data governance failure, as well as the components of data governance that will inform the right strategy and give companies a means of determining where and how to begin their data governance journeys.
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data governance, data governance failure, data governance initiative, governance, business intelligence, database development, data integration, data mining
    
SAP
By: Group M_IBM Q1'18     Published Date: Dec 20, 2017
Despite the business-transforming upsides of data from the Internet of things (IoT), there’s a downside: security. Porous networks and lax users offer tantalizing access for hackers. Although most security spending is at the enterprise level, a shift is needed to secure IoT applications and provide improved governance and accountability. Electronics companies must create secure environments that safely collect, consume, share and store data on their networks. But they also must go beyond devices and consumers to close holes to factory, ecosystem and partner networks.
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planet scale security, iot, security, iot application, application security, partner networks
    
Group M_IBM Q1'18
By: SAS     Published Date: Jun 06, 2018
Written by Jill Dyche and Kimbery Nevala, 10 Mistakes to Avoid When Launching your Data Governance Program lays out a comprehensive list of issues that can trip up an organization as it gets started with DG. Learn how to use good judgment and sound decision making to sidestep these common issues.
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SAS
By: SAS     Published Date: Mar 14, 2014
Judgment is a process and not a single event. Good judgment and sound decision making are at the heart of data governance.
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sas, data governance, data management, data measurement, governance policy, payback, tactical, structured
    
SAS
By: SAS     Published Date: Mar 14, 2014
This Q&A with Tom Davenport, Director of Research for the International Institute for Analytics (IIA), will help you understand how analytics is evolving, where you need to go, and how to get there.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives
    
SAS
By: SAS     Published Date: Mar 14, 2014
This paper explores the challenges organizations have today in implementing a data governance program via an actual business case. It highlights SAS technology that can help you solve many of those challenges.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives
    
SAS
By: SAS     Published Date: Mar 14, 2014
This report examines how data visualization can help organizations unleash the full value of information, and outlines key considerations to guide the solution evaluation process.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives
    
SAS
By: SAS     Published Date: Mar 14, 2014
Managing expectations before, during and after the adoption of visualization software is crucial. Users should know what the rollout process will look like and how it will take place, and have clear goals for using the tool. Make sure that the desired outcome isn’t just look-and-feel. Creating beautiful charts and graphs is not a substitute for practical business decisions.
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sas, data categorization, retrieval and quality, data visualization, data governance program, data management, data quality, business objectives
    
SAS
By: SAS     Published Date: Mar 14, 2014
This paper explores ways to qualify data control and measures to support the governance program. It will examine how data management practitioners can define metrics that are relevant.
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sas, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics
    
SAS
By: SAS     Published Date: Mar 14, 2014
Jill Dyche and SpectraDynamo explains the importance of understanding how to manage data and issues regarding data categorization, retrieval and quality.
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sas, data categorization, retrieval and quality, spectradynamo, telemetry data, data governance program, data management, data quality
    
SAS
By: Qualys     Published Date: Nov 16, 2012
This whitepaper discusses the challenges of security in the cloud and how the use of cloud-based services will enable organizations of all sizes, from the very smalles to multinational enterpries, to put trust back into the security equation.
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cloud based services, security, it security, data breach, ssl, ssl governance
    
Qualys
By: K2     Published Date: Jan 07, 2016
We’re experiencing a data explosion. By 2020 the data we create and copy annually will reach 44 trillion gigabytes.1 As this data disseminates into the workplace, companies add hardware and software systems to store, protect and manage it all. While data can help solve business problems, data is most helpful when it reaches those who can use it. Companies need to build Microsoft SharePoint apps that integrate with other line-of-business (LOB) systems so users can take full advantage of this data explosion. But the reality of creating apps that integrate data across organizational systems presents an intimidating challenge. To integrate multiple isolated data sources into an application that transforms data into useful information requires technical expertise, coding and ongoing maintenance. Integration also raises security and governance concerns. So it’s no surprise that only 47 percent of SharePoint users have connected their SharePoint apps with other systems.2 As a result, nearly
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microsoft sharepoint, data integration, security, sharepoint solutions, networking, it management, knowledge management
    
K2
By: K2     Published Date: Jan 07, 2016
The cloud is here to stay, and Microsoft SharePoint users are finally making the move. Since 2013, the number of SharePoint users with intentions of moving their SharePoint sites to the cloud has doubled, according to a 2015 AIIM survey.1 Many users are making the change to reduce IT costs, improve access for external partners and increase mobility. Casey, IT manager at a mid-size healthcare organization, is one of those users planning to move his organization to a cloud-based SharePoint infrastructure. But because Casey works in healthcare, he’s especially concerned about the security of the cloud. And he’s not alone with that concern — AIIM reports that 62 percent of SharePoint users cite security as their biggest concern when considering a cloud or hybrid solution for SharePoint. More specifically, many SharePoint users are concerned about the following three areas of security in the cloud: • Identity and access • Data protection and privacy • Compliance and governance
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security confidence, cloud, microsoft sharepoint, cloud solution, hybrid solution, security, it management, wireless
    
K2
By: Tripwire     Published Date: Jun 30, 2009
Since the adoption of SOX, much has been learned about IT compliance. Discover how to make SOX efforts more effective in "Sustaining Sox Compliance."
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tripwire, sustain, sox, compliance, practice, risk, control, data
    
Tripwire
By: IBM     Published Date: May 28, 2014
Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.
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ibm, data retention, information governance, archiving, historical data, integrating big data, governing big data, integration
    
IBM
By: IBM     Published Date: May 12, 2015
Watch this video whitepaper to learn about data economics, information governance, and specific IBM solutions for governing the information lifecycle.
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ibm, governance, best practices, document management, information management, data center design and management
    
IBM
By: IBM     Published Date: Aug 05, 2014
There is a lot of discussion in the press about Big Data. Big Data is traditionally defined in terms of the three V’s of Volume, Velocity, and Variety. In other words, Big Data is often characterized as high-volume, streaming, and including semi-structured and unstructured formats. Healthcare organizations have produced enormous volumes of unstructured data, such as the notes by physicians and nurses in electronic medical records (EMRs). In addition, healthcare organizations produce streaming data, such as from patient monitoring devices. Now, thanks to emerging technologies such as Hadoop and streams, healthcare organizations are in a position to harness this Big Data to reduce costs and improve patient outcomes. However, this Big Data has profound implications from an Information Governance perspective. In this white paper, we discuss Big Data Governance from the standpoint of three case studies.
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ibm, data, big data, information, healthcare, governance, technology, it management
    
IBM
By: IBM     Published Date: Aug 28, 2014
Data volumes are getting out of control, but choosing the right information lifecycle governance solution can be a huge challenge, with multiple stakeholders, numerous business processes, and extensive solution requirements. Use this requirements kit from the Compliance, Governance and Oversight Council (CGOC) to find the tools and technology you need.
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ilg, data volumes, cgoc, information economics, it management, business intelligence, configuration management, service oriented architecture
    
IBM
By: IBM     Published Date: Aug 28, 2014
Not storing data is cheaper than storing it. As enterprise data continues to grow and IT budgets remain flat, organizations need to more effectively maximize existing storage capacity and manage storage spend based on data value. In this white paper, Enterprise Strategy Group Sr. Analyst Mark Peters demonstrates how IBM's Information Lifecycle Governance solutions can help IT buyers improve the information economics for their organizations by curtailing data growth through defensible disposal of data.
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data storage, data value, ilg, data disposal, data management, storage management
    
IBM
By: IBM     Published Date: Oct 01, 2014
This white paper discusses how IBM InfoSphere can support the integration and governance of Big Data in healthcare. The white paper reviews three case studies including predictive analytics with Electronic Medical Records, time series data in a neonatal intensive care unit and predictive pathways for disease.
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big data, data integration, healthcare, data management, business activity monitoring, business analytics
    
IBM
By: IBM     Published Date: Oct 22, 2014
Not storing data is cheaper than storing it. As enterprise data continues to grow and IT budgets remain flat, organizations need to more effectively maximize existing storage capacity and manage storage spend based on data value. In this white paper, Enterprise Strategy Group Sr. Analyst Mark Peters demonstrates how IBM's Information Lifecycle Governance solutions can help IT buyers improve the information economics for their organizations by curtailing data growth through defensible disposal of data.
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data storage, big data, data disposal, data value, it management, data management, business intelligence, content management system
    
IBM
By: IBM     Published Date: Feb 24, 2015
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.
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big data, ibm, big data outcomes, information governance, big data analytics, it management, data management
    
IBM
By: IBM     Published Date: Jul 14, 2015
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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big data, data warehouse, data center, information governance, analytics, big data analytics, business management, data management
    
IBM
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