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lifecycle data management

Results 1 - 25 of 26Sort Results By: Published Date | Title | Company Name
Published By: Delphix     Published Date: May 03, 2016
Today's test data management (TDM) solutions force teams to work with compromised data sets, and push testing to too late in the software development lifecycle. The end result is rework, delayed releases, and costly bugs that cripple production systems. Furthermore, prevailing approaches to test data management - including subsetting, synthetic data, shared environments, and standalone masking--represent flawed solutions that fail across one or more key dimensions.
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Delphix
Published By: Adobe     Published Date: Apr 25, 2016
In this paper we look at the old model of managing apps and then see if there’s a better way.
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mobile apps, mobile lifecycle, data management
    
Adobe
Published By: Adobe     Published Date: Apr 25, 2016
In this paper we look at the old model of managing apps and then see if there’s a better way.
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mobile apps, mobile lifecycle, data management
    
Adobe
Published By: Attunity     Published Date: Feb 12, 2019
How can enterprises overcome the issues that come with traditional data warehousing? Despite the business value that data warehouses can deliver, too often they fall short of expectations. They take too long to deliver, cost too much to build and maintain, and cannot keep pace with changing business requirements. If this all rings a bell, check out Attunity’s knowledge brief on data warehouse automation with Attunity Compose. The solution automates the design, build, and deployment of data warehouses, data marts and data hubs, enabling more agile and responsive operation. The automation reduces time-consuming manual coding, and error-prone repetitive tasks. Read the knowledge brief to learn more about your options.
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dwa, data warehouse automation, etl development, extract transform load tools, etl tools, data warehouse, data marts, data hubs data warehouse lifecycle
    
Attunity
Published By: Dassault Systèmes     Published Date: Jul 21, 2017
Product Lifecycle Management (PLM) software can help your company keep up with the increasing complexity of developing today’s high-tech products. While smaller companies may use relatively simple Product Data Management (PDM) tools, larger companies rely on full-featured PLM systems that help automate processes and share data across global supply chains. Mid-size companies can feel stuck because PDM is too basic, but PLM feels out of reach. This resource will help you: • Recognize why “simple” solutions fall short and do not support your capabilities • Better connect to customers and the supply chain • Drive higher product development speed • Get started with the right PLM solution Midsize manufacturers need a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time. So, what’s the right size PLM to fit a midsized high-tech company? Download this resource and take a look.
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product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed
    
Dassault Systèmes
Published By: Dassault Systèmes     Published Date: Jul 21, 2017
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization. This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions. Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
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product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed
    
Dassault Systèmes
Published By: Dassault Systèmes     Published Date: Jul 21, 2017
Project management relies primarily on past performance to predict future results, however many companies still lack forward-looking capabilities to predict project outcomes and ensure success. Enhancing project management with PLM analytics offers the opportunity to switch from task-based activities to performance-driven ones to improve success rates. Use PLM Analytics to: • Gain actionable insight and valuable intelligence • Dramatically boost business value and improve project management performance • Reduce error-prone behavior like manual data collection • Leverage big-data capabilities and project intelligence Learn how to extend the value of your PLM investment and improve business performance for your company.
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product solutions, lifecycle management, tech products, data management tools, pdm, plm, process automation, product development speed
    
Dassault Systèmes
Published By: IBM     Published Date: Apr 22, 2016
Developing a data integration and lifecycle management strategy for a hybrid environment This e-book focuses on building and executing a data integration and lifecycle management strategy.
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ibm, think data, integration, lifecycle strategy, ibm analytics, knowledge management, enterprise applications, data management
    
IBM
Published By: Dassault Systèmes     Published Date: Aug 08, 2017
Midsize Aerospace and Aviation manufacturers need to choose a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time. Product Lifecycle Management (PLM) software can help. It drives better product development performance by managing product-related data, processes and projects. While smaller companies may be able to control, access and share product data with relatively simple Product Data Management (PDM) tools, larger manufacturers rely on full featured PLM systems that help automate processes and share data across global Aerospace and Aviation companies.
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aerospace, aviation, manufacturing, product development, plm, product lifecycle management, automation, data
    
Dassault Systèmes
Published By: hightail     Published Date: Jan 17, 2014
Learn how the method of data collection and storage has changed and learn the 4 essential stages of managing your content in the digital age.
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enterprise applications, data management, cloud computing, content management, business technology
    
hightail
Published By: DataFlux     Published Date: Jan 07, 2011
This white paper introduces and examines a breakthrough platform solution designed to drive parallel-process data integration - without intensive pre-configuration - and support full-lifecycle data management from discovery to retirement.
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dataflux, enterprise data, data integration, configuration, lifecycle data management, data warehouses
    
DataFlux
Published By: VMware     Published Date: Nov 04, 2016
From private, public, and hybrid clouds to traditional and modern application architectures, today’s modern data center is complex. To effectively manage the evolving topology, IT needs a unified approach to management, with intelligent, cost-effective tools – which is just what an enterprise-ready cloud management platform (CMP) provides. CMP enables IT teams to automate provisioning as well as manage applications throughout their lifecycle with a single platform. Read this eGuide to learn more about how to avoid chaos in the data center with a unified cloud management platform.
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VMware
Published By: IBM     Published Date: May 29, 2008
IBM Multiform Master Data Management manages master data domains - customers, accounts, products - that have significant impact on the most important business processes and realize the promise of Service Oriented Architecture (SOA). IBM is the only vendor that delivers an integrated MDM product with significant out-of-the-box functionality for each MDM usage style - collaborative, operational and analytical - across multiple data domains, thereby managing the complete data lifecycle.
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data management, mdm, data lifecycle, master data management
    
IBM
Published By: LANDesk     Published Date: Apr 06, 2009
Implementing the ITIL set of guidelines to aid the implementation of a lifecycle framework for IT Service Management is now a major priority for a growing number of organizations, but remains a task where external help is often of critical importance.
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itil, avocent, landesk, lifecycle, configuration management database, cmdb, it infrastructure library, kpi
    
LANDesk
Published By: SnapLogic     Published Date: Aug 17, 2015
This whitepaper addresses new elastic iPaaS requirements in detail while highlighting the importance of each.
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elastic ipaas requirements, hybrid deployments, minimal lifecycle management, future-proofing, metadata-driven integration, error management, transactional support, pre-built connectivity
    
SnapLogic
Published By: IBM     Published Date: Feb 18, 2009
This white paper explains how the seven basic principles for managing enterprise application data can help your organization: Establish effective policies for full-lifecycle enterprise data management to control data growth and lower storage costs; Meet service level goals to achieve the timely completion of key business processes for mission-critical applications; Support data retention compliance initiatives and mitigate risk for audits and e-discovery requests; Implement scalable archiving strategies that easily adapt to your ongoing business requirements.
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ibm integrated data management, siebel crm, archiving project, service level goals, data retention compliance, archiving strategies, ibm optim data growth solution, rapid data growth
    
IBM
Published By: IBM     Published Date: Feb 18, 2009
This white paper explains how the seven basic principles for managing enterprise application data can help your organization: Establish effective policies for full-lifecycle enterprise data management to control data growth and lower storage costs; Meet service level goals to achieve the timely completion of key business processes for mission-critical applications; Support data retention compliance initiatives and mitigate risk for audits and e-discovery requests; Implement scalable archiving strategies that easily adapt to your ongoing business requirements.
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ibm integrated data management, oracle e-business suite, business-critical erp applications, archiving project, service level goals, data retention compliance, archiving strategies, ibm optim data growth solution
    
IBM
Published By: IBM     Published Date: Feb 18, 2009
This white paper explains how the seven basic principles for managing enterprise application data can help your organization: Establish effective policies for full-lifecycle enterprise data management to control data growth and lower storage costs; Meet service level goals to achieve the timely completion of key business processes for mission-critical applications; Support data retention compliance initiatives and mitigate risk for audits and e-discovery requests; Implement scalable archiving strategies that easily adapt to your ongoing business requirements.
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ibm integrated data management, jd edwards, business-critical erp applications, archiving project, service level goals, data retention compliance, archiving strategies, ibm optim data growth solution
    
IBM
Published By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
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ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data
    
IBM
Published By: IBM     Published Date: Jun 20, 2014
Data volumes are getting out of control, but choosing the right ILG solution can be a huge challenge, with multiple stakeholders, numerous business processes, and extensive solution requirements. Use this requirements kit from CGOC to find the tools and technology you need.
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ibm, ilg, information lifecycle governance, information management, ilg solutions, data storage, data management, it management
    
IBM
Published By: SPSS     Published Date: Jun 30, 2009
Read how Cabelcom recognized the key to tackling churn and was able to identify the point at which customers become dissatisfied with their service.
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spss, cablecom, customer retention, crm, churn rate, reduce churn, predictive analytics, statistics
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
Read how Cabelcom recognized the key to tackling churn and was able to identify the point at which customers become dissatisfied with their service.
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spss, cablecom, customer retention, crm, churn rate, reduce churn, predictive analytics, statistics
    
SPSS, Inc.
Published By: Cornerstone OnDemand     Published Date: Jun 29, 2018
Unified talent management is a term used for talent management software solutions that handle all pieces of the talent lifecycle in a single platform that shares data across all aspects of an employee’s career. Unified talent management technology solutions can help organizations define and use the same criteria for selection, performance management, and development planning, providing visibility into the entire talent pool.
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management, talent, goverment, workforce
    
Cornerstone OnDemand
Published By: IBM     Published Date: Dec 12, 2006
This white paper addresses the value of a company’s ability to integrate, analyze and optimize all types and sources of information throughout the product life cycle. 
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it spending, product lifecycle management, data integration, data analysis, plm, product information management, data management, mdm
    
IBM
Published By: IBM     Published Date: Dec 30, 2008
Does your business need to safeguard information, keep auditors and regulators satisfied, and improve data quality? Data governance is the answer. This informative video outlines the latest challenges and best practices in data governance. IBM data governance solutions help businesses with:• Audit and reporting • Data architecture/infrastructure • Data quality • Information lifecyle management • Metadata/business glossaries • Organizational design/development • Policy/risk management • Security/privacy/compliance • Stewardship/value creation
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ibm, data governance, safeguard information, data quality, data architecture, data infrastructure, information lifecycle management, metadata
    
IBM
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