quality data

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Data Visualization: Charting the Best Course for Your Organization

Published 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, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, business intelligence, productivity, data center
    
SAS

Data Visualization: 7 Considerations for Visualization Deployment

Published 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, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, visualization deployment, deployment, institute for analytics, best practices, business intelligence, data center
    
SAS

Populating a Data Quality Scorecard with Relevant Metrics

Published 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, business relevance, measured value, emergent patterns, quality metrics, potential classifications, data analyst, scorecard, reporting the scorecard, improve scorecard, business process, best practices, business activity monitoring
    
SAS

Observing Data Quality Service Level Agreements: Inspection, Monitoring and Tracking

Published By: SAS     Published Date: Mar 14, 2014
This paper will consider the relevance of measurement and monitoring – defining inspection routines, inserting them into the end-to-end application processing, and reporting the results.
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sas, data quality, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, potential classifications, data analyst, scorecard, reporting the scorecard, improve scorecard, business process, best practices, business analytics
    
SAS

Maps, Mechanics & Morals When Launching Your Data Governance Initiative

Published 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, business objectives, quality data, accuracy, lineage, structural consistency, relevant metrics, business relevance, measured value, emergent patterns, quality metrics, best practices, business analytics
    
SAS

Five Best Practices for Application-aware Network Performance Management (AANPM) in 2014

Published By: EMA     Published Date: Apr 01, 2014
Application-aware Network Performance Management (AANPM) practices and products provide detailed insights into exactly who is using which resources, what quality of experience is taking place, and where to look when things go wrong. Such information can significantly improve planning, monitoring, and troubleshooting efforts.
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ema, application aware network performace, aanpm, quality of experience, research, it management, data management, consulting
    
EMA

Making the case for data lifecycle management

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 infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, lifecycle management
    
IBM

Business Driven Governance: Managing Policies for Data Retention

Published 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, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence
    
IBM

Big Data, Good Data, Bad Data-the link between information governance and Big Data outcomes

Published 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, data center
    
IBM

IBM BigInsights BigIntegrate and BigQuality: Information Empowerment for Your Big Data Ecosystem

Published By: IBM     Published Date: Jan 14, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
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ibm, biginsights, bigintegrate, bigquality, data, ecosystem, governance, integration, enterprise applications, data management, business technology
    
IBM

The Total Economic Impact of IBM Information Integration and Governance Solutions-Forrester Report

Published By: IBM     Published Date: Jan 14, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
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ibm, biginsights, bigintegrate, bigquality, data, ecosystem, governance, integration, enterprise applications, data management, business technology
    
IBM

Top tips for securing big data environments

Published By: IBM     Published Date: Apr 06, 2016
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments
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ibm, big data, data security, risk management, security
    
IBM

IBM BigInsights BigIntegrate and BigQuality: Information Empowerment for Your Big Data Ecosystem

Published By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
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ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality, data integration
    
IBM

Top tips for securing big data environments

Published By: IBM     Published Date: Jul 15, 2016
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments.
Tags : 
ibm, data, security, big data, data management
    
IBM

Big Data, Bad Data, Good Data - The Link Between Information Governance and Big Data Outcomes

Published By: IBM     Published Date: Oct 18, 2016
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.
Tags : 
ibm, idc, big data, data, analytics, information governance, knowledge management, enterprise applications, data management, data center
    
IBM

Prepare And Maintain Your Data - Data Quality And Master Data Management In A Hybrid Environment

Published By: IBM     Published Date: Apr 14, 2017
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
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cloud-based data, data quality, data management, hybrid environment, decision making
    
IBM

Establishing Confidence in PDN Simulation

Published By: Mentor Graphics     Published Date: Apr 03, 2009
A powerful signal integrity analysis tool must be flexibility, easy to use and integrated into an existing EDA framework and design flow. In addition, it is important for the tool to be accurate enough. This report reviews a validation study for the Mentor Graphics HyperLynx 8.0 PI tool to establish confidence in using it for power integrity analysis.
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mentor graphics, pdn simulation, eda framework, mentor hyperlynx 8.0 pi, integrity analysis, virtual prototypes, esr, capacitor, power distribution network, vrm, voltage regulator module, signal, smas, analog models, backward crosstalk, capacitive crosstalk, controlling crosstalk, correct emc problems, correct emi problems, cross talk
    
Mentor Graphics

Measuring the Performance of Equalized Serial Data Links Across the Design Flow

Published By: Mentor Graphics     Published Date: Apr 03, 2009
For advanced signaling over high-loss channels, designs today are using equalization and several new measurement methods to evaluate the performance of the link. Both simulation and measurement tools support equalization and the new measurement methods, but correlation of results throughout the design flow is unclear. In this paper a high performance equalizing serial data link is measured and the performance is compared to that predicted by simulation. Then, the differences between simulation and measurements are discussed as well as methods to correlate the two.
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mentor graphics, equalized serial data links, design flow, high loss channels, tektronix, pcb, bit error rate, ber, ieee, serdes, simulation, system configuration, mentor graphics hyperlynx, simplified symmetric trapezoidal input, duty cycle distortion, ber contours, electronics, analog models, backward crosstalk, capacitive crosstalk
    
Mentor Graphics

How to Sell Backup to Your CFO

Published By: Unitrends     Published Date: Jun 15, 2010
In this document we're first going to explore the use of the insurance metaphor in terms of its most fundamental element: the broad consequences of data loss. We'll also discuss industry and regulatory consequences of data loss.
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unitrends, backup, data protection, data quality, server, replication, data loss, sox, backup and recovery, storage management, it spending, return on investment, database development
    
Unitrends

Don't Get Duped By Dedupe: Introducing Adaptive Deduplication

Published By: Unitrends     Published Date: Apr 12, 2010
The purpose of deduplication is to provide more storage, particularly backup storage, for less money, right? Then wouldn't it be ridiculous if deduplication vendors were demanding that their customers pay more per terabyte of storage? Or if they were simply pushing the task of integrating, monitoring, and managing deduplication back onto their users?
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unitrends, backup, data protection, data quality, server, replication, lossless, lossy, data compression, backup and recovery, storage area networks, storage management, storage virtualization, encryption, database development
    
Unitrends

7 Shortcuts to Losing Your Data (and Probably Your Job)

Published By: Unitrends     Published Date: May 18, 2010
This tongue in cheek white paper explores data loss from a contrarian point of view - exploring the top 7 shortcuts you can take to ensure that you lose your data. And since a fundamental responsibility of any information technology professional, as well as any C-level executive, is to ensure that the data upon which any company is created is protected - scrupulously following these shortcuts should also ensure that you lose not only your data but your job as well.
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unitrends, backup, data protection, data quality, server, replication, data loss, sox, backup and recovery, storage management
    
Unitrends

5 Data management for analytics best practices

Published By: SAS     Published Date: Aug 28, 2018
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
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SAS

The secret of IT Success? Enabling Choice and Control

Published By: SAS     Published Date: Mar 20, 2019
In today’s crowded analytics marketplace, who can you trust? What’s needed to deliver on the promise of transforming data into real value? And what do CIOs need to cost-effectively and successfully lead their organizations through changing technologies? For an organization to experiment with (and ultimately deploy) analytics, the responsibility falls squarely on the shoulders of IT. IT must provide secure access to lots of high-quality data, a friendly environment for experimentation and discovery, and a method for rapidly deploying and governing models. SAS can support an organization's journey toward becoming a data- and analytics-driven organization. We can help unlock the value by enabling with choices that make sense. Plus, we can show organizations how to get the most out of technology investments.
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SAS

How to Increase Landing Page Conversion Rates With Data Validation

Published By: StrikeIron     Published Date: Oct 03, 2013
Learn how to increase your landing page conversion rate by 10-30% using data validation, which will help you to get the most out of your landing page optimization.
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strikeiron, data quality, data validation, data, daas, data-as-a-service, landing page optimizations, cloud-based, cloud, landing page conversion rates, software development, it management, telecom
    
StrikeIron
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