�ݺ�ߣshows by User: aberkowitz

�ݺ�ߣshows by User: aberkowitz / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: aberkowitz / Mon, 20 Jul 2015 16:15:51 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: aberkowitz Data Ed: Best Practices with the DMM /slideshow/data-ed/50721817 dmm2015webinar-150720161551-lva1-app6892
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.]]>
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.]]> Mon, 20 Jul 2015 16:15:51 GMT /slideshow/data-ed/50721817 aberkowitz@slideshare.net(aberkowitz) Data Ed: Best Practices with the DMM aberkowitz The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dmm2015webinar-150720161551-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization’s data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.

Data Ed: Best Practices with the DMM from Data Blueprint

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1 Data-Ed: A Framework for no sql and Hadoop /slideshow/dataed-a-framework-for-no-sql-hadoop-handout/49227520 frameworkfornosqlhadoophandout-150610152815-lva1-app6892
Big Data and NoSQL continue to make headlines everywhere. However, most of what has been written about these topics is focused on the hardware, services, and scale out. But what about a Big Data and NoSQL Strategy, one that supports your business strategy? Virtually every major organization thinking about these data platforms is faced with the challenge of figuring out the appropriate approach and the requirements. This presentation will provide guidance on how to think about and establish realistic Big Data management plans and expectations. We will introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL and show how to demonstrate a sample use case.]]>
Big Data and NoSQL continue to make headlines everywhere. However, most of what has been written about these topics is focused on the hardware, services, and scale out. But what about a Big Data and NoSQL Strategy, one that supports your business strategy? Virtually every major organization thinking about these data platforms is faced with the challenge of figuring out the appropriate approach and the requirements. This presentation will provide guidance on how to think about and establish realistic Big Data management plans and expectations. We will introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL and show how to demonstrate a sample use case.]]> Wed, 10 Jun 2015 15:28:15 GMT /slideshow/dataed-a-framework-for-no-sql-hadoop-handout/49227520 aberkowitz@slideshare.net(aberkowitz) Data-Ed: A Framework for no sql and Hadoop aberkowitz Big Data and NoSQL continue to make headlines everywhere. However, most of what has been written about these topics is focused on the hardware, services, and scale out. But what about a Big Data and NoSQL Strategy, one that supports your business strategy? Virtually every major organization thinking about these data platforms is faced with the challenge of figuring out the appropriate approach and the requirements. This presentation will provide guidance on how to think about and establish realistic Big Data management plans and expectations. We will introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL and show how to demonstrate a sample use case. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/frameworkfornosqlhadoophandout-150610152815-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Big Data and NoSQL continue to make headlines everywhere. However, most of what has been written about these topics is focused on the hardware, services, and scale out. But what about a Big Data and NoSQL Strategy, one that supports your business strategy? Virtually every major organization thinking about these data platforms is faced with the challenge of figuring out the appropriate approach and the requirements. This presentation will provide guidance on how to think about and establish realistic Big Data management plans and expectations. We will introduce a framework for evaluating the various choices when it comes to implementing and succeeding with Big Data/NoSQL and show how to demonstrate a sample use case.

Data-Ed: A Framework for no sql and Hadoop from Data Blueprint

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1 Data-Ed: Monetizing Data Management /slideshow/dataed-monetizing-data-management-48339128/48339128 2015monetizingslides-150519144516-lva1-app6891
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.]]>
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.]]> Tue, 19 May 2015 14:45:16 GMT /slideshow/dataed-monetizing-data-management-48339128/48339128 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Monetizing Data Management aberkowitz Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015monetizingslides-150519144516-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.

Data-Ed: Monetizing Data Management from Data Blueprint

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1 Data-Ed: Data Governance Strategies /slideshow/2015-dg-strategies-handouts/47521195 2015dgstrategieshandouts-150428112311-conversion-gate02
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]>
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]> Tue, 28 Apr 2015 11:23:11 GMT /slideshow/2015-dg-strategies-handouts/47521195 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data Governance Strategies aberkowitz The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015dgstrategieshandouts-150428112311-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /> The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Governance Strategies from Data Blueprint

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1 Data-Ed: Data Architecture Requirements /slideshow/dataed-data-architecture-requirments/45765667 2015-03dataarchitecturerequirements-150312130553-conversion-gate01
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/]]>
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/]]> Thu, 12 Mar 2015 13:05:53 GMT /slideshow/dataed-data-architecture-requirments/45765667 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data Architecture Requirements aberkowitz Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015-03dataarchitecturerequirements-150312130553-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find out more: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Architecture Requirements from Data Blueprint

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1 Data-Ed: Business Value From MDM /slideshow/2015-business-value-from-mdm-final/44647906 2015-businessvaluefrommdmfinal-150213104351-conversion-gate01
This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM. Check out more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]>
This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM. Check out more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]> Fri, 13 Feb 2015 10:43:51 GMT /slideshow/2015-business-value-from-mdm-final/44647906 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Business Value From MDM aberkowitz This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM. Check out more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2015-businessvaluefrommdmfinal-150213104351-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM. Check out more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Business Value From MDM from Data Blueprint

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1 Strategy and roadmap slides /slideshow/strategy-and-roadmap-slides/43596694 strategyandroadmapslides-150116133828-conversion-gate02
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.]]>
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.]]> Fri, 16 Jan 2015 13:38:28 GMT /slideshow/strategy-and-roadmap-slides/43596694 aberkowitz@slideshare.net(aberkowitz) Strategy and roadmap slides aberkowitz Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/strategyandroadmapslides-150116133828-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.

Strategy and roadmap slides from Data Blueprint

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1 Data-Ed: Data Warehousing Strategies /aberkowitz/2014-warehousing-strategies-slides 2014warehousingstrategiesslides-141215094112-conversion-gate01
Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation. Find more Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]>
Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation. Find more Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/]]> Mon, 15 Dec 2014 09:41:12 GMT /aberkowitz/2014-warehousing-strategies-slides aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data Warehousing Strategies aberkowitz Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation. Find more Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014warehousingstrategiesslides-141215094112-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation. Find more Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Warehousing Strategies from Data Blueprint

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1 Data-Ed: Metadata Strategies /slideshow/2014-metadata-management-strategieskey-41655167/41655167 2014metadatamanagementstrategies-141117085734-conversion-gate01
Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy. Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]>
Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy. Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]> Mon, 17 Nov 2014 08:57:34 GMT /slideshow/2014-metadata-management-strategieskey-41655167/41655167 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Metadata Strategies aberkowitz Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy. Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014metadatamanagementstrategies-141117085734-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Good systems development often depends on multiple data management disciplines that provide a solid foundation. One of these is metadata. While much of the discussion around metadata focuses on understanding metadata itself along with its associated technologies, this perspective often represents a typical tool-and-technology focus, which has not achieved significant results to date. A more relevant question when considering pockets of metadata is whether to include them in the scope of organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies in support of business strategy. Find more data management webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Metadata Strategies from Data Blueprint

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1 Data-Ed: Trends in Data Modeling /slideshow/dataed-trends-in-data-modeling/40409144 trendsindatamodeling-141017132643-conversion-gate02
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]]> Fri, 17 Oct 2014 13:26:43 GMT /slideshow/dataed-trends-in-data-modeling/40409144 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Trends in Data Modeling aberkowitz <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/trendsindatamodeling-141017132643-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" />

Data-Ed: Trends in Data Modeling from Data Blueprint

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1 Data-Ed: Data Governance Strategies /slideshow/2014-dg-strategieskey1/39208722 2014dgstrategies-140917141135-phpapp02
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]>
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]> Wed, 17 Sep 2014 14:11:35 GMT /slideshow/2014-dg-strategieskey1/39208722 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data Governance Strategies aberkowitz The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014dgstrategies-140917141135-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data Governance Strategies from Data Blueprint

]]> 1610 4 https://cdn.slidesharecdn.com/ss_thumbnails/2014dgstrategies-140917141135-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Best Practices with the Data Management Maturity Model /slideshow/dmmkey-aug-12-final/38032641 dmm-140815133624-phpapp01
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.]]>
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.]]> Fri, 15 Aug 2014 13:36:24 GMT /slideshow/dmmkey-aug-12-final/38032641 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Best Practices with the Data Management Maturity Model aberkowitz The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dmm-140815133624-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.

Data-Ed: Best Practices with the Data Management Maturity Model from Data Blueprint

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1 Data-Ed: Design and Manage Data Structures /slideshow/dataed-design-and-manage-data-structures/36952381 2014datastructuresv6-140714075944-phpapp01
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]]> Mon, 14 Jul 2014 07:59:44 GMT /slideshow/dataed-design-and-manage-data-structures/36952381 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Design and Manage Data Structures aberkowitz <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014datastructuresv6-140714075944-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

Data-Ed: Design and Manage Data Structures from Data Blueprint

]]> 951 3 https://cdn.slidesharecdn.com/ss_thumbnails/2014datastructuresv6-140714075944-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Monetizing Data Management /slideshow/2014-monetizing-handouts/35801908 2014monetizing-handouts-140612113813-phpapp02
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives. Check out more of our webinars here: http://www.datablueprint.com/resource-center/]]>
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives. Check out more of our webinars here: http://www.datablueprint.com/resource-center/]]> Thu, 12 Jun 2014 11:38:13 GMT /slideshow/2014-monetizing-handouts/35801908 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Monetizing Data Management aberkowitz Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives. Check out more of our webinars here: http://www.datablueprint.com/resource-center/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014monetizing-handouts-140612113813-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives. Check out more of our webinars here: http://www.datablueprint.com/resource-center/

Data-Ed: Monetizing Data Management from Data Blueprint

]]> 940 7 https://cdn.slidesharecdn.com/ss_thumbnails/2014monetizing-handouts-140612113813-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Data Architecture Requirements /aberkowitz/2014-05-data-architecture-requirements-handouts 2014-05dataarchitecturerequirementshandouts-140516124336-phpapp01
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find more Data-Ed webinars here: www.datablueprint.com ]]>
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find more Data-Ed webinars here: www.datablueprint.com ]]> Fri, 16 May 2014 12:43:36 GMT /aberkowitz/2014-05-data-architecture-requirements-handouts aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data Architecture Requirements aberkowitz Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find more Data-Ed webinars here: www.datablueprint.com <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014-05dataarchitecturerequirementshandouts-140516124336-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business. Find more Data-Ed webinars here: www.datablueprint.com

Data-Ed: Data Architecture Requirements from Data Blueprint

]]> 1946 7 https://cdn.slidesharecdn.com/ss_thumbnails/2014-05dataarchitecturerequirementshandouts-140516124336-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

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1 2014 dqe handouts /slideshow/2014-dqe-handouts/33382925 2014dqehandouts-140410143248-phpapp01
Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring. ]]>
Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring. ]]> Thu, 10 Apr 2014 14:32:48 GMT /slideshow/2014-dqe-handouts/33382925 aberkowitz@slideshare.net(aberkowitz) 2014 dqe handouts aberkowitz Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014dqehandouts-140410143248-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring.

2014 dqe handouts from Data Blueprint

]]> 1359 6 https://cdn.slidesharecdn.com/ss_thumbnails/2014dqehandouts-140410143248-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Emerging Trends in Data Jobs /slideshow/emerging-data-jobs-handouts/32443235 emergingdatajobs-handouts-140318080451-phpapp01
Tools alone are not the answer: Career roles and growth tracks for data professionals. In today’s (Big) data-driven information economy, it is even more critical to focus on data as an asset that directly supports business imperatives. But tools alone are not the answer. Organizations that want to rise above their competition can only do so with the help of skilled professionals who know how to manage, mine, and draw actionable insights from the multitudes of (Big) data sources. Numerous new roles and job titles have emerged to address the high demand for specialized data professionals. This webinar brings together three individuals well qualified to contribute to this important industry-wide discussion of data jobs. We will take a closer look at these newer data management roles and present recommendations on how to enhance career paths. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-archive/]]>
Tools alone are not the answer: Career roles and growth tracks for data professionals. In today’s (Big) data-driven information economy, it is even more critical to focus on data as an asset that directly supports business imperatives. But tools alone are not the answer. Organizations that want to rise above their competition can only do so with the help of skilled professionals who know how to manage, mine, and draw actionable insights from the multitudes of (Big) data sources. Numerous new roles and job titles have emerged to address the high demand for specialized data professionals. This webinar brings together three individuals well qualified to contribute to this important industry-wide discussion of data jobs. We will take a closer look at these newer data management roles and present recommendations on how to enhance career paths. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-archive/]]> Tue, 18 Mar 2014 08:04:50 GMT /slideshow/emerging-data-jobs-handouts/32443235 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Emerging Trends in Data Jobs aberkowitz Tools alone are not the answer: Career roles and growth tracks for data professionals. In today’s (Big) data-driven information economy, it is even more critical to focus on data as an asset that directly supports business imperatives. But tools alone are not the answer. Organizations that want to rise above their competition can only do so with the help of skilled professionals who know how to manage, mine, and draw actionable insights from the multitudes of (Big) data sources. Numerous new roles and job titles have emerged to address the high demand for specialized data professionals. This webinar brings together three individuals well qualified to contribute to this important industry-wide discussion of data jobs. We will take a closer look at these newer data management roles and present recommendations on how to enhance career paths. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-archive/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/emergingdatajobs-handouts-140318080451-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Tools alone are not the answer: Career roles and growth tracks for data professionals. In today’s (Big) data-driven information economy, it is even more critical to focus on data as an asset that directly supports business imperatives. But tools alone are not the answer. Organizations that want to rise above their competition can only do so with the help of skilled professionals who know how to manage, mine, and draw actionable insights from the multitudes of (Big) data sources. Numerous new roles and job titles have emerged to address the high demand for specialized data professionals. This webinar brings together three individuals well qualified to contribute to this important industry-wide discussion of data jobs. We will take a closer look at these newer data management roles and present recommendations on how to enhance career paths. Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-archive/

Data-Ed: Emerging Trends in Data Jobs from Data Blueprint

]]> 2082 6 https://cdn.slidesharecdn.com/ss_thumbnails/emergingdatajobs-handouts-140318080451-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Data-centric Strategy & Roadmap /slideshow/dataed-datacentric-strategy-roadmap/31184924 2014-02data-centricstrategyandroadmapv8-140213144727-phpapp02
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers. Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]>
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers. Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ ]]> Thu, 13 Feb 2014 14:47:27 GMT /slideshow/dataed-datacentric-strategy-roadmap/31184924 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Data-centric Strategy & Roadmap aberkowitz Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers. Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2014-02data-centricstrategyandroadmapv8-140213144727-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers. Check out more of our webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/

Data-Ed: Data-centric Strategy & Roadmap from Data Blueprint

]]> 6202 5 https://cdn.slidesharecdn.com/ss_thumbnails/2014-02data-centricstrategyandroadmapv8-140213144727-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Demystifying Big Data /slideshow/dataed-demystifying-big-data/30139146 demystifyingbigdatahandouts-140117122147-phpapp01
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype. Check out more of our Data-Ed webinars here: www.datablueprint.com/webinar-schedule ]]>
We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype. Check out more of our Data-Ed webinars here: www.datablueprint.com/webinar-schedule ]]> Fri, 17 Jan 2014 12:21:47 GMT /slideshow/dataed-demystifying-big-data/30139146 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Demystifying Big Data aberkowitz We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype. Check out more of our Data-Ed webinars here: www.datablueprint.com/webinar-schedule <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/demystifyingbigdatahandouts-140117122147-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> We are in the middle of a data flood and we need to figure out how to tame it without drowning. Most of what has been written about Big Data is focused on selling hardware and services. But what about a Big Data Strategy that guides hardware and software decisions? While virtually every major organization is faced with the challenge of figuring out the approach for and the requirements of this new development, jumping into the fray hastily and unprepared will only reproduce the same dismal IT project results as previously experienced. Join Dr. Peter Aiken as he will debunk a number of misconceptions about Big Data as your un-typical IT project. He will provide guidance on how to establish realistic Big Data management plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers without getting lost in the hype. Check out more of our Data-Ed webinars here: www.datablueprint.com/webinar-schedule

Data-Ed: Demystifying Big Data from Data Blueprint

]]> 1147 5 https://cdn.slidesharecdn.com/ss_thumbnails/demystifyingbigdatahandouts-140117122147-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

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1 Data-Ed: Unlock Business Value through Document & Content Management /slideshow/2013-document-content-management-handouts/29185527 2013-documentcontentmanagementhandouts-131213113031-phpapp02
Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling. Learning Objectives: What is Document & Content Management and why is it important? Planning and Implementing Document & Content Management Document/Record Management Lifecycle Levels of Control Content management building blocks Guiding principles & best practices Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK) http://www.datablueprint.com/webinar-schedule]]>
Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling. Learning Objectives: What is Document & Content Management and why is it important? Planning and Implementing Document & Content Management Document/Record Management Lifecycle Levels of Control Content management building blocks Guiding principles & best practices Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK) http://www.datablueprint.com/webinar-schedule]]> Fri, 13 Dec 2013 11:30:31 GMT /slideshow/2013-document-content-management-handouts/29185527 aberkowitz@slideshare.net(aberkowitz) Data-Ed: Unlock Business Value through Document & Content Management aberkowitz Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling. Learning Objectives: What is Document & Content Management and why is it important? Planning and Implementing Document & Content Management Document/Record Management Lifecycle Levels of Control Content management building blocks Guiding principles & best practices Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK) http://www.datablueprint.com/webinar-schedule <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2013-documentcontentmanagementhandouts-131213113031-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Organizations must realize what it means to utilize document and content management in support of business strategy. The volume of unstructured data is growing at an enormous pace. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our business and data management capabilities into more critical and regulated areas. This presentation provides you with an understanding of the dimensions of these new developments, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling. Learning Objectives: What is Document & Content Management and why is it important? Planning and Implementing Document & Content Management Document/Record Management Lifecycle Levels of Control Content management building blocks Guiding principles & best practices Understanding foundational document & content management concepts based on the Data Management Body of Knowledge (DMBOK) http://www.datablueprint.com/webinar-schedule

Data-Ed: Unlock Business Value through Document & Content Management from Data Blueprint

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1 https://cdn.slidesharecdn.com/profile-photo-aberkowitz-48x48.jpg?cb=1522925730 Data Blueprint is a data management consulting firm that puts organizations on the right path to leverage data for competitive advantage and operational efficiency. We unlock business value. It is our belief that strong data management capabilities are the key to long-term value creation. Our unique approach leverages core competencies in both foundational and technical data management practices. We help clients leverage data as a strategic asset and become data-driven. www.datablueprint.com https://cdn.slidesharecdn.com/ss_thumbnails/dmm2015webinar-150720161551-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/data-ed/50721817 Data Ed: Best Practice... https://cdn.slidesharecdn.com/ss_thumbnails/frameworkfornosqlhadoophandout-150610152815-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/dataed-a-framework-for-no-sql-hadoop-handout/49227520 Data-Ed: A Framework f... https://cdn.slidesharecdn.com/ss_thumbnails/2015monetizingslides-150519144516-lva1-app6891-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/dataed-monetizing-data-management-48339128/48339128 Data-Ed: Monetizing Da...