The document discusses a presentation on managing unstructured data and documents. It provides an outline of the presentation topics, which include an overview of document and content management, planning and implementation, levels of control, and building blocks. It also introduces the presenter, Dr. Peter Aiken, and his background in data management. Live interaction is encouraged through social media like Twitter.
MDM and Data Quality: Not an Option but a RequirementDATAVERSITY
This document summarizes a webinar on reference and master data management (MDM). The webinar covered topics such as definitions of reference data, MDM, and the importance of quality reference and master data. It also reviewed building blocks and best practices for reference and MDM. The webinar was presented by Dr. Peter Aiken on June 12, 2012 and included a question and answer section where attendees could participate on Twitter.
Data-Ed Online: MDM: Quality is not an Option but a RequirementData Blueprint
This webinar aired originally on Tuesday, June 12, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Our 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.
Practical Applications for Data Warehousing, Analytics, BI, and Meta-Integrat...DATAVERSITY
The presentation provides an overview of data warehousing, business intelligence, analytics, and meta-integration technologies, explaining their definitions and importance for enabling analysis of previously unintegrated information to support better business decision making. It also discusses common data warehouse failures and outlines best practices for implementing these technologies, including the use of meta-models and a focus on data quality. The presentation concludes by emphasizing the takeaways and providing references and an opportunity for questions.
Data-Ed Online: Your Documents and Other Content: Managing Unstructured Data Data Blueprint
This webinar originally aired on Tuesday, August 14, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Non-tabular data plays an increasing role in organizations. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our data management capabilities into more critical and more regulated areas. This presentation provides you with an understanding of the dimensions of this vast new area, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling.
Get the Most Out of Your Tools: Data Management TechnologiesDATAVERSITY
This document provides an overview of a presentation on data management technologies. The presentation will be given by Dr. Peter Aiken, an internationally recognized expert in data management with over 30 years of experience. The presentation outlines includes discussions on data management tools, data technology architecture, CASE tools, repositories, profiling/discovery tools, data quality engineering tools, and the data lifecycle. The document encourages participants to engage on Twitter using the hashtag #dataed.
Data-Ed: Show Me the Money: The Business Value of Data and ROIData Blueprint
This webinar originally aired on Tuesday, December 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Failure to successfully monetize data management investments sets up an unfortunate loop of fixing symptoms without addressing the underlying problems. As organizations begin to understand poor data management practices as the root causes of many of their problems, they become more willing to make the required investments in our profession. This presentation uses specific examples to illustrate the costs of poor data management. Join us and learn how you can apply similar tactics at your organization to justify funding and gain management approval.
This webinar aired originally on Tuesday, March 13, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
This presentation provides you with an understanding of the data modeling and data development components of data management. Participants will understand how the analysis, design, implementation, deployment, and maintenance of data solutions should be approached in order to maximize the full value of the enterprise data resources and activities. Architecting in quality is imperative at this level and complements a subset of project activities within the system development lifecycle (SDLC) focused on defining data requirements, designing data solution components, and implementing these components. Participants will understand the difficulties organizations experience when interacting with data development efforts and how to best incorporate these efforts into specific data projects.
View the video recording here: http://www.slideshare.net/aberkowitz/dataed-online-practical-data-modeling-12019990
Data-Ed Online: How Safe is Your Data? Data Security WebinarData Blueprint
This webinar aired originally on Tuesday, May 15, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Our presentation provides you with an overview of the organizational data security management requirements that are necessary to meet industry benchmarks. Participants will understand the requirements for planning, developing, and executing security policies and procedures to provide proper authentication, authorization, access, and auditing of data and information assets. By the end of our session, you will understand how effective data security policies and procedures ensure that the right people can use and update data in the right way, as well as the importance of restricting inappropriate access.
MDM and Data Quality: Not an Option but a RequirementDATAVERSITY
This document summarizes a webinar on reference and master data management (MDM). The webinar covered topics such as definitions of reference data, MDM, and the importance of quality reference and master data. It also reviewed building blocks and best practices for reference and MDM. The webinar was presented by Dr. Peter Aiken on June 12, 2012 and included a question and answer section where attendees could participate on Twitter.
Data-Ed Online: MDM: Quality is not an Option but a RequirementData Blueprint
This webinar aired originally on Tuesday, June 12, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Our 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.
Practical Applications for Data Warehousing, Analytics, BI, and Meta-Integrat...DATAVERSITY
The presentation provides an overview of data warehousing, business intelligence, analytics, and meta-integration technologies, explaining their definitions and importance for enabling analysis of previously unintegrated information to support better business decision making. It also discusses common data warehouse failures and outlines best practices for implementing these technologies, including the use of meta-models and a focus on data quality. The presentation concludes by emphasizing the takeaways and providing references and an opportunity for questions.
Data-Ed Online: Your Documents and Other Content: Managing Unstructured Data Data Blueprint
This webinar originally aired on Tuesday, August 14, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Non-tabular data plays an increasing role in organizations. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our data management capabilities into more critical and more regulated areas. This presentation provides you with an understanding of the dimensions of this vast new area, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling.
Get the Most Out of Your Tools: Data Management TechnologiesDATAVERSITY
This document provides an overview of a presentation on data management technologies. The presentation will be given by Dr. Peter Aiken, an internationally recognized expert in data management with over 30 years of experience. The presentation outlines includes discussions on data management tools, data technology architecture, CASE tools, repositories, profiling/discovery tools, data quality engineering tools, and the data lifecycle. The document encourages participants to engage on Twitter using the hashtag #dataed.
Data-Ed: Show Me the Money: The Business Value of Data and ROIData Blueprint
This webinar originally aired on Tuesday, December 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Failure to successfully monetize data management investments sets up an unfortunate loop of fixing symptoms without addressing the underlying problems. As organizations begin to understand poor data management practices as the root causes of many of their problems, they become more willing to make the required investments in our profession. This presentation uses specific examples to illustrate the costs of poor data management. Join us and learn how you can apply similar tactics at your organization to justify funding and gain management approval.
This webinar aired originally on Tuesday, March 13, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
This presentation provides you with an understanding of the data modeling and data development components of data management. Participants will understand how the analysis, design, implementation, deployment, and maintenance of data solutions should be approached in order to maximize the full value of the enterprise data resources and activities. Architecting in quality is imperative at this level and complements a subset of project activities within the system development lifecycle (SDLC) focused on defining data requirements, designing data solution components, and implementing these components. Participants will understand the difficulties organizations experience when interacting with data development efforts and how to best incorporate these efforts into specific data projects.
View the video recording here: http://www.slideshare.net/aberkowitz/dataed-online-practical-data-modeling-12019990
Data-Ed Online: How Safe is Your Data? Data Security WebinarData Blueprint
This webinar aired originally on Tuesday, May 15, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Our presentation provides you with an overview of the organizational data security management requirements that are necessary to meet industry benchmarks. Participants will understand the requirements for planning, developing, and executing security policies and procedures to provide proper authentication, authorization, access, and auditing of data and information assets. By the end of our session, you will understand how effective data security policies and procedures ensure that the right people can use and update data in the right way, as well as the importance of restricting inappropriate access.
DataEd Online: Building the Case for the Top Data JobDATAVERSITY
This document discusses the need for a chief data officer role to oversee organizational data management. It notes that current IT management is not well-suited to leverage data as a strategic asset. Only 1% of organizations achieve data management success due to a lack of professional data management. The requirements dictate a full-time role external to IT to manage data from a function preceding software development. Creating this role could improve performance more than other initiatives. The presentation will provide context on data management and examine why CIOs cannot devote sufficient time or expertise to data, and will explore the ideal relationship between data and IT.
6-7-2011 Objects Engagement and Web 2.0 - PEMCIMathieu Plourde
Here are the steps:
1. Go to http://www.diigo.com and create a free account
2. Once logged in, search for the group "PEMCI 2011" and join it
3. Start bookmarking and tagging web pages you find relevant
4. You can now collaborate and share bookmarks with the group
Let me know if you have any other questions!
This document summarizes the agenda for the 2011 STI Semantic Summit. The summit was chaired by John Domingue and included sessions on topics such as managing data at web scale, the future of the semantic web, linked data in domains, and making linked data work. Presenters included Rudi Studer, Michael Brodie, Mark Greaves, and others. The summit provided an opportunity for discussion around conclusions, challenges, and next steps regarding semantic web and linked data technologies.
Research Data and Scholarly CommunicationDorothea Salo
This document is a presentation on research data and scholarly communication given by Dorothea Salo at Marquette University on February 11, 2013. It discusses how data is becoming increasingly important in scholarly communication, raising issues around who owns metadata, how data is shared and stored, and the infrastructure needed to support data citation, discovery, and reuse. The presentation covers topics such as funder policies, data management practices, and the human training required to facilitate open data sharing.
The document provides an overview of a workshop on using social software like blogs and wikis in the classroom, including going over examples of blogs and wikis, hands-on creating of blogs and wikis, and reflecting on their educational benefits and challenges in implementing them. The workshop will cover setting up blogs and wikis, their purposes in education, and providing time to work on creating blogs and getting feedback.
My talk at UC Berkeley on 26 April 2102 at the Swinging & Flowing Conference. An opportunity to compare the digital divide in the USA and the UK and to talk about ways to increase digital equality.
This is the dossier walking through the planning phase for a wordpress plugin--a project management tool.
It includes requirements gathering, sample output, and definitions of the plugin's vocabulary.
Data-Ed Online: Unlock Business Value through Document & Content ManagementDATAVERSITY
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 include:
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)
How to utilize document & content management in support of business strategy
Ep seminar presentation version 2 morgan mar 2013Andrew Morgan
This document discusses environmental plans for marine resource development projects. It provides an overview of the regulatory requirements for environmental plans in Australia, including their content, assessment criteria, and consultation requirements. The document aims to understand how different aspects of environmental plans are connected and to provide solutions to improve their preparation and acceptance by regulators.
In this slide, we introduce the mechanism of Solr used in Search Engine Back End API Solution for Fast Prototyping (LDSP). You will learn how to create a new core, update schema, query and sort in Solr.
CDO Slides: Real World Data Strategy Success StoriesDATAVERSITY
A common question from upper management is “Does this really work? Can you show me where there has been success?” Well, the answer is “Yes, this works.” Join John and Kelle for a review of Data Strategy success stories. We will review success stories for data governance, data quality, and other types of data.
Some successes we will examine are:
- Standing up data governance in difficult cultures
- EIM programs that created value for the organization
- Several small case studies of organizations that have had success in DQ, Analytics, and MDM
The 2020 consumer is coming fast. Companies need to get ready for a new form of marketing. This presentation describes the capabilities and the organization needed to be successful in 2020.
Data-Ed Online: Let's Talk Metadata: Strategies and Successes Data Blueprint
This webinar originally aired on Tuesday, September 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Commonly described as metadata management, properly implemented metadata practices incorporate data structures into more abstract processing. By using data about the data to enhance its value, its understandability, ease of use and many other options, organizations have developed sophisticated ways to enhance their data management and especially their data quality engineering efforts. Join us to learn more about specific metadata benefits and how to leverage it to achieve success within your organization.
Data-Ed Online: Practical Applications for Data Warehousing, Analytics, BI, a...Data Blueprint
This webinar aired originally on Tuesday, July 10, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Meta-integration is considered data warehousing by some, while others describe it as data virtualization. This presentation provides an overview of meta-integration starting with organizational requirements. We will discuss how meta-models can be used to jump-start organizational efforts. Participants will understand the strengths and weaknesses of various technological capabilities, and the key role of data quality in all of them.
DataEd Online: Show Me the Money - The Business Value of Data and ROIDATAVERSITY
This document provides a summary of a presentation on monetizing data management and calculating return on investment (ROI) from data. The presentation was given by Dr. Peter Aiken on December 11, 2012. It included an outline covering data management overview, ineffective data management investments, root cause analysis, success stories and monetization examples, guiding principles, and a question and answer section.
The presentation discussed common reasons for ineffective data management investments such as a lack of data management planning, involvement and coordination. It also reviewed statistics on high rates of IT project failures and challenges calculating ROI from data. Examples of successful monetization strategies from other organizations were to be provided.
Practical Applications for Data Warehousing, Analytics, BI, and Meta-Integrat...DATAVERSITY
This presentation provides an overview of data warehousing, analytics, business intelligence, and meta-integration technologies. It will discuss organizational requirements and how meta-models can help jumpstart efforts. Participants will understand strengths and weaknesses of technologies and the key role of data quality. Proper analysis at the start leads to more accurate technology selection. The presentation is given by Dr. Peter Aiken, an internationally recognized expert in data management.
Data-Ed Online: How Safe is Your Data? Data SecurityDATAVERSITY
The document is a presentation on data security management given by Dr. Peter Aiken. It discusses the importance of data security and outlines the key aspects of planning, developing, and executing security policies and procedures. This includes requirements for proper authentication, authorization, access controls, and auditing to restrict inappropriate access and ensure the right people can access and update data securely. Examples of data security breaches and their high costs are also provided to illustrate the importance of effective data security.
Data-Ed: Get the Most Out of Your Tools: Data Management TechnologiesData Blueprint
This webinar originally aired on Tuesday, November 13th, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
This presentation provides an overview of the many types and classes of useful technology available to data managers. These include: computer aided software/systems engineering (CASE) tools, repositories, profiling/discovery tools, data quality engineering technologies, and data integration servers.
Data-Ed Online: A Practical Approach to Data ModelingDATAVERSITY
This document summarizes a presentation on practical data modeling by Dr. Peter Aiken. The presentation provides an understanding of data modeling and data development as components of data management. It covers topics such as data modeling frameworks, data architecture building blocks, guiding principles and best practices. The presentation also discusses common mistakes organizations make in data modeling and development, and how to improve these processes.
DataEd Online: Building the Case for the Top Data JobDATAVERSITY
This document discusses the need for a chief data officer role to oversee organizational data management. It notes that current IT management is not well-suited to leverage data as a strategic asset. Only 1% of organizations achieve data management success due to a lack of professional data management. The requirements dictate a full-time role external to IT to manage data from a function preceding software development. Creating this role could improve performance more than other initiatives. The presentation will provide context on data management and examine why CIOs cannot devote sufficient time or expertise to data, and will explore the ideal relationship between data and IT.
6-7-2011 Objects Engagement and Web 2.0 - PEMCIMathieu Plourde
Here are the steps:
1. Go to http://www.diigo.com and create a free account
2. Once logged in, search for the group "PEMCI 2011" and join it
3. Start bookmarking and tagging web pages you find relevant
4. You can now collaborate and share bookmarks with the group
Let me know if you have any other questions!
This document summarizes the agenda for the 2011 STI Semantic Summit. The summit was chaired by John Domingue and included sessions on topics such as managing data at web scale, the future of the semantic web, linked data in domains, and making linked data work. Presenters included Rudi Studer, Michael Brodie, Mark Greaves, and others. The summit provided an opportunity for discussion around conclusions, challenges, and next steps regarding semantic web and linked data technologies.
Research Data and Scholarly CommunicationDorothea Salo
This document is a presentation on research data and scholarly communication given by Dorothea Salo at Marquette University on February 11, 2013. It discusses how data is becoming increasingly important in scholarly communication, raising issues around who owns metadata, how data is shared and stored, and the infrastructure needed to support data citation, discovery, and reuse. The presentation covers topics such as funder policies, data management practices, and the human training required to facilitate open data sharing.
The document provides an overview of a workshop on using social software like blogs and wikis in the classroom, including going over examples of blogs and wikis, hands-on creating of blogs and wikis, and reflecting on their educational benefits and challenges in implementing them. The workshop will cover setting up blogs and wikis, their purposes in education, and providing time to work on creating blogs and getting feedback.
My talk at UC Berkeley on 26 April 2102 at the Swinging & Flowing Conference. An opportunity to compare the digital divide in the USA and the UK and to talk about ways to increase digital equality.
This is the dossier walking through the planning phase for a wordpress plugin--a project management tool.
It includes requirements gathering, sample output, and definitions of the plugin's vocabulary.
Data-Ed Online: Unlock Business Value through Document & Content ManagementDATAVERSITY
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 include:
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)
How to utilize document & content management in support of business strategy
Ep seminar presentation version 2 morgan mar 2013Andrew Morgan
This document discusses environmental plans for marine resource development projects. It provides an overview of the regulatory requirements for environmental plans in Australia, including their content, assessment criteria, and consultation requirements. The document aims to understand how different aspects of environmental plans are connected and to provide solutions to improve their preparation and acceptance by regulators.
In this slide, we introduce the mechanism of Solr used in Search Engine Back End API Solution for Fast Prototyping (LDSP). You will learn how to create a new core, update schema, query and sort in Solr.
CDO Slides: Real World Data Strategy Success StoriesDATAVERSITY
A common question from upper management is “Does this really work? Can you show me where there has been success?” Well, the answer is “Yes, this works.” Join John and Kelle for a review of Data Strategy success stories. We will review success stories for data governance, data quality, and other types of data.
Some successes we will examine are:
- Standing up data governance in difficult cultures
- EIM programs that created value for the organization
- Several small case studies of organizations that have had success in DQ, Analytics, and MDM
The 2020 consumer is coming fast. Companies need to get ready for a new form of marketing. This presentation describes the capabilities and the organization needed to be successful in 2020.
Data-Ed Online: Let's Talk Metadata: Strategies and Successes Data Blueprint
This webinar originally aired on Tuesday, September 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
Commonly described as metadata management, properly implemented metadata practices incorporate data structures into more abstract processing. By using data about the data to enhance its value, its understandability, ease of use and many other options, organizations have developed sophisticated ways to enhance their data management and especially their data quality engineering efforts. Join us to learn more about specific metadata benefits and how to leverage it to achieve success within your organization.
Data-Ed Online: Practical Applications for Data Warehousing, Analytics, BI, a...Data Blueprint
This webinar aired originally on Tuesday, July 10, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
Meta-integration is considered data warehousing by some, while others describe it as data virtualization. This presentation provides an overview of meta-integration starting with organizational requirements. We will discuss how meta-models can be used to jump-start organizational efforts. Participants will understand the strengths and weaknesses of various technological capabilities, and the key role of data quality in all of them.
DataEd Online: Show Me the Money - The Business Value of Data and ROIDATAVERSITY
This document provides a summary of a presentation on monetizing data management and calculating return on investment (ROI) from data. The presentation was given by Dr. Peter Aiken on December 11, 2012. It included an outline covering data management overview, ineffective data management investments, root cause analysis, success stories and monetization examples, guiding principles, and a question and answer section.
The presentation discussed common reasons for ineffective data management investments such as a lack of data management planning, involvement and coordination. It also reviewed statistics on high rates of IT project failures and challenges calculating ROI from data. Examples of successful monetization strategies from other organizations were to be provided.
Practical Applications for Data Warehousing, Analytics, BI, and Meta-Integrat...DATAVERSITY
This presentation provides an overview of data warehousing, analytics, business intelligence, and meta-integration technologies. It will discuss organizational requirements and how meta-models can help jumpstart efforts. Participants will understand strengths and weaknesses of technologies and the key role of data quality. Proper analysis at the start leads to more accurate technology selection. The presentation is given by Dr. Peter Aiken, an internationally recognized expert in data management.
Data-Ed Online: How Safe is Your Data? Data SecurityDATAVERSITY
The document is a presentation on data security management given by Dr. Peter Aiken. It discusses the importance of data security and outlines the key aspects of planning, developing, and executing security policies and procedures. This includes requirements for proper authentication, authorization, access controls, and auditing to restrict inappropriate access and ensure the right people can access and update data securely. Examples of data security breaches and their high costs are also provided to illustrate the importance of effective data security.
Data-Ed: Get the Most Out of Your Tools: Data Management TechnologiesData Blueprint
This webinar originally aired on Tuesday, November 13th, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract:
This presentation provides an overview of the many types and classes of useful technology available to data managers. These include: computer aided software/systems engineering (CASE) tools, repositories, profiling/discovery tools, data quality engineering technologies, and data integration servers.
Data-Ed Online: A Practical Approach to Data ModelingDATAVERSITY
This document summarizes a presentation on practical data modeling by Dr. Peter Aiken. The presentation provides an understanding of data modeling and data development as components of data management. It covers topics such as data modeling frameworks, data architecture building blocks, guiding principles and best practices. The presentation also discusses common mistakes organizations make in data modeling and development, and how to improve these processes.
Data-Ed Online: Data Operations Management: Turning Your Challenges Into SuccessData Blueprint
This webinar aired originally on Tuesday, April 10, 2012. It is part of Data Blueprint’s ongoing webinar series on data management with Dr. Peter Aiken.
Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.
Abstract
While database operations comprise the majority of the organizational data operations management focus, other data delivery options, e.g. portals and virtualization, are interacting with increasingly complex regulatory environments. This presents organizations with dense analysis challenges in order to understand reporting obligations. Using the Zachman Framework as a guide, you will learn how to understand and approach data operations challenges from tuning to real-time reconfiguration. This presentation provides you with an understanding of data operations management, including the initiation, operation, tuning, maintenance, backup/recovery, archiving and disposal of data assets in support of organizational strategies and other activities.
Data-Ed Online: Data Operations Management: Turning your Challenges into SuccessDATAVERSITY
This document summarizes a presentation on data operations management. Dr. Peter Aiken will present on turning data challenges into success, including understanding and approaching data operations from tuning to real-time reconfiguration. The presentation will cover data operations management, including initiation, operation, tuning, maintenance, backup/recovery, archiving and disposal of data assets. It will provide an overview of data management, why data operations management is important, its building blocks, and best practices.
DataEd Online: Let's Talk Metadata Strategies and SuccessesDATAVERSITY
The document is a presentation on metadata strategies and successes given by Dr. Peter Aiken on September 11, 2012. It provides an outline of the topics to be covered including defining metadata and its importance, different types of metadata, benefits of metadata, strategies for implementation, and specific examples. The presentation aims to discuss how metadata unlocks the value of data and requires effective management.
DataEd Online: Unlocking Business Value through Data Modeling and Data Archit...DATAVERSITY
The document discusses using data modeling to unlock business value. It describes a webinar that will show how data modeling can be used to solve business problems and contribute to organizational challenges beyond traditional data modeling. The webinar aims to help attendees envision ways to use data modeling that will raise its perceived utility for business executives. Key topics that will be covered include understanding foundational data modeling concepts and how to utilize data modeling in support of business strategy.
Data-Ed: Unlocking Business Value through Data Modeling and Data Architecture...Data Blueprint
This document summarizes a webinar on using data modeling to unlock business value. The webinar discusses using data modeling as an analysis method to understand and solve business problems, rather than just showing how to data model. It demonstrates how data modeling can be used to contribute to organizational challenges, guide problem analysis, and support business strategy and architecture/engineering techniques. The goal is to help executives understand the utility of data modeling beyond traditional uses.
Data-Ed Online: Building A Solid Foundation-Data/Information ArchitectureData Blueprint
This webinar aired originally on Tuesday, February 14, 2012.
It is part of Data Blueprint’s ongoing webinar series on data management. For more information and to sign up for future session, please visit www.datablueprint.com/webinar-schedule
Abstract:
All organizations have data architectures. The question is: How effectively do they use them? This presentation provides a clear and concise understanding of what is meant by the term data architecture and the requirement that data and information architectures must be simultaneously managed. More importantly, organizations must understand what it means to use data architecture to support the implementation of organizational strategy. Participants will understand the requirements for an iterative, incremental approach to data architecture reengineering, the complimentary role of the Zachman Framework, and the ability to articulate the business value of data architecture projects and components.
View the video recording here: http://www.slideshare.net/aberkowitz/dataed-online-building-a-solid-foundationdatainformation-architecture
Data-Ed Online: "Building a Solid Foundation: Data/Information Architecture"DATAVERSITY
Dr. Peter Aiken gave a presentation on building a solid foundation through effective data and information architecture. The presentation covered defining data/information architecture, why it is important, common frameworks used including the Zachman Framework, key components, guiding principles, and how organizations can improve their utility. The goal was to provide understanding of using architecture to support organizational strategy through an iterative process.
Data-Ed: Unlocking business value through data modeling and data architecture...Data Blueprint
When asked why they are architecting data, many in the practice answer: "Because that is what must be done." However, a better approach to this question is to speak in terms that are understood in the executive suite – business results! All of our organizations are faced with various organizational challenges that require analysis. Building new systems is just one example. This webinar describes the use of data architecting as a basic analysis method (one of many that good analysts should keep in their “toolbox"). I will demonstrate various uses of data architecting to inform, clarify, understand, and resolve aspects of a variety of business problems. As opposed to showing how to architect data, I 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.
Learning Objectives:
Understanding how to contribute to organizational challenges beyond traditional data architecting
Realizing the fundamental difference between "definition" and "purpose"
Guiding analyses through data analysis
Using data modeling in conjunction with architecture/engineering techniques
Understanding foundational data architecture concepts based on the Data Management Body of Knowledge (DMBOK)
How to utilize data architecting in support of business strategy
DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Archi...DATAVERSITY
This document summarizes a webinar on using data architecture and modeling for business value. The webinar discusses data management practices and principles like the Data Management Body of Knowledge. It then provides examples of how data architecture can help solve business problems in areas like implementing a software package, processing donations, and performing text mining and analytics. The goal is to demonstrate how data architecture is a useful tool for informing, clarifying and resolving organizational challenges.
Data-Ed: Building the Case for the Top Data JobData Blueprint
Reflections on the past 25 years of organizational IT accomplishments, combined with performance measurement data, indicate that current IT management has been called upon to do a job that it cannot do well. Data are assets that deserve to be managed as professionally and aggressively as other company assets. Objective measurements show that approximately 1% of all organizations achieve data management success. In the face of the ongoing “data explosion,” this leaves most organizations wholly unprepared to leverage their sole, non-degrading, strategic asset. The requirements and organizational performance dictate a full time position that does not report to IT and manages the data function from a function that is external to and precedes the SDLC. While transformation may require some organizational discomfort, this move will achieve improved organizational IT performance faster and cheaper than ERPs or any other silver bullet.
Learning Objectives:
Why there typically isn’t and ultimately must be an authority (a chief) on organizational informational asset management
Why CIOS have not been able to devote the required time and attention
The seriousness of the skill gap – requisite expertise is rare
Understanding the ideal relationship between Data and IT.
Data-Ed Online - Making the Case for Data GovernanceData Blueprint
This webinar aired orginally on Tuesday, January 24, 2012
It is part of Data Blueprint’s ongoing webinar series on data management. For more information and to sign up for future session, please visit www.datablueprint.com/webinar-schedule
Abstract:
When thinking about data management, data governance is not one of those topics that immediately come to mind. Although neglected and often poorly performed, it is a vital function of data management and it is absurd to even consider managing data without some form of formal guidance. Data governance is central to “defining, coordinating, resourcing, implementing, and monitoring organizational data program strategies, policies, and plans as a coherent set of activities.” This presentation provides you with a clear and concise 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 and confusion that often surround initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
View the video recording here: http://www.slideshare.net/aberkowitz/dataed-online-making-the-case-for-data-governance-11407047
Data-Ed Online: Making the Case for Data GovernanceDATAVERSITY
This document provides an overview of data governance and outlines the keynote presentation by Dr. Peter Aiken on making the case for data governance. The presentation covers data management concepts, defines data governance, explains why it is important, outlines 5 requirements for effective data governance, and discusses data governance frameworks and best practices. The goal is to provide a clear understanding of data governance and how it fits within overall data management.
DataEd Slides: Data Management Best PracticesDATAVERSITY
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This approach combines the DM BoK and the CMMI/DMM, permitting organizations with the opportunity to benefit from the best of both. The approach permits organizations to understand current Data Management practices, strengths to leverage, and remediation opportunities. In a nutshell, it describes what must be done at the programmatic level to achieve better data use.
Similar to Data-Ed Online: Structuring Your Unstructured Data Document & Content Management (20)
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen?
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
1) The document discusses best practices for data protection on Google Cloud, including setting data policies, governing access, classifying sensitive data, controlling access, encryption, secure collaboration, and incident response.
2) It provides examples of how to limit access to data and sensitive information, gain visibility into where sensitive data resides, encrypt data with customer-controlled keys, harden workloads, run workloads confidentially, collaborate securely with untrusted parties, and address cloud security incidents.
3) The key recommendations are to protect data at rest and in use through classification, access controls, encryption, confidential computing; securely share data through techniques like secure multi-party computation; and have an incident response plan to quickly address threats.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
5. Your Documents &
Other Content:
Managing
Unstructured Data
Managing non-tabular Data: Document & Content Management
DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012