This document presents an overview of a reference process model for master data management. It includes an introduction discussing business requirements for master data and challenges in managing master data quality. It also describes the research methodology used to develop an iterative reference process model. The results section provides an overview of the reference process model and discusses its evaluation through three case studies. The conclusion recognizes the model's contribution in explicating the design process for master data management organizations.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Five Things to Consider About Data Mesh and Data GovernanceDATAVERSITY
Data mesh was among the most discussed and controversial enterprise data management topics of 2021. One of the reasons people struggle with data mesh concepts is we still have a lot of open questions that we are not thinking about:
Are you thinking beyond analytics? Are you thinking about all possible stakeholders? Are you thinking about how to be agile? Are you thinking about standardization and policies? Are you thinking about organizational structures and roles?
Join data.world VP of Product Tim Gasper and Principal Scientist Juan Sequeda for an honest, no-bs discussion about data mesh and its role in data governance.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Data modelling is considered a staple in the world of data management. The skill of the data modeler and their knowledge of the business plays a large role in successful Enterprise Information Management across many organizations. Data modeling requires formal accountability, attention to metadata and getting the business heavily involved in data requirement development. These are all traits of solid Data Governance programs.
Join Bob Seiner and a special guest modeler extraordinaire in this month’s installment of Real-World Data Governance to discuss data modeling as a form of data governance. Learn how to use the skillfulness of the data modeler to advance data-as-an-asset and governance agendas while conveying the importance and value of both disciplines.
In this webinar Bob and a special guest will talk about:
•Data Modeling as Art or Science
•Role of Data Modeler in a Governance Program
•Data Modeler Skills as Governance Skills
•Modeling and Governance Best Practices
•Leveraging the Model as a Governance Artifact
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...DATAVERSITY
Achieving a ‘single version of the truth’ is critical to any MDM, DW, or data integration initiative. But have you ever tried to get people to agree on a single definition of “customer”? Or to get Sales, Marketing, and IT to agree on a target audience?
This webinar will discuss how a conceptual data model can be used as a powerful communication tool for data-intensive initiatives. It will cover how to build a high-level data model, how the core concepts in a data model can have significant business impact on an organization, and will provide some easy-to-use templates and guidelines for a step-by-step approach to implementing a conceptual data model in your organization.
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The Importance of Master Data ManagementDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to:
Structure their Data Management processes around these principles
Incorporate Data Quality engineering into the planning of reference and MDM
Understand why MDM is so critical to their organization’s overall data strategy
Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Data Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
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More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Building the Data Lake with Azure Data Factory and Data Lake AnalyticsKhalid Salama
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
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, customer centricity, 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.
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Master Data Management - Aligning Data, Process and Governance Precisely
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Watch the webinar at: http://embt.co/1OMDHK7
Although master data management (MDM) systems have been deployed in numerous industries and organizations, the vision of creating an overall “single source of truth” is beginning to yield to a more pragmatic perspective of providing visibility to shared information about uniquely-identifiable entities within the enterprise. This more mature approach sheds light on some of the potential gaps associated with the typical out-of-the-box data models for customer or product.
In this webinar, David Loshin addresses data modeling for MDM systems, and share insights about:
+ Some of the complexities emerging from reliance on canned master data models
+ Alternatives for revising how master data entities are viewed and consumed within the enterprise
+ How a consumption-oriented engagement process will help the master data modeler devise thoughtful conceptual and logical representations of shared master data
He also discusses how these different ways of looking at master data modeling will help reduce complexity for master data adoption, system interoperability, and legacy migration.
Learn more about ER/Studio at http://www.embarcadero.com/products/er-studio
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Data modelling is considered a staple in the world of data management. The skill of the data modeler and their knowledge of the business plays a large role in successful Enterprise Information Management across many organizations. Data modeling requires formal accountability, attention to metadata and getting the business heavily involved in data requirement development. These are all traits of solid Data Governance programs.
Join Bob Seiner and a special guest modeler extraordinaire in this month’s installment of Real-World Data Governance to discuss data modeling as a form of data governance. Learn how to use the skillfulness of the data modeler to advance data-as-an-asset and governance agendas while conveying the importance and value of both disciplines.
In this webinar Bob and a special guest will talk about:
•Data Modeling as Art or Science
•Role of Data Modeler in a Governance Program
•Data Modeler Skills as Governance Skills
•Modeling and Governance Best Practices
•Leveraging the Model as a Governance Artifact
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...DATAVERSITY
Achieving a ‘single version of the truth’ is critical to any MDM, DW, or data integration initiative. But have you ever tried to get people to agree on a single definition of “customer”? Or to get Sales, Marketing, and IT to agree on a target audience?
This webinar will discuss how a conceptual data model can be used as a powerful communication tool for data-intensive initiatives. It will cover how to build a high-level data model, how the core concepts in a data model can have significant business impact on an organization, and will provide some easy-to-use templates and guidelines for a step-by-step approach to implementing a conceptual data model in your organization.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
The Importance of Master Data ManagementDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and Master Data Management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI). To that end, attendees of this webinar will learn how to:
Structure their Data Management processes around these principles
Incorporate Data Quality engineering into the planning of reference and MDM
Understand why MDM is so critical to their organization’s overall data strategy
Discuss foundational MDM concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Data Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Building the Data Lake with Azure Data Factory and Data Lake AnalyticsKhalid Salama
In essence, a data lake is commodity distributed file system that acts as a repository to hold raw data file extracts of all the enterprise source systems, so that it can serve the data management and analytics needs of the business. A data lake system provides means to ingest data, perform scalable big data processing, and serve information, in addition to manage, monitor and secure the it environment. In these slide, we discuss building data lakes using Azure Data Factory and Data Lake Analytics. We delve into the architecture if the data lake and explore its various components. We also describe the various data ingestion scenarios and considerations. We introduce the Azure Data Lake Store, then we discuss how to build Azure Data Factory pipeline to ingest the data lake. After that, we move into big data processing using Data Lake Analytics, and we delve into U-SQL.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
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, customer centricity, 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.
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
Product-thinking is making a big impact in the data world with the rise of Data Products, Data Product Managers, data mesh, and treating “Data as a Product.” But Honest, No-BS: What is a Data Product? And what key questions should we ask ourselves while developing them? Tim Gasper (VP of Product, data.world), will walk through the Data Product ABCs as a way to make treating data as a product way simpler: Accountability, Boundaries, Contracts and Expectations, Downstream Consumers, and Explicit Knowledge.
Master Data Management - Aligning Data, Process and Governance Precisely
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Watch the webinar at: http://embt.co/1OMDHK7
Although master data management (MDM) systems have been deployed in numerous industries and organizations, the vision of creating an overall “single source of truth” is beginning to yield to a more pragmatic perspective of providing visibility to shared information about uniquely-identifiable entities within the enterprise. This more mature approach sheds light on some of the potential gaps associated with the typical out-of-the-box data models for customer or product.
In this webinar, David Loshin addresses data modeling for MDM systems, and share insights about:
+ Some of the complexities emerging from reliance on canned master data models
+ Alternatives for revising how master data entities are viewed and consumed within the enterprise
+ How a consumption-oriented engagement process will help the master data modeler devise thoughtful conceptual and logical representations of shared master data
He also discusses how these different ways of looking at master data modeling will help reduce complexity for master data adoption, system interoperability, and legacy migration.
Learn more about ER/Studio at http://www.embarcadero.com/products/er-studio
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
Gartner: Seven Building Blocks of Master Data ManagementGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm.
Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations.
Data modelling for the business half day workshop presented at the Enterprise Data & Business Intelligence conference in London on November 3rd 2014
chris.bradley@dmadvisors.co.uk
The business dimensional life cycle. Summarized from the second chapter of 'The Data Warehouse Lifecyle Toolkit : Expert Methods for Designing, Developing, and Deploying Data Warehouses' by Ralph Kimball
Manager in the filed of BPMA, providing services in below areas:
- Data Warehousing
- Business Intelligence
- SDLC (Waterfall & Agile)
- Business Analysis
- Project Management
- MIS & Reporting
- CRM development
- Artificial Intelligence
- Production Support
- Data Quality & Governance framework
- System Integration
Skill Set:
Sql, SAS, Qlik sense, SAP BO
IRM Data Governance Conference February 2009, London. Presentation given on the Data Governance challenges being faced by BP and the approaches to address them.
Business Models in the Data Economy: A Case Study from the Business Partner D...Boris Otto
Data management seems to experience a renaissance today. One particular trend in the so-called data economy has been the emergence of business models based on the provision of high-quality data. In this context, the paper
examines business models of business partner data providers. The paper explores as to how and why these business models differ. Based on a study of six cases, the paper identifies three different business model patterns. A resource-based view is taken to explore the details of these patterns. Furthermore, the paper develops a set of propositions that help understand why the different business models evolved and how they may develop in the future. Finally, the paper discusses the ongoing market transformation process indicating a shift from traditional value chains toward value networks—a change which, if it is sustainable, would seriously threaten the business models of well-established data providers, such as Dun & Bradstreet, for example.
Building an Effective & Extensible Data & Analytics Operating ModelCognizant
Building an effective and scalable operating model requires a strong basis in data and analytics management. Creating such an operating model is a step-by-step process, as outlined here.
Suggest an intelligent framework for building business process management [ p...ijseajournal
As companies enter into the digital world, information technology is playing a major role in bringing
process improvements to the forefront of business management. In the recent decades, many organizations
have struggled to redesign and improve their business processes to reduce their total cost. The main
contribution of this research study is to propose an intelligent framework that possesses the ability to
employ a database of best practices, business standards, and business activity history in order to permit the
manager to analyze and improve the design of the business processes.
In addition, the other objective of this research is to build a business process or workflow directly from its
process design logic in order to enable rapid process development and deployment. This procedure
requires some technical improvements of the business design, as it is mainly based on building the business
process using Microsoft Office Visio, which communicates the defined business process to the business
process management engine.
Turning your Excel Business Process Workflows into an Automated Business Inte...OAUGNJ
Many organizations have evolved key internal business processes built on top of Microsoft Excel. These cross-functional workflows involve several organizational units responsible for collecting business system transactions, modifying this raw data, consolidating, transforming, pivoting and preparing data into a published set of Reports & Graphs – all in MS Excel. Such workflows are a burden to organizations – not repeatable, costly, time-consuming, inflexible and hard to scale, and evolve to become more complex over time. Business critical processes such as financial analysis, operational analysis and revenue analysis are often supported this way. Attempting to replace such systems can be quite daunting and a barrier to replace. The goal of this session is to present an easy to understand methodology and use cases to demonstrate how to move from an operational workflow in Excel to truly automated Business Intelligence.
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Dieser Vortrag motiviert Datensouveränität in Produktions- und Logistiknetzwerken. Datensouveränität ist die Fähigkeit zur Selbstbestimmung über das Wirtschaftsgut Daten - auch beim Austauschen der Daten in Unternehmensnetzwerken. Der Vortrag führt in die Architektur des Industrial Data Space ein, der einen virtuellen Datenraum für den souveränen Datenaustausch bildet. Der Vortrag schließt mit Anwendungsbeispielen und einer Diskussion des Beitrags für die Wissenschaft und die Praxis.
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This presentation (in German) gives an overview about how Fraunhofer ISST supports digital transformation projects in various industries. It motivates Digital Business Engineering as a methodological framework and show-cases typical applications. The presentation was given at the Fraunhofer ISST 25th anniversary event at Zeche Zollern in Dortmund.
Der Vortrag leitet am Beispiel der Automobilindustrie in die wesentlichen Entwicklungen zur Digitalisierung von Industriebetrieben ein und stellt dabei die besondere Rolle der Daten und eines wirksamen Datenmanagements heraus. Abschließend gibt der Vortrag Empfehlungen zum Management der Digitalen Transformation.
Data Sovereignty - Call for an International EffortBoris Otto
This presentation will be given at the Digitisting Manufacturing in the G20 Conference on March 16, 2017, in Berlin, in the context of the workshop "Data Sovereignty in Global Value Networks".
This presentation was held at the 2nd Internet of Manufacturing Conference on February 7, 2017, in Munich, Germany. It addresses the need of a new kind of data management to cope with the requirements digital scenarios pose on the industrial enterprise. Motivated by examples, the talk outlines design principles for smart data management and concludes with two leading examples, namely the Industrial Data Space initiative and the Corporate Data League.
Industrial Data Space: Referenzarchitekturmodell für die DigitalisierungBoris Otto
Diese Präsentation auf der VDI Industrie 4.0 Tagung am 25.1.2017 in Düsseldorf gibt ein Update der Entwicklungen des Industrial Data Space. Schwerpunkte sind Datensouveränität, der Industrial Data Space als Bindeglied zwischen IoT-Cloud-Plattformen sowie der Referenz-Use-Case Logistik.
Industrial Data Space: Digitale Souveränität über DatenBoris Otto
Der Vortrag führt in Grundbegriffe der Datenökonomie ein und macht einen Vorschlag zur Definition des Begriffs der digitalen Souveränität. Zudem arbeitet der Vortrag heraus, welchen wichtigen Beitrag der Industrial Data Space zur Wahrung der digitalen Souveränität leistet.
The Industrial Data Space aims at establishing a virtual data space in which partners in business ecosystems can securely exchange and easily link their data assets. The presentation puts the Industrial Data Space in the context of recent developments in the area of Smart Service Welt and Industrie 4.0 and sketches a reference architecture model and functional software components. Furthermore, the presentation introduces the Industrial Data Space Association which institutionalizes the user requirements and drives standardization. The presentation was given at the Industry 4.0 session at MACH 2016 on April 14, 2016, in Birmingham, UK.
Industrial Data Space: Digital Sovereignty for Industry 4.0 and Smart ServicesBoris Otto
The presentation takes a look on the digitization of the industrial enterprise, linking Industry 4.0 and Smart Service activities. It points out the crucial role of data for future business success and positions the Industrial Data Space as a collaborative approach to securely exchange and easily link data within business ecosystems. The presentation was given at the Manufacturing Analytics workshop organized by the Insitute of Manufacturing at the University of Cambridge on February 1st, 2016.
Industrial Data Space: Referenzarchitektur für Data Supply ChainsBoris Otto
Dieser Vortrag stellt den Industrial Data Space als Referenz-Architektur für Data Supply Chains vor. Data Supply Chains sind vernetzte, unternehmensübergreifende Datenflüsse. Data Supply Chains sind Voraussetzung um hybride Leistungsangebote (Smart Services) einerseits und digitalisierte Leistungserstellung (Industrie 4.0) andererseits zu verbinden. Durch die effektive und effiziente Bewirtschaftung von Data Supply Chains erhöhen Unternehmen ihre Wettbewerbsfähigkeit. Der Industrial Data Space liefert hierzu die Blaupause, als Referenzarchitektur für die Datenökonomie.
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buy old yahoo accounts buy yahoo accountsSusan Laney
As a business owner, I understand the importance of having a strong online presence and leveraging various digital platforms to reach and engage with your target audience. One often overlooked yet highly valuable asset in this regard is the humble Yahoo account. While many may perceive Yahoo as a relic of the past, the truth is that these accounts still hold immense potential for businesses of all sizes.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Company Valuation webinar series - Tuesday, 4 June 2024FelixPerez547899
This session provided an update as to the latest valuation data in the UK and then delved into a discussion on the upcoming election and the impacts on valuation. We finished, as always with a Q&A
An introduction to the cryptocurrency investment platform Binance Savings.Any kyc Account
Learn how to use Binance Savings to expand your bitcoin holdings. Discover how to maximize your earnings on one of the most reliable cryptocurrency exchange platforms, as well as how to earn interest on your cryptocurrency holdings and the various savings choices available.
Top mailing list providers in the USA.pptxJeremyPeirce1
Discover the top mailing list providers in the USA, offering targeted lists, segmentation, and analytics to optimize your marketing campaigns and drive engagement.
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs