IT-relaterad tjänstekatalog i kommunen

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Björn Bergqvist

Exempel på tjänsteleverans (Infrastruktur)
-färgerna visar på etableringsgrad

Tjänstekatalog i relation med kundportfölj

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Santander's Data Transformation

Umran Rafi

Data Governance

Rob Lux

Business Architecture Foundations

Mohamed Zakarya Abdelgawad

Welcome to The Chief Data Officer Agenda, a DATAVERSITY monthly webinar focused on the emerging priorities of the Chief Data Officer (CDO). What issues are CDOs facing now, and what should be on their Agenda. The webinar series is moderated by DATAVERSITY CEO and Founder, Tony Shaw, who will be joined each month by guest experts to discuss the requirements and demands on the burgeoning CDO role. This month in the series: The value proposition of enterprise information management is founded on Information being treated as an Asset. Information management professionals concur, but CxOs will say "So what?" In most organizations, they are both right! The conflict starts with one group thinking metaphorically, and the other literally. CDOs know that “Information asset” needs to be more than a metaphor…it has to be actionable. When you’re in charge of the application and value of data, how do you measure that? How do you measure progress? What types of metrics are there and which ones actually work? There is a lot more to measuring the value of information than common ROI. This presentation will give you some starting points for real information asset management and information economics. You’ll learn some of the techniques being used successfully today, and considerations for quantifying the value and progress of information management. There is a means of reconciliation between the metaphors and reality, and this talk will outline a vision for the future, but with practical steps to help you get there.

The Chief Data Officer Agenda: Metrics for Information and Data Management

DATAVERSITY

(Note: This is a very dated version of this popular deck, as SlideShare does not provide authors with a mechanism to update their documents. If interested in the latest version, feel free to message me on LinkedIn or at wweinmeyer@gmail.com. Also, feel free to ask SlideShare to bring back the ability to update posted documents.) A discussion of the fundamentals you need to nail in your architecture practice: - Architecture vs. Design - Conceptual vs. Logical vs. Physical architecture - Viewpoint Frameworks - Architecture Domains - Architecture Tiers You are free to use/copy this information but if you do so, please include an acknowledgement

An introduction to fundamental architecture concepts

wweinmeyer79

Use a Service Taxonomy to Organize and Manage Your IT Services ! What services do we offer? How do we organize them? How can we make them "customer centric?” What is a good starting point? Successful IT Service Catalogs have well organized services. The Services Taxonomy, or framework is the key to organizing and understanding your services well. Please join us to learn how to build a good service taxonomy in 4 logical steps, as well as 3 key mistakes to avoid. In addition to a demo of our prebuilt service taxonomy, we will demonstrate these concepts in our constantly evolving view of a very advanced Employee Self-Service Catalog & Portal, built on ServiceNow technologies. Recording with demo available at http://content.evergreensys.com/service-taxonomy-webinar-slides-manage-it-services

What is a Service Taxonomy and Why Do I Need One?

Evergreen Systems

Best Practices for Implementing a Service Catalog and Enhanced ITSM

hdicapitalarea

Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.

DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...

DATAVERSITY

How to Build & Sustain a Data Governance Operating Model

DATUM LLC

A Business Intelligence requirement gathering checklist

Madhumita Mantri

Your Challenge Organizations have to adapt to a growing number of trends, putting increased pressure on IT to move at the same speed as the business. The business, seeing that IT is slower to react, looks to external solutions to address its challenges and capitalize on opportunities. IT and business leaders don’t have a clear and unified understanding or definition of an operating model. Our Advice Critical Insight The IT operating model is not a static entity and should evolve according to changing business needs. However, business needs are diverse, and the IT organization must recognize that the business includes groups that consume technology in different patterns. The IT operating model needs to support and enable multiple groups, while continuously adapting to changing business conditions. Impact and Result Determine how each technology consumer group interacts with IT. Use consumer experience maps to determine what kind of services consumer groups use and if there are opportunities to improve the delivery of those services. Identify how changing business conditions will affect the consumption of technology services. Classify your consumers based on business uncertainty and reliance on IT to plan for the future delivery of services. Optimize the IT operating model. Create a target IT operating model based on the gathered information about technology service consumers. Select different implementations of common operating model elements: governance, sourcing, process, and structure.

Optimize the IT Operating Model

Info-Tech Research Group

10 Worst Practices in Master Data Management

ibi

IT4IT - The Full Story for Digital Transformation - Part 2

Mohamed Zakarya Abdelgawad

IT Service Catalog Taxonomy Essentials

Evergreen Systems

7 Steps to Creating an Effective ITSM Service Catalog

Cherwell Software

IT4IT Overview (A new standard for IT management)

Charles Betz

Frontit seminarium: "Om COBIT, PM3 eller ITIL är svaret..."- Malmö 22 oktober

Frontit

The data architecture of solutions is frequently not given the attention it deserves or needs. Frequently, too little attention is paid to designing and specifying the data architecture within individual solutions and their constituent components. This is due to the behaviours of both solution architects ad data architects. Solution architecture tends to concern itself with functional, technology and software components of the solution Data architecture tends not to get involved with the data aspects of technology solutions, leaving a data architecture gap. Combined with the gap where data architecture tends not to get involved with the data aspects of technology solutions, there is also frequently a solution architecture data gap. Solution architecture also frequently omits the detail of data aspects of solutions leading to a solution data architecture gap. These gaps result in a data blind spot for the organisation. Data architecture tends to concern itself with post-individual solutions. Data architecture needs to shift left into the domain of solutions and their data and more actively engage with the data dimensions of individual solutions. Data architecture can provide the lead in sealing these data gaps through a shift-left of its scope and activities as well providing standards and common data tooling for solution data architecture The objective of data design for solutions is the same as that for overall solution design: • To capture sufficient information to enable the solution design to be implemented • To unambiguously define the data requirements of the solution and to confirm and agree those requirements with the target solution consumers • To ensure that the implemented solution meets the requirements of the solution consumers and that no deviations have taken place during the solution implementation journey Solution data architecture avoids problems with solution operation and use: • Poor and inconsistent data quality • Poor performance, throughput, response times and scalability • Poorly designed data structures can lead to long data update times leading to long response times, affecting solution usability, loss of productivity and transaction abandonment • Poor reporting and analysis • Poor data integration • Poor solution serviceability and maintainability • Manual workarounds for data integration, data extract for reporting and analysis Data-design-related solution problems frequently become evident and manifest themselves only after the solution goes live. The benefits of solution data architecture are not always evident initially.

Data Architecture for Solutions.pdf

Alan McSweeney

The new Archimate 3.1 has improved the strategy layer with major modeling objects related to value analysis: value stream and capability. These objects are linked and answer major questions : - [VALUE STREAM] What value do we deliver to customers ? What value do we want to deliver to customers ? This is the enterprise business model. - [CAPABILITY] What operational model do we need to deliver value ? The capability model describes the operational model required to deliver value to customers. You cannot succeed to transform a business model, enterprise activities without considering Value Stream & Capability analysis. Technology considerations are necessary but not sufficient. Feel free to contact if you wish to get more support with your transformation projet.

Value analysis with Value Stream and Capability modeling

COMPETENSIS

Digital Operating Model & IT4IT

David Favelle

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