Data Management: Introduction


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Bas van Gils
Posted by Bas van Gils on May 6, 2013

Enterprise Architecture

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The topic of Data Management (DM) is increasingly important for many organizations. Much has been researched and written in this field, both from a business and a technical perspective. For example:

  • The Data Asset by Tony Fisher presents a strong argument for considering data from a business perspective and argues the case that quality data is quintessential for sustainable business success
  • Master Data Management and The Practitioner's Guide to Data Quality Improvement by David Loshin provide an excellent technology independent overview of several key aspects of data management with attention for business and technology concerns
  • The DAMA DMBOK is considered to be the most comprehensive overview of the field of data management in existence

It is increasingly recognized that enterprise architecture (EA) models are a valuable tool in this field. At the recent MDM/DG summit, hosted by IRM UK, (see also our previous blogpost) it was agreed that:

  • Architects and Data Management Professionals often talk to the same stakeholders
  • Share a common mindset, tools,and models
  • Tackle similar issues

Given BiZZdesign’s proposition in this field with ArchiMate and Architect, it makes sense to investigate how ArchiMate can be leveraged in the field of Data Management – at least from a modeling perspective. Obviously, the Data Management -space covers much more than models but that is beyond the scopeof this series. This subject is too large to tackle in one go though, so we follow an incremental approach and tackle various aspects one by one, as depicted in the figure below:

Data management. Incremental approach

For each aspect we will give a short introduction describing context and relevance, after which we explore the relevant modeling concepts and how they could be translated to ArchiMate:

  • Subject Area & objects: an overview of how the information landscape can be subdivided into coherent subject areas, which can be decomposed into business entities
  • Realization of Entities in applications: entities represent business concepts, and may be realized by some IT system. In this post we will show how to model this
  • Stewardship: a steward is the person responsible for the quality of information, i.e. the entities that are part of a subject area
  • Mastering data: many organizations have dispersed data about key entities. It is not uncommon for these versions to mismatch. Master Data Management (MDM) is about creating a master record for these key entities
  • Meta Data: meta data is often defined as data about data. This is a broad discipline which covers various topics including  business- and technical metadata
  • Business Intelligence: is a discipline in its own right. Loosely defined it is the discipline that is concerned with providing management with the ‘intelligence’ necessary to run the business. It is often associated with such things as an Enterprise Data Warehouse.
  • We end the series with:an overview of the relevant concepts from the ArchiMate metamodel and provide an idea of what advanced / custom visualization in this context would look like.

Stay tuned for the next posting in which we dive into the “meat” of the series. If you have a question or suggestion, please leave a comment.

Forrester Wave Enterprise Architecture 2017

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