Open Framework, Information Management Strategy & Collaborative Governance | Data & Social Methodology - MIKE2.0 Methodology
Wiki Home
Collapse Expand Close

Collapse Expand Close

To join, please contact us.

Improve MIKE 2.0
Collapse Expand Close
Need somewhere to start? How about the most wanted pages; or the pages we know need more work; or even the stub that somebody else has started, but hasn't been able to finish. Or create a ticket for any issues you have found.

Enterprise Data Management Strategy Solution Offering

From MIKE2.0 Methodology

Jump to: navigation, search
Hv4.jpg This Solution Offering is provided through the MIKE2.0 Methodology. It receives full coverage within the Overall Implementation Guide and SAFE Architecture and contains a number of Supporting Assets. It has been defined inline with the appropriate Solution Offering Creation Guide and has been peer reviewed. It may have some minor issues with Activities or lack depth. In summary, the Solution Offering can be used but it still may have some issues.
A Creation Guide exists that can be used to help complete this article. Contributors should reference this guide to help complete the article.



The Enterprise Data Management (EDM) Strategy Solution Offering provides a method for an organization to define its strategic approach to EDM and how it will be implemented. The offering provides recommendations related to a contemporary set of EDM technologies, revisions to organizational structures, necessary staff skill sets and governance process improvements needed for Enterprise Data Management. This is done through a Blueprinting/Roadmap-based approach that starts with a current-state assessment, uses architecture best practices and offers recommendations on how to implement the solution through an overall programme. Although it also includes more tactical options for delivery within the strategic framework, it is a solution offering that is focused on large-scale change in the organisation.

Executive Summary

Increasingly federated and integrated systems mean that information management issues are more complex than ever before. As organisations move towards a focus on Information Development, a comprehensive strategy is required to shift from work practices that are often siloed within business units and focused more towards function and infrastructure. This comprehensive strategy involves starting with the overall business vision and defining an approach that is inclusive of people, process, organisation and technology. This top-down style is often necessary as each of these areas requires a fundamental re-design to move towards an Information Development Organisation. In MIKE2.0, this is referred to as a Blueprinting approach to a Data Management Strategy.

Whilst the Blueprinting approach is the most comprehensive – it isn’t always the best way to start. Some organisations find it more effective to start with more of a bottom-up approach. Whereas the top-down approach will eventually be required to develop the comprehensive approach, starting on a small, focused initiative that assesses the current-state is oftentimes the best way to build momentum for a larger programme. In the bottom-up approach the focus is on data profiling, to build a quantitative understanding of the data quality issues in the current-state environment. In MIKE2.0 this is referred to as an Investigative approach to Data Management Strategy.

A third approach may be classified as starting “in the middle”. Starting in the middle involves building a reference model of the current-state environment that often starts with a data dictionary. This can then be extended to a more comprehensive metadata management environment that tracks information such as data owners, data stewards and mapping rules. Data profiling can assist in populating some of the information into this repository. In MIKE2.0 this is referred to as a Metadata-driven approach to a Data Management Strategy.

The MIKE2.0 Solution Offering for an Enterprise Data Management Strategy explores the techniques in each of these areas, and compares and contrasts the respective benefits.

The Executive Overview on EDM Strategy provides an introductory presentation on this approach.

Solution Offering Purpose

This is a Core Solution Offering. Core Solution Offerings bring together all assets in MIKE2.0 relevant to solving a specific business and technology problem. Many of these assets may already exist and as the suite is built out over time, assets can be progressively added to an Offering.

A Core Solution Offering contains all the elements required to define and deliver a go-to-market offering. It can use a combination of open, shared and private assets.

Solution Offering Relationship Overview

The EDM Strategy Solution Offering is part of the Architecture, Strategy and Governance Solution Group

The MIKE2.0 Enterprise Data Management Strategy Solution Offering describes how the Activities and Supporting Assets of the MIKE2.0 Methodology can be used to deliver a comprehensive strategy for Information Management.

MIKE2.0 Solution Offerings provide a detailed and holistic way of addressing specific problems. MIKE2.0 Solutions can be mapped directly to the Phases and Activities of the MIKE2.0 Overall Implementation Guide, providing additional content to help understand the overall approach.

The MIKE2.0 Overall Implementation Guide explains the relationships between the Phases, Activities and Tasks of the overall methodology as well as how the Supporting Assets tie to the overall Methodology and MIKE2.0 Solutions.

Users of the MIKE2.0 Methodology should always start with the Overall Implementation Guide and the MIKE2.0 Usage Model as a starting point for projects.

Solution Offering Definition

This Solution Offering provide 3 different techniques for defining an MIKE2.0 Enterprise Data Management Strategy. Each of these techniques is valid and best applied in different situations.

The Blueprinting Approach

The comprehensive Blueprinting approach that goes across people, process, organisation and technology with the aim of forming a mature Information Development Organisation is a significant undertaking. The key objectives of this approach are as follows:

Building an EDM Strategy that can accommodate:

  • Continuous development through increment-based delivery
  • Changing business requirements over a multi-year programme
  • Delivery of tactical projects in the context of long-term strategic initiatives
  • Progressive changes to technology with vendor releases

Aligning the EDM strategy with other strategic initiatives in order to:

  • Provide deliverables with consistent definitions of “blueprints”, “roadmaps”, and “frameworks”
  • Ensure consistent leveling – re-factor deliverables that are too high-level or too detailed
  • Make sure the strategy is in touch with organisational culture and their ability to change
  • Define a delivery approach that allows for parallel activities and avoids serial bottlenecks
  • Ensure delivery is focused on high-risk areas of Data Management
  • Improve Operational Efficiency through reuse of common work products

Building an improved competency in Data Management across the organisation in order do:

  • Deliver through a systematic process that you follow from a data management perspective – within IT, the overall business and across departments
  • Integrate Data Management performance metrics into all your activities
  • Build a framework to reuse content at a detailed technical level
  • Provide solutions that integrate at the conceptual, logical and physical level to be insulated from vendor changes

Defining this strategy for Information Development should complement any strategy initiatives related to infrastructure, integration and applications and must be driven from an overall business strategy.

The Metadata-Driven Approach

The goal of the Metadata-Driven Approach is to build a reference model of the organisation that includes not just data elements, but the complete enterprise information management environment. This means that common data definitions, transformation rules, governance standards. Content should be stored in a structured form, through either a bespoke or vendor-developed metadata repository. This model then serves as a reference model for future information management initiatives. The goal is that this reference model becomes physically implemented and not only a point of reference.

The Investigative Approach

Data Profiling can be conducted to quantitatively understand data quality issue of the current environment. As the current-state is always a limitation to what can be done in the future when it comes to data, Data Profiling can provide a valuable way to start defining the strategy.

The benefit to Data Profiling is that it helps remove the uncertainty and assumptions regarding the current information environment to allow for fact-based decisions to be made regarding the information management strategy based on the data that is available.

Data Profiling often uses a tools-based approach that enables the initial establishment of standards and initial formulation of metadata. It works by parsing and analysing free-form and single domain fields, and determining the number and frequency of unique values and classifying or assigning a business meaning to each occurrence of a value within a field. It can also be used to determine referential integrity issues that exist within systems and between systems.

Relationship to Solution Capabilities

Relationship to Enterprise Views

Areas of focus for a comprehensive Data Management Strategy

An Enterprise Data Management Strategy is focused primarily on the area of Information Development, although it should complement a Business Strategy and Infrastructure Strategy. A comprehensive Data Management Strategy should be focused across people, process, organisation and technology and formulate an implementable action plan for each of the areas. The more focused approaches are narrower in their overall scope but are still primarily focused on the area of Information Development.

Mapping to the Information Governance Framework

The Information Governance Solution Offering is required across all Solution Offerings. For this offering it is particularly important that the governance models focus on process, standards, architecture and organisational structure that is most effective for managing content across the enterprise.

Mapping to the SAFE Architecture Framework

Development of a comprehensive Data Management Strategy will include varying components from the SAFE Architecture, depending on the scope of the initiative.

The Blueprinting approach to an data management strategy will likely determine that a number of components from the SAFE Architecture will be required in the future-state architecture. It is important that foundation capabilities be in place first, before more sophisticated capabilities such as Services Oriented Architecture and that Enabling Technologies be used to smooth the transition to these most advanced techniques. A number of artifacts from the SAFE Architecture can help define the component capabilities as part of comprehensive approach.

The key architectural component for the Metadata-driven approach is some form of repository for storing artifacts and supporting modelling tools to create data models and meta-models. There are vendor offerings in this space and many organisations build bespoke repository-based solutions.

In the Investigative approach, the most relevant aspect of the SAFE Architecture is the Data Profiling component. The output of this approach can go into a metadata repository or form the analysis for loading data into a target environment. It may also form the initial step in a data re-engineering initiative.

Mapping to the Overall Implementation Guide

Depending on the type of strategy that is being defined, different activities from MIKE2.0 will be required. Shown below is a high-level description of the key activities for defining an Enterprise Data Management Strategy.

Blueprint-Based Information Management Strategy

Business Assessment and Strategy Definition Blueprint (Phase 1)

A comprehensive Enterprise Data Management strategy means developing a vision that impacts people, process, organisation and technology. All activities from the Business Blueprint phase of MIKE2.0 will be required to define this strategic approach. In a large, complex organisation it will require engagement with a large number of stakeholders and may result in significant organisational change.

In the Business Blueprint phase, the focus is on developing an initial information development strategy that is aligned to the specific set of business requirements, many of which are driven from the application development stream. The SAFE Architecture is used as a starting point to define the strategic conceptual architecture at the component level and a set of high level solution architecture options.

Most organisations will require a large degree of structural change to move to a mature Information Development organisation. It is starting in Phase 1 that we want to begin to “re-balance” the Enterprise to take more of a focus on the development of information. The Data Governance activities that are first initiated through the use of IM QuickScan are important to start early in the Transformation programme. As part of the MIKE2.0 methodology, the Information Development organisation is established to complement more traditional organisational models around application development and infrastructure.

Technology Assessment and Selection Blueprint (Phase 2)

All activities from the Technology Blueprint phase of MIKE2.0 will be required to define the strategic approach to Information Management. Implementation of the Information Management strategy will also involve a very large number of new technologies. In phase 2 of MIKE2.0, a diligent approach is applied to establish the technology requirements at the level required to make strategic product decisions. Once inline with the overall business case, technology selection can then take place during this phase.

The establishment of functional and non-functional requirements not only leads to the selection of technologies, but also to how it will be implemented. In this phase, the overall SDLC strategy (standards, testing and development environments) that will support development are put in place. This is explained in the MIKE2.0 Overall Implementation Guide and there are a number of Supporting Assets in this area. These technology standards are an important part of the overall Information Management strategy and will apply across the scope of the enterprise for which the strategy was conducted.

Also in phase 2, the Data Governance activities move from establishing the initial organisation to determining how it will function. The strategic set of standards, policies and procedures for the overall Information Development organisation are first established during this phase. This Information Development Organisation has established reporting lines into the other aspects of the organisation from a management, architecture and delivery perspective.

Metadata-Driven Information Management Strategy

Defining a Metadata-Driven Data Management will involve a number of techniques across the first 3 phases of the MIKE2.0 Methodology. The key activities for this approach are can be difficult to follow as they cross aspects of the MIKE2.0 Overall Implementation Guide is a non-sequential order. In summary, first build a data dictionary, then to store other metadata artefacts and then continue to populate this model with different artefacts.

Metadata Driven Architecture

MIKE2.0 aims to move to a Metadata-Driven Architecture by getting metadata management practices in place from the onset. As part of the initial strategy it can valuable to build a prototype Metadata Repository and define an initial set of metadata management standards. Some of the content that may go into this repository includes information defined in the following activities:

Database Design

Defining a Data Dictionary should be a standard aspect of any database design. In reality, it is a practice that is often not strictly followed. The Metadata-Driven approach to an Information Management Strategy often involves re-visiting existing data models and the enhancing database design with a more robust data dictionary encompassing domain values, term definitions and relevant physicalistion information.

Data Governance Policies

Data Governance Policies are derived from the Policies and Guidelines developed in Phase 1. It is important to define these policies as part of a reference approach as they are a natural process of understanding the reference current-state. The high-level policies impact the definition of Data Standards, in particular around data security, normalisation and auditing practices.

Data Standards

Data Standards should be established before the modelling team begins any detailed work. Some form of existing standards can often be used as a starting point. This will make sure that the team is working to a common set of techniques and conventions. Data Standards should be straightforward and follow a common set of best practices. Oftentimes data standards will already exist that can be leveraged.

Enterprise Information Architecture

An Enterprise Information Architecture is the final product of the Metadata-Driven Information Management Strategy. MIKE2.0 takes the approach of building out the Enterprise Information Architecture over time for each new increment that is implemented as part of the overall programme. The scope for building the Enterprise Information Architecture is defined by the in-scope Key Data Elements (KDEs). The enterprise data model is the major part of this overall information architecture.

Investigative Approach to Information Management Strategy

There are 2 main activities to conduct as part of a bottom-up Information Management Strategy: determination of Data Governance Metrics to set some level of business targets for profiling and the actual profiling itself. There may be a number of other activities for scoping and setting up the infrastructure environment that can be referenced in the MIKE2.0 Solution for Data Investigation and Re-Engineering.

Data Governance Metrics

Data Governance Metrics provide the information quality objectives that the organisation plans to achieve. As part of an Information Management strategy the initial targets should be set as well as which areas will be profiled. Not all metrics can be determined through profiling, some will require an interviewing based assessment and architectural review.

Data Profiling

Data Profiling focuses on conducting an assessment of actual data and data structures and is focused on measuring data integrity, consistency, completeness and validity. As part of this process, data quality issues are identified individual attribute level, at the table-level and between tables. Metadata such as business rules and mapping rules are identified as a by-product of this process. As the result of data profiling, fact-based decisions can now be made regarding the Information Management Strategy.

Mapping to Supporting Assets

Logical Architecture, Design and Development Best Practices

A number of artefacts help support this Solution Offering: For the Blueprinting approach, key assets include:

For the Metadata-driven approach which builds an Enterprise Information Model, the following can be used

  • Reference Metadata Model to check that the correct information is being captured as part of the ,meta-modelling process
  • The MIKE2.0 Data Modelling Solution brings together a number of artefacts that may prove useful in this area
  • The MIKE2.0 Metadata Management Solution brings together a number of artefacts that may prove useful in this area

For the Investigative approach, the best point of reference is the MIKE2.0 Data Investigation and Re-Engineering Solution, which brings together tool-specific and logical techniques for data profiling.

Product-Specific Implementation Techniques

Product Selection Criteria

An Information Management Strategy is often conducted to select technologies, although use of vendor tools can act as benefit as part of this process. Capturing artifacts into an Enterprise Modelling tool is the preferred approach as part of the MIKE2.0 Methodology.

Estimating Project Complexity

There are a number of variables that can impact scoping in a top-down Enterprise Data Management Strategy. For a large organisation, timelines can be significant to get full coordination and coverage although the goal should be to deliver meaningful aspects of the strategy in 3 month increments. Key variables include:

  1. Complexity of the business problem
  2. Depth of current-state analysis required
  3. Scope of systems and complexity of the environment
  4. Level of detail needed around programme planning
  5. Level of financial analysis required to define the project Business Case
  6. Organisational review requirements such as skill sets, organisational structure
  7. Whether any of the proposed activities have already been completed
  8. Availability of Subject Matter Experts and level of system documentation
  9. Vendor Selection requirements
  10. Detail around detailed Data Governance activities (standards, policies)

Scoping in a “Phase 0” can be beneficial to review variables.

Relationships to other Solution Offerings

This activity is used by organisations looking to define a data management strategy at an Enterprise level. Therefore, many solution offerings make use of the work. As an example, this project may be conducted at the group level of a large organisation to define the overall data management approach. The organisation may then break work into multiple workstreams to do the implementation. In some cases these specific workstreams may re-initiate strategy activities on in a more focused area (e.g. specific strategy activities for Data Warehousing but it is this overall strategy that brings the workstreams together.

Extending the Open Methodology through Solution Offerings

At this stage all core activities are envisaged to be in place in relation to this offering.

Wiki Contributors
Collapse Expand Close

View more contributors