Introduction

The requirements for data as well as for data management (DM), are interpreted through data architecture. This interpretation defines the requirements to design the physical data consumed, produced and provisioned by the business process. Data architecture is a bridge between the requirements for data of the business process and the physical execution of that data in technology infrastructure.

The efficient and effective movement of data is critical to business operations. Technology architecture determines how data, tools and platforms operate in collaboration to satisfy business requirements. The proper alignment of these components dictates application efficiency and system processing speed. This enables organizations to control costs and achieve infrastructure scalability and elasticity which are characteristic of an organization that is designed for long-term implementation success.

The roadmaps to achieve architecture integration across business, data and technology need to be aligned on a path to the target-state. The roadmaps define the governance and controls that are needed to ensure compliance across the organization.

Definition

The Data & Technology Architecture (TA) component is a set of capabilities to align the architectural requirements of the business, data, and technology across the organization to support the desired business process outcomes. These outcomes include the DM processes and required technology infrastructure.

Scope

• Work with DM Project Management Office (PMO) to design and implement sustainable business-as-usual processes and tools for the integration of business and technology architecture with data architecture.
• Ensure DM function alignment with business, data and technology architecture and strategy.
• Ensure that the DM governance is aligned to both business and technology governance activities.

Value Proposition

Organizations that effectively deliver technology architecture aligned to business and data architecture get a return on investment from several areas:

• A simplified environment allows an organization to be nimble to market, agile in response to regulatory changes and faster to innovate
• Tool selection and implementation are simplified, aligned to business process and data requirements which reduces complexity and cost
• A data storage strategy is developed consistent with the objectives of business while it controls cost and risk
• Operational risk architecture ensures the continuous flow of data to critical business functions in the event of an outage incident

Overview

Information architecture is the combination of data architecture and technology architecture. Business architecture or data architecture should not dictate technology. The technology infrastructure of an organization is the responsibility of the technology function. However, the requirements of business architecture and data architecture inform technology. Data architecture captures the information requirements of the business process and translates them into the what, where and when of data: what data is needed; where is it to be delivered, and by when. Technology architecture is the enabler and defines the plan and roadmap for implementation.

There are four areas of technology architecture that are critical to a successful DM initiative.

• Database Platforms: Technology architecture defines acceptable data platforms for enterprise use. Enterprise-class database platforms, appliance technologies, distributed computing, and in-memory solutions all need to be defined, communicated and governed by technology architecture.
• Tools: Often one of the biggest expenses and source of inconsistent handling of data is the proliferation of multiple, disparate DM technology tools within an organization. Technology architecture must define the allowable tool stacks – what Business Intelligence (BI) tools, extract, transform & load (ETL) tools, and various discovery tools are permitted for use within the organization.
• Storage Strategy: Technology architecture must define how organizations will store and maintain its data. Several aspects of the target-state storage strategy are the determination of how to maintain data and control data storage. This includes decisions about the use of internal versus external cloud technology, how data will be archived and retained, and how data will be defensibly removed and destroyed from the organization’s infrastructure.
• Operational Risk Planning: A sound technology architecture addresses operational risk, business continuity, and disaster recovery strategies. Data is the lifeblood of an organization and needs proper planning to ensure that data flows to all parts of the organization even in the face of events that interrupt business continuity.

Finally, all the above aspects of a sound technology architecture must be supported by a strong technology governance operating model integrated with the governance of business and data architecture. Policies must be in place, agreed to by business, data and technology stakeholders, supported by executive management, and subject to internal audit scrutiny and adherence. Without integrated governance over business, data and technology architecture, infrastructure and tools will grow independently of each other. This uncontrolled infrastructure will result in inefficiencies and security issues putting data quality (DQ) and the organization at risk.

Core Questions

• Is technology architecture driven by business process and data requirements?
• Are policies in place to integrate the governance of business, data and technology architectures?
• Are governance procedures in place to ensure adherence?
• Are design reviews in place and required to ensure enhancements and new development utilize standard business, data and technology architecture definitions?
• Is adherence to data architecture standards auditable?

Core Artifacts

The following are the core artifacts required to execute an effective Data & Technology Architecture capability. Items with an ‘*’ link to published best practice guidelines.

• Data & Technology Architecture Policy Alignment Matrix
• Data Management Tool Stack Roadmap
• Storage Criteria, Strategy, & Roadmap
• Tool Selection Strategy Document

First Capability

The Technology function must work in collaboration with the DM initiative. Together they define the organization-wide data platform, storage and distribution infrastructures. This collaboration must be supported by mutual governance and policy.

First Sub-Capability

Description

The role of the Technology function is to define and design the architecture needed to accommodate data requirements in collaboration with business process requirements. The Technology function must work in collaboration with the DM initiative. Together they define the database strategies, analytics platform approaches, middleware solutions, storage and retention technologies, information security considerations, and all other aspects of the holistic technology infrastructure needed to support the DM goals and objectives of the organization.

Objectives

• Design an integrated TA strategy. Obtain agreement from business, data and technology senior executive stakeholders and socialize the strategy.
• Develop the TA strategy to include the review of business objective requirements that can be supported by innovative technology tools and methods. Key among these are Machine Learning (ML) and Artificial Intelligence (AI).
• Support and enforce the integrated architecture strategy using the Internal Audit policy.

Advice

The technology vision must ensure that the DM initiative can be supported by the Technology function. The Technology function runs the technology infrastructure. It does not define data functionality or requirements. Evaluate the TA strategy with DM objectives at the forefront.

An obligation of the data architecture (DA) and TA functions is to evaluate the business objectives and inform the business senior executives of opportunities to deploy innovative technology tools and methods like ML/AI. The review should include opportunities to support the DM initiative objectives and processes using these tools and methods.

Questions

• What are the mechanisms to ensure a formal, ongoing partnership between the Office of Data Management (ODM) and the Technology function?
• Have the DA and TA functions evaluated and communicated opportunities to deploy innovative technical tools and methods in support of the defined business objectives?

Artifacts

• TA strategy alignment with DM strategy, inclusive of the DA strategy
• List of stakeholders and evidence of bi-directional communication

Scoring

Next Sub-Capability

Description

The DM initiative must be engaged with TA in the platform infrastructure to define and execute a strategy, an execution roadmap and a governance structure. For a technology strategy to be sustainable, it must have a budget commitment over the life of the designed roadmap.

Objectives

• Design an integrated platform infrastructure strategy. Obtain agreement from business, data, and technology senior executive stakeholders.
• Develop an integrated platform infrastructure roadmap.
• Develop budgets and gain approval. Integrate the budget into the organization’s budget processes.
• Build and make operational an integrated platform infrastructure governance system and policies.
• Ensure that all enhancements and new developments are subject to a review and approval consistent with the defined platform infrastructure strategy and roadmap.
• Obtain the backing of Internal Audit for the platform infrastructure strategy.

Advice

TA is accountable for the platform infrastructure strategy, the execution roadmap and. The strategy must be coordinated with business requirements for the Database Management Systems (DBMS) organization-wide. The ODM should be a facilitator, providing coordination among the stakeholders to represent these business considerations. Prioritization is critical.

Some opportunities for innovation in the organization-wide platform infrastructure involve new technology tools and methods. The infrastructure may benefit from the addition of AI, ML, Natural Language Processing (NLP), knowledge graphs and big data.

Questions

• What are the mechanisms to ensure coordination among business, data, and technology at the proper levels of the organization?
• Are legal and compliance involved in these decisions?
• Are additional legal requirements considered?
• What are the mechanisms for coordination and prioritization?

Artifacts

• Platform infrastructure requirements, strategy, and roadmap
• Evidence of alignment with the DM strategy
• Evidence of alignment, socialization, and approval
• DBMS consideration represented in policy and standards
• Evidence of DBMS consideration in Software Development Lifecycle (SDLC) tollgates at the onset of technology platform enhancements or new development

Scoring

Next Sub-Capability

Description

The DM initiative must be engaged with TA in the data storage infrastructure to define and execute a strategy, an execution roadmap and a governance structure. For a technology strategy to be sustainable, it must have a budget commitment over the life of the designed roadmap.

Objectives

• Design an integrated storage management strategy. Obtain agreement from business, data, and technology senior executive stakeholders.
• Develop an integrated data storage roadmap.
• Develop budgets and gain approval. Integrate the budget into the organization’s budget processes.
• Build and make operational a storage management infrastructure governance system and policies.
• Ensure that all enhancements and new developments are subject to a review and approval consistent with the defined storage management strategy and roadmap
• Obtain the backing of Internal Audit for the storage management strategy.

Advice

Data storage management strategy, execution roadmap and governance are each a TA function. The strategy must be coordinated with business requirements for areas like archiving capability, legal and compliance considerations, retention and defensible destruction of data. It is important to extend the storage strategy to incorporate sandbox environments. The ODM should be a facilitator, providing coordination among the stakeholders to represent these business considerations. Additionally, data storage, archive, and retrieval plans must be coordinated across the various stakeholders (business, data, technology, legal, and compliance). Prioritization is critical.

Some opportunities for innovation in the organization-wide data storage infrastructure involve new technology tools and methods. Consider the roles Hadoop, cloud and on-prem/off-prem-Data might play in building new infrastructure. There are also, new opportunities for data to be encrypted, tokenized, anonymized, or pseudonymized at rest, in transit and in storage.

Questions

• What are the mechanisms to ensure coordination among business, data, and technology at the proper levels of the organization?
• Are legal and compliance involved in these decisions?
• Are additional legal requirements considered in the strategy including but not limited to masking, anonymization, and the full complement of personal privacy rights?
• What is the organization’s appetite for cloud data storage services?
• How will the organization manage data reconstruction from an archive?
• What are the mechanisms for coordination and prioritization?

Artifacts

• Storage requirements, strategy, and roadmap
• Evidence of alignment with the DM strategy
• Evidence of alignment, socialization, and approval
• Storage consideration represented in policy and standards
• Evidence of storage consideration in SDLC tollgates at the onset of technology platform enhancements or new development

Scoring

Next Sub-Capability

Description

The DM initiative must be engaged with TA in the data distribution infrastructure to define and execute a strategy, an execution roadmap and a governance structure. For a technology strategy to be sustainable, it must have a budget commitment over the life of the designed roadmap.

Objectives

• Design an integrated data distribution strategy. Obtain agreement from business, data, and technology senior executive stakeholders.
• Develop a data distribution infrastructure roadmap.
• Develop budgets and gain approval. Integrate the budget into the organization’s budget processes.
• Build and make operational a data distribution infrastructure governance system and policies.
• Ensure that all enhancements and new developments are subject to a review and approval consistent with the defined data distribution strategy and roadmap.
• Obtain the backing of Internal Audit for the data distribution strategy.

Advice

TA is accountable for a data distribution infrastructure strategy, execution roadmap and governance structure. The strategy must be coordinated with business requirements for areas like data access controls, information security restrictions, authorized data provisioning points and data as a service (DaaS). The ODM should be a facilitator – providing coordination among the stakeholders to represent these business considerations. Prioritization is critical.

Some opportunities for innovation in the organization-wide data distribution involve new technology tools and methods. Consider the roles DaaS–API/Technology; web-based access; macros for power users and various BI tools might play in building new infrastructure.

Questions

• What are the mechanisms to ensure coordination among business, data, and technology at the proper levels of the organization?
• Are legal and compliance involved in these decisions?
• What is the organization’s appetite for data distribution as a service?
• What are the mechanisms for coordination and prioritization?

Artifacts

• Platform infrastructure requirements, strategy, and roadmap
• Evidence of alignment with the DM strategy
• Evidence of alignment, socialization, and approval
• Data distribution infrastructure represented in policy and standards
• Evidence of data distribution infrastructure consideration in SDLC tollgates at the onset of technology platform enhancements or new development

Scoring

Next Sub-Capability

Description

The DM governance must be engaged with TA governance to align with the overall technology vision and strategy along with the specific strategies for organization-wide platform, data storage and data distribution infrastructures. Alignment to TA governance processes may include design reviews, permit to build, permit to use and permit to send approvals.

Objectives

• Develop an integrated governance structure and policies in alignment with the TA and DA strategies.
• Ensure all technology development meets the TA policy requirement to follow DA policy and standards.
• Submit all enhancements and new developments for architectural platform design review and approval.

Advice

Technology governance is the responsibility of the technology group. Because of the close relationship between the DM initiative and technology implementation, it is imperative that the DM function collaborate with the technology group. Together they create, support and enforce technology policy and standards that impact the DM initiative.

This collaboration with technology is designed to ensure alignment with business processes, compliance with data restrictions and harmonization with both technical and architectural standards. This will include design reviews to ensure that technology implementation follows DA policy and standards and that toll gates are in place to review the technical implementation.

TA governance guarantees adherence to declared platform and tool standards. The objective is to ensure that existing TA governance policies reflect the goals of the DM initiative.

The emerging AI and ML tools also have potential application to enhancing the DM processes and should be considered in the overall DM technology tool stack planning.

Questions

• Is TA governance aligned with DA governance?
• Is DA involved in the technical design review process?
• Are authorizations to build, use and send data in place?
• Are legal and compliance involved in this effort?
• Is TA policy aligned with the DM strategy?

Artifacts

• Evidence of governance collaboration such as stakeholder meeting agendas and results, escalation procedures
• Evidence of toll gate review process, for example, minutes and meeting outcomes
• TA policy and DA policy reference the other without duplication
• List of stakeholders and evidence of bi-directional communication on technical review and authorizations

Scoring

Next Capability

The DM business process must define requirements for the DM technology tool stack. Execution roadmaps and governance ensure the tools are adopted.

First Sub-Capability

Description

The DM initiative is just like any other business process. Technology requirements must be defined by the DM business process and the requirements for data from the business process. The DM executive is accountable for the requirements for technology and technology is responsible for a DM technology strategy that delivers against those requirements.

Objectives

• Design an integrated DM technology tool strategy. Obtain agreement on the strategy from business, data and technology senior executive stakeholders. Socialize the DM technology tool strategy.
• Demonstrate support for the DM technology tool strategy by corporate policy. Engage with Internal Audit for enforcement.

Advice

Ensure that there is a defined DM technology tool selection strategy and that it is aligned with the DM initiative. The ODM must ensure that the DM initiative can support the use of various tools (i.e., modeling, ETL, metadata, glossary, DQ, analytics). This support capability requires coordination between business, data, and technology stakeholders to define the DM initiative business process and data requirements for the DM tool selection.

Questions

• What are the mechanisms for coordination between the technology tool selection process and DM?
• Are the policies, procedures, and processes that govern this relationship defined and verified?

Artifacts

• Tool selection strategy document
• List of stakeholders and evidence of bi-directional communication

Scoring

Next Sub-Capability

Description

A technology tool roadmap must be developed to execute the DM technology infrastructure defined in the tool selection strategy.

Objectives

• Develop an integrated technology tool roadmap in adherence to the technology tool strategy. Include guidelines for new development as well as decommission plans for non-standardized legacy tool implementations.
• Develop budgets aligned to the organization’s budget cycle processes. Move the budget through the process to approval.

Advice

Once the tool selection strategy is defined, it needs to be converted into an actionable implementation roadmap. Make sure the technology roadmap is practical, aligned to business priorities and harmonized with internal procurement processes.

Questions

• Is the DM technology tool roadmap aligned with internal procurement processes?
• Is the DM technology tool roadmap shared with the ODM?

Artifacts

• Technology tool roadmap document
• Evidence of alignment with the DM strategy
• Documented approvals

Scoring

Next Sub-Capability

Description

Technology, in partnership with the DM initiative, must define and govern the DM related technology stack. Data tools include but are not limited to data discovery tools, DQ tools, data profiling tools, metadata tools, lineage tools, BI tools and data governance tools.

Objectives

• Put in place an operational, integrated technology tool governance structure with a complete set of associated policies. Confirm that the structure is in alignment with the DM strategy.
• Get a review and approval of all enhancements and new development projects to ensure alignment with technology tool selection. Technology governs the permissible technology stack for related data tools.
• Implement data tool governance structure and complete operational roll-out across all technology development teams.

Advice

Ensure the governance structure for DM technology tools is in place and operational, and that the governance policies and practices incorporate the DM initiative requirements. Different tools that perform the same functions can produce disparate data. Beyond this, the proliferation of tools can increase complexity, add cost and inhibit systems integration. However, the business needs the flexibility to acquire the best tools for their objectives. The challenge is, the ODM must manage the disparate data.

Questions

• What are the mechanisms for coordination between the technology tool selection governance, and DM?
• How is the organization working with innovation teams to keep abreast of new technology capabilities?
• Is there a mechanism for collaboration between DM and data tool selection?
• Is there an agreement between technology and business regarding the scope and controls associated with technology tools?

Artifacts

• Technology tool governance structure document
• Evidence of governance operation such as meetings and procedures, documents
• Policy and standards for data tool governance which are documented and verified
• List of authorized tools
• Bi-directional communication between business, data and technology on tool selection and criteria for approval

Scoring

Next Capability

The DM governance structure must be in alignment with operational risk governance and engaged in the contingency planning and testing for data access and maintenance in the event of an operational disruption.

First Sub-Capability

Description

The DM initiative governance structure must be in alignment with operational risk governance. The data policy must align with the operational risk policy without creating duplication in the policies.

Objectives

• Develop an integrated operational risk governance structure and policies and make them operational.
• Approve operational risk plans for all enhancements and new development through project tollgates.
• Bring Internal Audit in to approve the operational risk planning.

Advice

Operational risk routines such as disaster recovery, Business Continuity Planning, cyber-threats, degrees of interconnectedness, testing and dependency planning must be formalized for all data systems. Changes to existing systems and new development must be evaluated against the operational risk guidelines. Operational risk will also be driven by regulation. Governance oversight should ensure compliance in advance of an internal audit or regulatory examinations.

Questions

• Is operational risk governance formalized and aligned with the organization’s risk and escalation plans?
• Is operational risk governance aligned with the DM governance mechanisms?

Artifacts

• Disaster recovery governance mechanisms
• Evidence of disaster recovery planning collaboration with compliance

Scoring

Next Sub-Capability

Description

The DM initiative, while not directly accountable, must be engaged in the contingency planning and testing for data access and maintenance in the event of an operational disruption.

Objectives

• Develop an integrated technology operational risk management strategy. Obtain agreement from business, data, and technology senior executive stakeholders.
• Engage Internal Audit to review and support the integrated technology operational risk management strategy.

Advice

Operational risk requirements for data must be considered early in the SDLC. These requirements will define the data architecture’s choice of data storage applications and data recovery strategies. When evaluating a data storage application, keep in mind applications may hold data from multiple data domains. The most stringent data recovery requirements might be applied to all data in the application. The more stringent data recovery has a higher cost so this may inflate storage cost for all the data.

Questions

• What are the mechanisms to ensure collaboration between DM and operational risk contingency planning?
• Are all data dependencies defined and understood for recovery?

Artifacts

• Disaster Recovery Plan
• Tests and results of Disaster Recovery Plan

Scoring