Build a Data Architecture Roadmap

Optimizing data architecture requires a plan, not just a data model.

EXECUTIVE BRIEF

Analyst Perspective

A modern and business-driven data environment is integral to an insight-driven enterprise.

As business and data landscapes change, an organization's data architecture must keep pace with these changes. It must be responsive not only to ensure the organization continues to operate efficiently but to support the organization's overall strategic direction.

In the dynamic marketplace of today, organizations are constantly juggling disruptive forces and are finding the need to be more proactive. As such, organizations are realizing their data is a source of competitive advantage where the data architecture must not only support the increasing amount, sources, and rate at which organizations are capturing and collecting data but also meet and deliver on changing business needs.

Data architecture optimization should, therefore, aid in breaking down data silos and creating a more shared and all-encompassing data environment to better empower the business.

Crystal Singh
Research Director, Data and Information Practice
Info-Tech Research Group

Our understanding of the problem

This research is designed for

• Data architects or their equivalent who intend to optimize and improve the efficiency of the capture, movement, and storage of data for a variety of business drivers.
• Enterprise architects intending to improve the backbone of the holistic approach of their organization's structure.

This research will help you

• Identify the business drivers that are impacted and improved by best-practice data architecture.
• Optimize your data architecture using tactical practices to address the business' pressing issues and drive modernization.
• Align the organization's data architecture with the greater enterprise architecture.

This research will also assist

• CIOs concerned with costs, benefits, and the overall structure of their organizations data flow.
• Database administrators tasked with monitoring crucial elements of the data architecture.

This research will also help you

• Get a handle on the current situation of data within the organization.
• Understand how data architecture affects the operations of the data sources within the enterprise.

Executive Summary

Your Challenge

Your organization is experiencing data challenges:

• Large data volume, variety, and velocity, if not properly managed, may result in unreliable data and unfavorable output.
• Business transformation shapes the modern data landscape. Organizations face a growing number of challenges when it comes to adopting modern technologies.

Data architects are at the center of this turmoil and must be able to translate high-level business requirements into specific instructions for data workers using complex data models.

Common Obstacles

• Data architects must account for constantly growing data and application complexity, and more demanding business needs.
• There is an ever-increasing number of data sources and a growing need to integrate components to ensure that performance isn't compromised.
• There isn't always a clearly defined data architect role, yet the responsibilities must be filled to get maximum value from data.

Info-Tech's Approach

• Identify and prioritize the business drivers in which data architecture changes would create the largest overall benefit and determine the corresponding data architecture tiers that must be addressed to customize your solution.
• Discover the best-practice trends, measure your current state, and define the targets for your data architecture tactics.
• Build a cohesive and personalized roadmap for restructuring your data architecture. Manage your decisions and resulting changes.

Info-Tech Insight

Data architecture is a cornerstone of significant business transformation (such as digital transformation, mergers and acquisitions, and emergence of new business models and innovations). Lubricate your business transformation with sound data architecture.

Your data is the foundation of your organization's knowledge and ability to make decisions

Data should be at the foundation of your organization's evolution.

The transformational insights that executives are constantly striving to leverage can be uncovered with a data practice that makes high quality, trustworthy information readily available to the business users who need it.

Business Information
Actionable Insights
Digital Transformation

Whether you're hoping to gain a better understanding of your business or trying to become an innovator in your industry, any organization can get value from its data regardless of where you are in your journey to becoming a data-driven enterprise.

88% of respondents say that being data driven helps them stay on top of customer needs and market trends.
Source: Experian, 2022

The journey to being data-driven

The journey to becoming a data-driven organization requires a pit stop at data enablement.

The Data Economy

• Data disengaged
  You have a low appetite for data and rarely use data for decision making.
• Data enabled
  Technology, data architecture, and people and processes are optimized and supported by data governance.
• Data driven
  You are differentiating and competing on data and analytics, described as a "data first" organization. You're collaborating through data. Data is an asset.

As organizations strive to become more data driven, it is imperative to better manage data for its effective use

Here comes the zettabyte era.

• Worldwide data creation is projected to increase to more than 180 zettabytes by 2025 (Statista, 2021), a challenge that is only compounded by the speed at which the data is expected to move.
• Arriving at the understanding that data can be the driving force of your organization is just the beginning. The greater obstacles to overcome are in facing the challenges of today's data landscape.

Solution

Well-defined and structured data management practices are the best way to mitigate the limitations that derive from these challenges and leverage the most possible value from your data.

Refer to Info-Tech's capstone Create a Data Management Roadmap blueprint to understand data quality in the context of data disciplines and methods for improving your data management capabilities.

Data architecture is an integral aspect of data management

Data architects must maintain a comprehensive view of the organization's rapidly proliferating data

The data architect:

• Acts as a translator between the business and data workers to communicate data and technology requirements.
• Is proactive in partnering with the business to facilitate the alignment of IT and business systems.
• Facilitates the creation of the data strategy.
• Manages the enterprise data model.
• Has a greater knowledge of operational and analytical data use cases.
• Recommends data management policies and standards and maintains data management artifacts.
• Reviews project solution architectures and identifies cross impacts across the data lifecycle.
• Is a hands-on expert in data management and warehousing technologies.
• Is not necessarily its own designated position, but a role that can be filled by a variety of IT professionals.

"Fundamentally, the role of a data architect is to understand the data in an organization at a reasonable level of abstraction."
– Andrew Johnston, Independent Consultant

Many are experiencing the pains of poor data architecture, but leading organizations are proactively addressing these issues

Once on your path to redesigning your data architecture, neglecting the strategic elements may leave you ineffective

Focusing only on data models without the required data architecture guidance may cause harmful symptoms in your IT department, which will lead to organization-wide problems.

You need a solution that will prevent the pains.

Despite investments in data initiatives, organizations are carrying high levels of data debt

Data debt is "the accumulated cost that is associated with the sub-optimal governance of data assets in an enterprise, like technical debt" (Experian, 2020).

Data debt is the problem for 78% of organizations.

Think of all the time your organization spends on non-value-add activities such as cleaning and massaging data, discussing and disagreeing on the proper definition of business data terms, etc.

Data debt is the cost of fixing things instead of gathering value when your data architecture is not efficient.

Data architecture is not a standalone concept: it fits into the more holistic design of enterprise architecture

Data architecture in alignment

• Data architecture cannot be designed to simply address the focus of data specialists or even the IT department.
• It must act as a key component in the all-encompassing enterprise architecture and reflect the strategy and design of the entire business.
• Data architecture collaborates with application architecture in the delivery of effective information systems and informs technology architecture on data related infrastructure requirements/considerations.

• Please refer to the following blueprints for the full picture of enterprise architecture:
  • Design an Enterprise Architecture Strategy
  • Agile Enterprise Architecture Operating Model

Adapted from TOGAF

Refer to Phase C of TOGAF and Bizbok for references to the components of business architecture that are used in data architecture.

Executive Brief Case Study

INDUSTRY: Financial
SOURCE: Info-Tech Consulting

Monetary authority

The monetary authority is responsible for monitoring the financial situation of a country that takes in revenue from foreign incorporation. Due to increased pressure from international regulatory bodies, the monetary authority became responsible for generating multiple different types of beneficial ownership reports based on corporation ownership data within 24 hours of a request.

A stale and inefficient data architecture prevented the monetary authority from fulfilling external regulatory requirements.

Normally, the process to generate and provide beneficial ownership reports took a week or more. This was due to multiple points of stale data architecture, including a dependence on outdated legacy systems and a broken process for gathering the required data from a mix of paper and electronic sources.

Results

Info-Tech helped the monetary authority identify the business need that resulted from regulatory pressures, the challenges that needed to be overcome, and actionable tactics for addressing the needs.

As you go through this blueprint, you will find additional case studies that elaborate on how Info-Tech helped this monetary authority.

Info-Tech's methodology was followed to optimize the areas of data architecture that address the business driver.

Build a Data Architecture Roadmap Project Overview

Insight summary

Overarching insight

Data architecture is a cornerstone of significant business transformation (such as digital transformation, mergers and acquisitions, and emergence of new business models and innovations). Lubricate your business transformation with sound data architecture.

Insight 1

Data architecture is not just about models. Viewing data architecture as just technical data modeling can lead to a data environment that does not aptly serve or support the business. Identify the priorities of your business and adapt your data architecture to those needs.

Insight 2

Changes to data architecture are typically driven by four common business driver patterns. Use these as a shortcut to understand how to evolve your data architecture.

Insight 3

Data is used differently across the layers of an organization's data architecture. Therefore, the capabilities needed to optimize the use of data change with it. Architecting and managing data from source to warehousing to presentation requires different tactics for optimal use.

Tactical insight

Focus on early alignment. Assessing capabilities within specific job functions can result in disagreement or debate, especially between business and IT people. Objectively facilitate any debate and only finalize capability assessments when there is full alignment. Remind everyone that data architecture should ultimately serve business needs wherever possible.

Tactical insight

Optimizing data architecture requires a tactical approach, not a passive one. The demanding task of optimization requires the ability to heavily prioritize. After you have identified why, determine how using our prebuilt roadmap to address the four common drivers.

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

Key deliverable:

Data Architecture Tactical Roadmap Tool

This Data Architecture Tactical Roadmap Tool will help you analyze your organization's data architecture capabilities and the gaps between the organization's current and future states.

Data Architecture Driver Pattern Identification Tool

Data Architecture Optimization Template

Data Architecture Trends Presentation

Data Architecture Decision Template

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

“Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.”

Guided Implementation

“Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.”

Workshop

“We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.”

Consulting

“Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”

Diagnostics and consistent frameworks used throughout all four options