Build a Data Architecture Roadmap

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

ANALYST PERSPECTIVE

Integral to an insight-driven enterprise is a modern and business-driven data environment.

“As business and data landscapes change, an organization’s data architecture needs to be able to keep pace with these changes. It needs to be responsive so as to not only ensure the organization continues to operate efficiently but that it supports the overall strategic direction of the organization.

In the dynamic marketplace of today, organizations are constantly juggling disruptive forces and are finding the need to be more proactive rather than reactive. As such, organizations are finding their data to be a source of competitive advantage where the data architecture has to be able to not only support the increasing amount, sources, and rate at which organizations are capturing and collecting data but also be able to 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 for better empowering the business.” (Crystal Singh, Director, Research, Data and Information Practice, Info-Tech Research Group)

Our understanding of the problem

Executive summary

Situation

• The data architecture of a modern organization involves many moving pieces requiring coordination to provide greatest value from data.
• 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.

Complication

• Data architects must account for the constantly growing data and application complexity, and more demanding needs from the business.
• 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.

Resolution

• To deal with these challenges, a data architect must have a framework in place to identify the appropriate solution for the challenge at hand.
  • 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 need to 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

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.
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.
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.

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 seeking to leverage can be uncovered with a data practice that makes high quality, trustworthy information readily available to the business users who need it.

50% Organizations that embrace data are 50% more likely to launch products and services ahead of their competitors. (Nesta, 2016)

Whether 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:

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

Here comes the zettabyte era.

A zettabyte is a billion terabytes. Organizations today need to measure their data size in zettabytes, 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 first step. The reality is that the true hurdles to overcome are in facing the challenges of today’s data landscape.

“The data environment is very chaotic nowadays. Legacy applications, data sprawl – organizations are grappling with what their data landscape looks like. Where are our data assets that we need to use?” (Andrew Johnston, Independent Consultant)

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 Plan For Establishing a Business-Aligned Data Management Practice 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. 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 it’s own designated position, but a role that can be completed by a variety of IT professionals.

Data architects bridge the gap between strategic and technical requirements: “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 tackling these issues

Outdated and archaic systems and processes limit the ability to access data in a timely and efficient manner, ultimately diminishing the value your data should bring.

Intuitive organizations who have recognized these shortcomings have already begun the transition to modernized and optimized systems and processes.

Leading organizations are attacking data architecture problems … you will be left behind if you do not start now!

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

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

Follow Info-Tech’s methodology to optimize data architecture to meet the business needs

The following is a summary of Info-Tech’s methodology:

1	Prioritize your core business objectives and identify your business driver. Learn how business drivers apply to specific tiers of Info-Tech’s five-tier data architecture model. Determine the appropriate tactical pattern that addresses your most important requirements.
2	Select the areas of the five-tier architecture to focus on. Measure current state. Set the targets of your desired optimized state.
3	Roadmap your tactics. Manage and communicate change.

Info-Tech will get you to your optimized state faster by focusing on the important business issues

First Things First

1. Info-Tech’s methodology helps you to prioritize and establish the core strategic objectives behind your goal of modernizing data architecture. This will narrow your focus to the appropriate areas of your current data systems and processes that require the most attention.

Info-Tech has identified these four common drivers that lead to the need to optimize your data architecture.

• Becoming More Data Driven
• Regulations and Compliance
• Mergers and Acquisitions
• New Functionality or Business Rule

These different core objectives underline the motivation to optimize data architecture, and will determine your overall approach.

Use the five-tier architecture to provide a consumable view of your data architecture

Every organization’s data system requires a unique design and an assortment of applications and storage units to fit their business needs. Therefore, it is difficult to paint a picture of an ideal model that has universal applications. However, when data architecture is broken down in terms of layers or tiers, there exists a general structure that is seen in all data systems.

Thinking of your data systems and processes in this framework will allow you to see how different elements of the architecture relate to specific business operations.

Use the five-tier architecture to prioritize tactics to improve your data architecture in line with your pattern

Info-Tech’s Data Architecture Capability Model	Based on your business driver, the relevant data tiers, and your organization’s own specific requirements you will need to establish the appropriate data architecture capabilities. This blueprint will help you measure how you are currently performing in these capabilities… And help you define and set targets so you can reach your optimized state.
Once completed, these steps will be provided with the information you will need to create a comprehensive roadmap. Lastly, this blueprint will provide you with the tools to communicate this plan across your organization and offer change management guidelines to ensure successful adoption.	Info-Tech Insight Optimizing data architecture requires a tactical approach, not a passive approach. The demanding task of optimization requires the ability to heavily prioritize. After you have identified why, determine how using our pre-built roadmap to address the four common drivers.

Do not forget: data architecture is not a standalone concept; it fits into the more holistic design of enterprise architecture

Data Architecture in Alignment Data architecture can not 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 to see the full picture of enterprise architecture: Select and Implement an EA Tool Enhance Your Application Architecture

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.

Info-Tech’s data architecture optimization methodology helped a monetary authority fulfill strict regulatory pressures

CASE STUDY

Industry: Financial Source: Info-Tech Consulting

Look for this symbol as you walk through the blueprint for details on how Info-Tech Consulting assisted this monetary authority.

Situation: Strong external pressures required the monetary authority to update and optimize its data architecture.

The monetary authority is responsible for oversight of 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 pressures.

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.

Provide a structured approach to solving the problem

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.

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

• External Requirements
• Business Driver
  Diagnose Data Architecture Problems
  • Outdated architecture (paper, legacy systems)
  • Stale data from other agencies
  • Incomplete data
    Data Architecture Optimization Tactics
    1. Optimized Source Databases
    2. Improved Integration
    3. Data Warehouse Optimization
    4. Data Marts for Reports
    5. Report Delivery Efficiency

As you walk through this blueprint, watch for additional case studies that walk through the details of how Info-Tech helped this monetary authority.

This blueprint’s three-step process will help you optimize data architecture in your organization

Use these icons to help direct you as you navigate this research

Use these icons to help guide you through each step of the blueprint and direct you to content related to the recommended activities.

This icon denotes a slide where a supporting Info-Tech tool or template will help you perform the activity or step associated with the slide. Refer to the supporting tool or template to get the best results and proceed to the next step of the project.

This icon denotes a slide with an associated activity. The activity can be performed either as part of your project or with the support of Info-Tech team members, who will come onsite to facilitate a workshop for your organization.

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

Diagnostics and consistent frameworks used throughout all four options

Build a Business-Aligned Data Architecture Optimization Strategy – project overview

	PHASE 1 Prioritize Your Data Architecture With Business-Driven Tactics	PHASE 2 Personalize Your Tactics to Optimize Your Data Architecture	PHASE 3 Create Your Tactical Data Architecture Roadmap
Best-Practice Toolkit	1.1 Identify Your Business Driver for Optimizing Data Architecture 1.2 Determine Actionable Tactics to Optimize Data Architecture	2.1 Measure Your Data Architecture Capabilities 2.2 Set a Target for Data Architecture Capabilities 2.3 Identify the Tactics that Apply to Your Organization	3.1 Personalize Your Data Architecture Roadmap 3.2 Manage Your Data Architecture Decisions and the Resulting Changes
Guided Implementations	Understand what data architecture is, how it aligns with enterprise architecture, and how data architects support the needs of the business. Identify the business drivers that necessitate the optimization of the organization’s data architecture. Create a tactical plan to optimize data architecture across Info-Tech’s five-tier logical data architecture model.	Understand Info-Tech’s tactical data architecture capability model and measure the current state of these capabilities at the organization. Determine the target state of data architecture capabilities. Understand the trends in the field of data architecture and identify how they can fit into your environment.	Use the results of the data architecture capability gap assessment to determine the priority of activities to populate your personalized data architecture optimization roadmap. Understand how to manage change as a data architect or equivalent.
Onsite Workshop	Module 1: Identify the Drivers of the Business for Optimizing Data Architecture	Module 2: Create a Tactical Plan for Optimizing Data Architecture	Module 3: Create a Personalized Roadmap for Data Architecture Activities