- Data architecture 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.
- Data architects must account for the constantly growing data and application complexity, more demanding needs from the business, an ever-increasing number of data sources, and a growing need to integrate components to ensure that performance isn’t compromised.
Our Advice
Critical Insight
- Data architecture needs to evolve with the changing business landscape. There are four common business drivers that put most pressure on archaic architectures. As a result, the organization’s architecture must be flexible and responsive to changing business needs.
- Data architecture is not just about models. Viewing data architecture as just technical data modeling can lead to structurally unsound data that does not serve the business.
- Data is used differently across the layers of an organization’s data architecture, and the capabilities needed to optimize use of data change with it. Architecting and managing data from source to warehousing to presentation requires different tactics for optimal use.
Impact and Result
- Have a framework in place to identify the appropriate solution for the challenge at hand. Our three-phase practical approach will help you build a custom and modernized data architecture.
- 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.
- 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.
Member Testimonials
After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.
8.8/10
Overall Impact
$10,215
Average $ Saved
27
Average Days Saved
Client
Experience
Impact
$ Saved
Days Saved
Sanmar Corp
Guided Implementation
9/10
$32,499
5
General Dynamics Mission Systems, Inc
Guided Implementation
8/10
$2,599
5
American Bankers Association
Guided Implementation
8/10
$2,141
3
PRIDE Industries
Guided Implementation
10/10
$12,599
120
Dura-Line Corporation
Guided Implementation
9/10
$1,239
2
Republic Services Procurement, Inc.
Workshop
9/10
$251K
50
Kuvare US Holdings
Workshop
10/10
$62,999
50
England & Wales Cricket Board Ltd
Guided Implementation
9/10
$10,440
26
Toronto Community Housing Corporation
Guided Implementation
9/10
$20,500
10
Workshop: Build a Data Architecture Roadmap
Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Identify the Drivers of the Business for Optimizing Data Architecture
The Purpose
- Explain approach and value proposition.
- Review the common business drivers and how the organization is driving a need to optimize data architecture.
- Understand Info-Tech’s five-tier data architecture model.
- Determine the pattern of tactics that apply to the organization for optimization.
Key Benefits Achieved
- Understanding of the current data architecture landscape.
- Priorities for tactical initiatives in the data architecture practice are identified.
- Target state for the data quality practice is defined.
Activities
Outputs
Explain approach and value proposition.
- Five-tier logical data architecture model
Review the common business drivers and how the organization is driving a need to optimize data architecture.
- Data architecture tactic plan
Understand Info-Tech’s five-tier data architecture model.
Determine the pattern of tactics that apply to the organization for optimization.
Module 2: Determine Your Tactics For Optimizing Data Architecture
The Purpose
- Define improvement initiatives.
- Define a data architecture improvement strategy and roadmap.
Key Benefits Achieved
- Gaps, inefficiencies, and opportunities in the data architecture practice are identified.
Activities
Outputs
Create business unit prioritization roadmap.
- Business unit prioritization roadmap
Develop subject area project scope.
- Subject area scope
Subject area 1: data lineage analysis, root cause analysis, impact assessment, business analysis
- Data lineage diagram
Module 3: Create a Strategy for Data Quality Project 2
The Purpose
- Define improvement initiatives.
- Define a data quality improvement strategy and roadmap.
Key Benefits Achieved
- Improvement initiatives are defined.
- Improvement initiatives are evaluated and prioritized to develop an improvement strategy.
- A roadmap is defined to depict when and how to tackle the improvement initiatives.
Activities
Outputs
Create business unit prioritization roadmap.
- Business unit prioritization roadmap
Develop subject area project scope.
- Subject area scope
Subject area 1: data lineage analysis, root cause analysis, impact assessment, business analysis.
- Data lineage diagram
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
This Research Is Designed For:
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This Research Will Help You:
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This Research Will Also Assist:
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This Research Will Help Them:
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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
- 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.
- 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.
- 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:
Business Monitoring
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Business Insights
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Business Optimization
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Business Transformation
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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.
Challenges of The Modern Data Landscape | ||||
Data at rest | Data movement | |||
Greater amounts | Different types | Uncertain quality | Faster rates | Higher complexity |
“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 ArchitectureThe set of rules, policies, standards, and models that govern and define the type of data collected and how it is used, stored, managed, and integrated within the organization and its database systems. In general, the primary objective of data architecture is the standardization of data for the benefit of the organization. 54% of leading “analytics-driven” enterprises site data architecture as a required skill for data analytics initiatives. (Maynard 2015) |
MYTHData architecture is purely a model of the technical requirements of your data systems. REALITYData architecture is largely dependent on a human element. It can be viewed as “the bridge between defining strategy and its implementation”. (Erwin 2016) |
FunctionsA strong data architecture should:
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Business valueA strong data architecture will help you:
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Data architects must maintain a comprehensive view of the organization’s rapidly proliferating data
The data architect:
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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.
59% |
of firms believe their legacy storage systems require too much processing to meet today’s business needs. (Attivio, Survey Big Data decision Makers, 2016) | 48% |
of companies experience pains from being reliant on “manual methods and trial and error when preparing data.” (Attivio, Survey Big Data decision Makers, 2016) | 44% |
44% of firms said preparing data was their top hurdle for analytics, with 22% citing problems in accessing data. (Data Virtualization blog, Data Movement Killed the BI Star, 2016) |
Intuitive organizations who have recognized these shortcomings have already begun the transition to modernized and optimized systems and processes.
28% |
of survey respondents say they plan to replace “data management and architecture because it cannot handle the requirements of big data.” (Informatica, Digital Transformation: Is Your Data Management Ready, 2016) | 50% |
Of enterprises plan to replace their data warehouse systems and analytical tools in the next few years. (TDWI, End of the Data Warehouse as we know it, 2017) |
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.
IT Symptoms Due to Ineffective Data Architecture | ||
Poor Data Quality
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Poor Accessibility
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Strategic Disconnect
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Leads to Poor Organizational Conditions | ||
Inaccurate Insights
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Ineffective Decision Making
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Inefficient Operations
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You need a solution that will prevent the pains. |
Follow Info-Tech’s methodology to optimize data architecture to meet the business needs
The following is a summary of Info-Tech’s methodology:
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Info-Tech will get you to your optimized state faster by focusing on the important business issues
First Things First
- 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.
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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
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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: |
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
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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
- Optimized Source Databases
- Improved Integration
- Data Warehouse Optimization
- Data Marts for Reports
- 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
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 |
Step 1: Identify Your Business Driver for Optimizing Data Architecture
Data Architecture Driver Pattern Identification Tool
Data Architecture Optimization Template |
Step 1: Measure Your Data Architecture Capabilities
Data Architecture Tactical Roadmap Tool
Data Architecture Tactical Roadmap Tool
Data Architecture Trends Presentation |
Step 1: Personalize Your Data Architecture Roadmap
Data Architecture Tactical Roadmap Tool
Data Architecture Decision Template |
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
DIY Toolkit |
Guided Implementation |
Workshop |
Consulting |
"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." | "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." | "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." | "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
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 |
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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 |
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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 |