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Build Your Data Practice and Platform

Construct a scalable data foundation.

The complex nature of data investment leads to de-scoping and delivery of data services that do not meet business needs or give value to the business. Subject matter experts are hired to resolve the problem, but their success is impacted by absent architecture, technology, and organizational alignment.

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Critical Insight

Walking through a book of architecture building plans with a personal guide is cheaper and faster than employing an architect to build and design your home.


Impact and Result

Info-Tech's approach provides a proven methodology that includes the following:

  • Business-aligned data initiatives and capabilities that address data challenges and realize business strategic objectives.
  • Comprehensive data practice designed based on the required business and data capabilities.
  • Data platform design based on Info-Tech data architecture reference patterns and prioritized data initiatives and capabilities.

Build Your Data Practice and Platform Research & Tools

1. Build Your Data Practice and Platform Storyboard – A step-by-step document that leverages road-tested patterns and frameworks to properly build your data practice and pattern in continuous alignment with the business landscape.

Info-Tech's approach provides a proven methodology that includes following:   

  • Business-aligned data initiatives and capabilities that address data challenges and realize business strategic objectives.
  • Comprehensive data practices designed based on the required business and data capabilities.

Data platform design based on Info-Tech data architecture reference patterns and prioritized data initiatives and capabilities.

Build Your Data Practice and Platform Storyboard

2. Data Practice and Platform Models – Leveraging best-of-breed frameworks to help you build a clear, concise, and compelling data practice and platform.

Data practice & platform pre-build pattern templates based on Info-Tech data reference patterns and data platform design best practices.

Data Practice and Platform Models

Workshop: Build Your Data Practice and Platform

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: Establish Business Context and Value

The Purpose

Establish business context and value.

Key Benefits Achieved

Business context and strategic driver.

Activities

Outputs

1.1

Understand/confirm the organization's strategic goals

  • Business context and strategic drivers
1.2

Classify the strategic goals and map to business drivers

  • Prioritized business capabilities and processes
1.3

Identify the business capabilities that the strategy focuses on

  • Data culture survey results analysis
1.4

Identify the business processes realizing the strategy

Module 2: Identify Your Top Initiatives

The Purpose

Identify your top initiatives.

Key Benefits Achieved

High-value business-aligned data initiative.

Activities

Outputs

2.1

Highlight data-related outcomes/goals to realize to fulfill the business goal

  • High-value, business-aligned data initiatives
2.2

Map business data initiatives to the business strategic goals

2.3

Prioritize data initiatives

Module 3: Analyze Data Challenges

The Purpose

Analyze data challenges.

Key Benefits Achieved

Clear understanding of the data challenges.

Activities

Outputs

3.1

Map data challenges to Info-Tech data challenges

  • List of data challenges preventing data maturation with the organization
3.2

Review Info-Tech data capabilities based on prioritized initiatives

3.3

Discuss data platform and practice next steps

Module 4: Map Data Capability

The Purpose

Map data capability.

Key Benefits Achieved

Prioritized data capability.

Activities

Outputs

4.1

Map data challenges to Info-Tech data challenges

  • Required data capabilities
4.2

Review Info-Tech data capabilities based on prioritized initiatives

  • Data platform and practice – plan
4.3

Discuss data platform and practice next steps

  • Initialized data management RACI 
Unlock This Blueprint

Build Your Data Practice and Platform

Construct a scalable data foundation

Analyst Perspective

Build a data practice and platform that delivers value to your organization.

The build or optimization of your data practice and data platform must be predicated on a thorough understanding of the organization’s goals, objectives, and priorities and the business capabilities and process they are meant to support and enable.

Formalizing your practice or constructing your platform just for the sake of doing so often results in an initiative that is lengthy, costly, fizzles out, does not deliver business value, and ends up being considered a failure.

Leverage Info-Tech’s approach and incorporate our pre-built models and patterns to effectively navigate that crucial and often difficult phase upfront of comprehensively defining business data needs so you can ultimately realize faster time-to-delivery of your overall data practice and platform.

Photo of Rajesh Parab, Director, Research & Advisory, Data & Analytics Practice, Info-Tech Research Group.

Rajesh Parab
Director, Research & Advisory, Data & Analytics Practice
Info-Tech Research Group
Photo of Crystal Singh, Director, Research & Advisory, Data & Analytics Practice, Info-Tech Research Group.

Crystal Singh
Director, Research & Advisory, Data & Analytics Practice
Info-Tech Research Group

Attempting to Solve Data Problems?

Situation
  • Lack of data centric leadership results in downstream issues such as integration, quality, and accessibility.
  • The complex nature of the data and lack of understanding leads to de-scoping delivery of data services that does not meet business needs or add value.
  • Poorly designed practice and siloed platforms result in an initiative that is lengthy, costly, fizzles out, does not deliver business value, and ends up being considered a failure.
 Complication
  • Data problem: When the data problem is diagnosed, the organization adopts a tactical approach.
  • Confirmation bias: Subject matter experts (SME) are hired to resolve the poorly defined problem, but the success of the SME is impacted by lack of architecture, technology, and organizational alignment.
  • Still no value: The selected tactical approach does not provide a solid foundation or solve your data problem.
  • Strategy for sake of strategy: Implementing a strategic approach for the sake of being strategic but this becomes overwhelming.
  • Fall back to tactical and operational: The data services are now potentially exposed and vulnerable, which strains business continuity and increases data debt.
  • Increased complexity and risk: Data silos, poor understanding, and high complexity results in an unmanageable data environment.
 Resolution
  • Requirements: Define and align your data requirement to business.
  • Capabilities: Discover data, identify data capabilities, and map your requirements.
  • Practices: Design and select fit-for-purpose data practices.
  • Platform: Optimize your data platform investments though sound architecture.

Info-Tech Insight

The true value of data comes from defining intentional relationships between the business and the data through a well thought out data platform and practice.

Situation – Perpetual Data Problem

Diagram of a head with gears around it and speech bubbles with notes titled 'Data Problem'. The surrounding gears, clockwise from bottom left, say 'Accessibility', 'Trust', 'Data Breach', 'Ambiguity', 'Ownership', 'Duplication', 'System Failure', and 'Manual Manipulation'. The speech bubbles notes, clockwise from bottom left, say 'Value-Add: How do I translate business needs to data capabilities?', 'Practice Organization: How do I organize resources and roles assignment challenges?', 'Platform: How do I organize data flows with no conceptual view of the environment?', and 'Break Down Silos: How do I break down silos?'
I can’t access the data.
I don’t trust the data in the report.
It takes too long to get to the data for decision making
  • Lack of data-centric leadership results in downstream issues: integration, quality, accessibility
  • The organization’s data is too complex to manage without a cohesive plan.
  • The complex nature of the data and a lack of understanding leads to de-scoping delivery of data services that does not meet business needs or add value.
  • Poorly designed practice and siloed platforms result in an initiative that is lengthy, costly, fizzles out, does not deliver business value, and ends up being considered a failure.

Complication – Data Initiative Fizzles Out

  • Data problem: When the data problem is diagnosed the organization adopts a tactical approach.
  • Confirmation bias: Subject matter experts (SME) are hired to resolve the poorly defined problem, but the success of the SME is impacted by lack of architecture, technology, and organizational alignment.
  • Still no value: the selected tactical approach does not provide a solid foundation or solve your data problem.
  • Strategy for sake of strategy: Implementing a strategic approach for sake of being strategic but this becomes overwhelming.
  • Fall back to tactical and operational: The data services are now potentially exposed and vulnerable, which strains business continuity and increases data debt.
  • Increased complexity and risk: Data silos, poor understanding, and high complexity result in an unmanageable data environment.
 Flowchart beginning with 'Data Symptom Exhibited' and 'Data Problem Diagnosed', then splitting into two paths 'Solve Data Problem as a point solution' or 'Attempt Strategic approach without culture, capacity, and business leadership'. Each approach ends with 'Data too complex, and initiative fizzles out...' and cycles back to the beginning.
Use the road-tested patterns and frameworks in our blueprint to break the perpetual data solution cycle. Focus on the value that a data and analytics platform will bring rather than focusing on the data problems alone.

Build Your Data Practice and Platform

Bring Your Data Strategy to Life

 Logo for Info-Tech.
Logo for #iTRG.
CONVENTIONAL WISDOM

Attempting to Solve Your Data Problems

DATA SYMPTOM EXHIBITED

Mismatch report, data quality issue, or similar symptom of a data problem.

 DATA PROBLEM DIAGNOSED

Data expert identifies it as a data problem.

 COMPLEX STRATEGIC APPROACH ATTEMPTED

Recognized need to attempt it strategically, but don't have capacity or culture to execute.
Cycle diagram titled 'Data Problems' with numbers connected to surrounding steps, and a break after Step 3 where one can 'BREAK THE CYCLE'. In the middle are a list of data problems: 'Accessibility’, ‘Data Breach', 'Manual Manipulation', 'System Failure', 'Ambiguity', 'Duplication', 'Ownership', and 'Trust'.
SOLUTION FAILS

The tactical solution fails to solve the root cause of the data problem, and the data symptoms persist.

 TACTICAL SOLUTION FALLBACK

A quick and dirty solution is attempted in order to fix the data problem.

 THE COMPLEX APPROACH FIZZLES OUT

Attempted strategic approach takes too long, fizzles out.
BREAK THE CYCLE

Solving Your Data Problems

  1. DEFINE YOUR DATA REQUIREMENTS Incorporate a Business to Data Approach by utilizing Info-Tech's business capability templates for identifying data needs. BUSINESS-ALIGNED DATA REQUIREMENTS
  2. CONDUCT YOUR DATA DISCOVERY Understand the data behind your business problem. Identify the required data capabilities and domains as required by your business processes. RECOMMENDED DATA CAPABILITIES
  3. DESIGN YOUR DATA PRACTICES Build your custom data practices based on the predefined reusable models. CUSTOMIZED DATA PRACTICE
  4. ARCHITECT YOUR DATA PLATFORM Build your custom data platform based on the redefined reusable architecture patterns. CUSTOMIZED DATA PLATFORM
 CONTINUOUS PHASE: ROADMAP, SPONSORSHIP FEEDBACK AND DELIVERY

Develop a roadmap to establish the practice and implement the architecture as designed. Ensure continuous alignment of the practice and architecture with the business landscape.

Phase-by-Phase Approach to Build Your Data Practice and Platform

Flowchart detailing the path to take through the four phases of this blueprint beginning with the 'Inputs' and 'People' involved and incorporating 'Deliverables' along the way. Phase-by-Phase Approach
  • Phase 1: Step 1 – Define Your Data Requirement
  • Phase 1: Step 2 – Conduct Your Data Discovery
  • Phase 2 – Design Your Data Practice
  • Phase 3 – Architect Your Data Platform

Measure value when building your data practice and platform

Sample Data Management Metrics

Lists of data management metrics in different categories.

  • Refine the metrics for the overall Data Management practice and every initiative therein.
  • Refine the metrics at each platform and practice component to show business value against implementation effort.

Understand and Build Data Culture

See your Info-Tech Account Representative for more details on our Data Culture Diagnostic

Only 14.29% of Transportation and Logistics respondents agree BI and Analytics Process and Technology are sufficient What is a diagnostic?

Our diagnostics are the simplest way to collect the data you need, turn it into actionable insights, and communicate with stakeholders across the organization.

 52.54% of respondents from the healthcare industry are unaware of their organization’s data security policy
Ask the Right Questions

Use our low-effort surveys to get the data you need from stakeholders across the organization.

 Use Our Diagnostic Engine

Our diagnostic engine does all the heavy lifting and analysis, turning your data into usable information.

 Communicate & Take Action

Wow your executives with the incredible insights you've uncovered. Then, get to action: make IT better.
On average only 40% agree that they have the reporting when needed


(Source: Info-Tech’s Data Culture Diagnostic, 53 Organizations, 3138 Responses)

 35% of respondents feel that a governance body is in place looking at strategic data

Build a Data-Driven Strategy Using Info-Tech Diagnostic Programs

Make informed IT decisions by starting your diagnostic program today. Your account manager is waiting to help you.		 Sample of Info-Tech's 'Data Culture Scorecard'.

Use Our Predefined Data and Analytics Patterns to Build Your DnA Landscape

Walking through a book of architecture building plans with a personal guide is cheaper and faster than employing an architect to build and design your home

Two books titled 'The Everything Homebuilding Book' and 'Architecture 101'. An open book with a finger pointing to a diagram.

The first step is to align business strategy with data strategy and then start building your data practice and data platform

 Flowchart starting with business strategy focuses, then to data strategy focuses, and eventually to 'Data Metrics'.

Insights

The true value of data comes from defining intentional relationships between the business and the data through a well-thought-out data platform and practice.

  • Phase 1
    • Some organizations are low maturity so using the traditional Capability Maturity Model Integration (CMMI) would not make sense. A great alternative is to leverage existing models and methodologies to get going off the bat.
    • The Data Strategy is an input into the platform and practice. This is considered the Why; Data Practice and Platform is the How.
  • Phase 2
    • Info-Tech’s approach is business-goal driven and it leverages patterns, which enable the implementation of critical and foundational components and subsequently facilitates the evolution and development of the practice over time.
    • Systems should not be designed in isolation. Cross-functional collaboration throughout the design is critical to ensure all types of issues are revealed early. Otherwise, crucial tests are omitted, deployments fail, and end-users are dissatisfied.
  • Phase 3
    • Build your conceptual data architecture based on well-thought-out formulated patterns that align with your organization’s needs and environment.
    • Functional needs often take precedence over quality architecture. Quality must be baked into design, execution, and decision-making practices to ensure the right trade-offs are made.

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

Info-Tech’s Methodology for Building Your Data Practice and Platform

Phase 1 –
Define Your Data Requirements and Conduct Your Data Discovery		 Phase 2 –
Design Your Data Practices		 Phase 3 –
Architect Your Data Platform
Phase Steps
  1. Identify your top initiatives
  2. Map your data initiatives to data capabilities
  1. Understand the practices value statement
  2. Review the Info-Tech practice pattern
  3. Initiate your practice design and setup
  1. Identify your data component
  2. Refine your data platform architecture
  3. Design your data platform
  4. Identify your new components and capabilities
  5. Initiative platform build and rollout
Phase Outcomes Business-aligned data initiatives and capabilities that address data challenges and realize business strategic objectives Comprehensive data practice design based on the required business and data capabilities Data platform design based on Info-Tech data architecture reference pattern and prioritized data initiatives and capabilities

Data Platform and Practice Implementation Plan

Example timeline for data platform and practice implementation plan with 'Fiscal Years' across the top, and below they're broken down into quarters. Along the left side 'Phase 1: Step 1...', 'Phase 1: Step 2...', 'Phase 2...' and 'Phase 3'. Tasks are mapped onto the timeline in each phase with a short explanation.

Workshop Overview
Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889
Info-Tech’s Workshop support for Build Your Data Practice and Platform. 'Build Your Data Practice and Platform' slide from earlier.
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."

 Workshop 1

Data Needs and Discovery

 Workshop 2

Data Practice Design

 Workshop 3

Data Platform Design

Workshop 1:
Data Needs and Discovery

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889
Day 1 Day 2 Day 3 Day 4
Establish Business Context and Value
Identify Your Top Initiatives
Analyze Data Challenges
Map Data Capability
Activities

1.1 Understand/confirm your organization’s strategic goals

1.2 Classify the strategic goals and map to business drivers

1.3 Identify the business capabilities that the strategy focus is on

1.4 Identify the business processes realizing the strategy

2.1 Highlight data-related outcomes /goals to realize to fulfill the business goal

2.2 Map business data initiatives to the business strategic goals

2.3 Prioritize Data initiatives

3.1 Understand data management capabilities and framework

3.2 Classify business data requirements using Info-Tech’s classification approach

3.3 Highlight data challenges in your current environment

4.1 Map data challenges to Info-Tech data challenges

4.2 Review Info-Tech data capabilities based on prioritized initiative

4.3 Discuss Data Platform and Practice Next Steps
Deliverables
  • Business context and strategic drivers
  • Prioritized business capabilities and processes
  • Data Culture Survey results analysis
  • High-value business-aligned data initiative
  • List of data challenges preventing data maturation with the organization
  • Required data capabilities
  • Data platform and practice – plan
  • Initialized data management RACI
Participants Business stakeholder, Business leader Business Subject Matter Expert, Data IT sponsor (CIO), Head of Data, Data Architect Business stakeholder, Business leader Business Subject Matter Expert, Data IT sponsor (CIO), Head of Data, Data Architect Data experts, Business Subject Matter Expert, Head of Data, Data Architect Data experts, Business Subject Matter Expert, Head of Data, Data Architect

Workshop 2:
Data Practice Design

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889
Day 1 Day 2 Day 3 Day 4
Plan Your Data Practices
Design Your Data Practices 1
Design Your Data Practices 2
Design Your Data Practices 3
Activities

Prerequisite: Business context, business data requirement, and data capabilities

1.1 Understand data practice framework

1.2 Define your practice implementation approach

1.3 Review and update data management RACI

2.1 Understand Info-Tech data practice patterns for each prioritized practice

2.2 Define your practice setup for each prioritized practice

2.3 Highlight critical processes for each practice

3.1 Understand Info-Tech data practice patterns for each prioritized practice

3.2 Define your practice setup for each prioritized practice

3.3 Highlight critical processes for each practice

4.1 Understand Info-Tech data practice patterns for each prioritized practice

4.2 Define your practice setup for each prioritized practice

4.3 Highlight critical processes for each practice

4.4 Discuss data platform and practice next steps
Deliverables
  • Data practice implementation approach
  • Data management RACI
  • Data practice setup pattern for your organization
  • Data practice process pattern for your organization
  • Data practice setup pattern for your organization
  • Data practice process pattern for your organization
  • Data practice setup pattern for your organization
  • Data practice process pattern for your organization
  • Data platform and practice – plan
Participants Data experts, Business Subject Matter Expert, Head of Data, Data Architect Data experts, Business Subject Matter Expert, Head of Data, Data Architect Data experts, Business Subject Matter Expert, Head of Data, Data Architect Data experts, Business Subject Matter Expert, Head of Data, Data Architect

Workshop 3:
Data Platform Design

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889
Day 1Day 2Day 3Day 4
Data Platform Overview
Update Data Platform Reference Architecture
Design Your Data Platform
Design Your Data Practices 4
Activities

Prerequisite: Business context, business data requirement, and data capabilities

1.1 Understand data platform framework and data capabilities

1.2 Understand key data architecture principles and best practices

1.3 Shortlist data platform patterns

2.1 Map and identify data capabilities to data platform components

2.2 Build data platform architecture using Info-Tech data platform reference architecture

2.3 Highlight critical processes for each practice

3.1 Design your target data platform using Info-Tech’s data platform template

3.2 Identify new capabilities and components in your platform design

4.1 Identify new capabilities and component in your platform design

4.2 Discuss data platform initiatives

Deliverables
  • Shortlisted data platform patterns
  • Data platform reference architecture for your organization
  • Data platform design for your organization
  • Data platform plan
ParticipantsData experts, Business Subject Matter Expert, Head of Data, Data ArchitectData experts, Business Subject Matter Expert, Head of Data, Data ArchitectData experts, Business Subject Matter Expert, Head of Data, Data ArchitectData experts, Business Subject Matter Expert, Head of Data, Data Architect

Build Your Data Practice and Platform

Phase 1

Phase 1: Step 1 – Define Your Data Requirements
Phase 1: Step 2 – Conduct Your Data Discovery

Phase 1

1.1 Define Your Data Requirements
1.2 Conduct Your Data Discovery

 Phase 2 Phase 3

Phase 1: Step 1 – Define Your Data Requirements will walk you through the following activities:

  • Confirm the organizational strategic goals, business drivers, business capabilities, and processes driving the Data Practice and Platform effort.
  • Identify the data related outcomes, goals, and ideal environment needed to fulfill the business goals.

This phase involves the following participants:

A blend of business leaders and business SMEs together with the Data Strategy team.

Phase 1: Step 2 – Conduct Your Data Discovery will walk you through the following activities:

  • Identify and highlight the data challenges faced in achieving the desired outcome.
  • Map the data challenges to the data capabilities required to realize the desired data outcome.

This phase involves the following participants:

Key personnel from IT/Data team: (Data Architect, Data Engineers, Head of Head of Reporting and Analytics)

Build Your Data Practice and Platform visualization

Construct a scalable data foundation.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Authors

Crystal Singh

Dirk Coetsee

Rajesh Parab

Related Content: Data Management

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