1. Develop a Five Year Data Architecture Plan
Secure your footings in data to lay a foundation that will withstand the winds and rain of the IT disruptors of today and tomorrow.
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2. Introduction
Cloud and mobile computing are changing where and how data is stored and accessed; increasing data provenance and management headaches. Big Data and Analytics are upon us. Architect for change to reduce chaos and plan for each disruptor’s impact on your environment now and into the future.
This Research Is Designed For:
This Research Will Help You:
Organizations of any size who have a formal data architecture in place or are transitioning to a formal architecture.
Technical leaders in the organization such as: CIOs, Chief Architects, and IT Managers.
Business leaders trying to understand how and why these technologies are affecting data.
Data practitioners such as: Data Architects, Data Specialists, Data Stewards, and Data Scientists.
See the impacts of the immediate and future technologies on data architecture and management.
Develop a data architecture to accommodate the immediate and future technologies without compromising on data quality, provenance, management, and security.
Perform short and long-term planning for data architecture implementation using people, policy, process, and technology.
Future proof your data architecture.

3. Executive Summary Today’s IT innovations are data disruptors
An enterprise level Data Architecture will help you deal with and plan for data disruptions. A holistic view of data repositories, governed by set principles, policies, and guidelines relevant to the organization and the information it manages will prepare you for dealing with changes in data, technology, and resource requirements.
At the root of all data is a person, place, or thing: use your master data as an index to connect your data repositories. Master data management maintains a single source of truth for people, places, and things relevant to an organization. Use an MDM repository as an enterprise data integration index.
“Big” skills are in high demand but short supply. Plan for new positions to manage Big Data and perform analytics. Be prepared to pay a premium or go (back) to school to get them.
Info-Tech Insights
Cloud computing takes the data out of the enterprise IT environment.
Mobile computing allows access to corporate data anywhere, anytime.
New computing paradigms impact the level of trust organizations have in their own data.
Data management technology is improving to meet the new demands.
Big Data and Analytics are creating value but not without chaos.
Be proactive on immediate and critical data issues
Set policies and use technology to maintain control of your data in a cloudy IT environment.
Set policies to control corporate data access from mobile devices.
Improve data trust through provenance policies and data stewardship.
Use data virtualization technology as part of your data management plan for faster time to value of data aggregation and integration.
Architect and plan for the future
Data provenance technology is emerging; impacting all data repositories from operations through backup and archiving.
Big Data is a big deal. Prepare for it with architecture and planning to define boundaries, allocate resources, funding, and procure technology.
Analytics are providing new insights into old problems. Don’t ignore it.

4. How to use this blueprint
There are multiple ways you can use this Info-Tech Best Practice Blueprint in your organization. Choose the option that best fits your needs:
Best Practice Blueprint
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Use this Best Practice Blueprint to help you complete your project. The slides in this Blueprint will walk you step-by-step through every phase of your project with supporting tools and templates ready for you to use.
Project Accelerator Workshop
You can also use this Best Practice Blueprint to facilitate your own project accelerator workshop within your organization using the workshop slides and facilitation instructions provided in the Appendix.
We recommend that you supplement the Best Practices Blueprint with a Guided Implementation.
For most Info-Tech members, these Guided Implementations are included in your membership plan.* Our expert analysts will provide telephone assistance to you and your team at key project milestones to review your materials, answer your questions, and explain our methodology.
Info-Tech Research Group’s expert analysts will come onsite to help you work through our project methodology in a 2-5 day project accelerator workshop. We take you through every phase of the project and ensure that you have a road map in place to complete your project successfully. In some cases, we can even complete the project while we are onsite.
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5. Book a free guided implementation today!
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Enroll in a Guided Implementation for your project Send an to Or call and ask for the Guided Implementation Coordinator
Book your analyst meetings Once you are enrolled in a Guided Implementation, our analysts will reach out to book a series of milestone-related telephone meetings with you and your team.
Get advice from a subject matter expert At each Guided Implementation point, our Consulting Analyst will review your completed deliverables with you, answer any of your questions, and work with you to plan out your next phase.
This symbol signifies when you’ve reached a Guided Implementation point in your project.
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6. Book a workshop today!
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Plan your workshop A Workshop Facilitator will contact you to go over the workshop outline and choose the contents that are appropriate to your situation.
Participate in your workshop Our experienced Workshop Facilitators will take your project team through your tailored slides and exercises and will summarize all the workshop outputs into a final report.
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7. 5-Year Data Architecture Plan
Looking for research on Data Architecture and Integration? Your search starts and ends here
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Applications
Systems Integration
Application
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Business
Process
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Best Practices
Data Integration
Workflow and
Forms Automation

8. Guided Implementation Points in the Data Architecture project
Book a Guided Implementation Today: Info-Tech is just a phone call away and can assist you with your project. Our expert Analysts can guide you to successful project completion.
Here are the suggested Guided Implementation points in the Data Architecture project:
Section 2: Current Architecture Assessment
Validate architecture documentation and focus. Review your organization’s current architecture documentation and identify areas of focus for data architecture improvements.
Section 3: Immediate Disruptor Assessment
Identify critical areas of focus. Using your organization’s business and IT drivers for cloud and mobile computing, develop architecture building blocks to help mitigate the disruption while weaving data trust foresight into the mix.
Section 4: Data Management Assessment
Determine most effective use of data management technologies and approaches. Understand where and how data integration, virtualization, quality, replication, security, and master data management fit in your environment.
Section 5: Future Disruptor Assessment
Take a position on big data and analytics so you can plan now for the future.
Section 6: Architecture Plan Assessment
Review your plan. Identify any gaps in the plan based on reference architectures and best practices.
This symbol signifies when you’ve reached a Guided Implementation point in your project.
To enroll, send an to or call and ask for the Guided Implementation Coordinator.

9. Finding your way in the maze
Cloud and Data Architecture
Mobile and Data Architecture
Data Trust
Big Data and Analytics
Finding your way in the maze
Data Architecture
Immediate and Critical Policy Issues
Data Management
Future Policy Issues
Using the Plan

10. Mastered Data Architecture?
Organizations that struggle with data quality, integration, and master data aren’t prepared for today’s IT innovations
Data architecture and master data management hold the keys to cleaning up the current environment and leveraging new technologies.
Data architecture provides a holistic view of enterprise data repositories, their relationships with each other and ownership.
Data architecture sets the principles, policies, and guidelines relevant to an organization and the information it manages.
Master data is critical. It is the source of truth for all the people, places, and things relevant to organizations
Master data repositories provide a location independent view of the truth.
Master data needs to be the most trusted data in the organization.
Master data management provides the relationships to derivatives of the people, places, and things.
Master data provides the keys to linking big structured and unstructured data, and is the basis on which analytics are performed.
Mastered Data Architecture?
Cloud computing is here today and even if you aren’t using it, your competitors are.
Mobile computing is allowing for access to corporate data from anywhere at any time.
Trusting your data goes beyond the quality of what it is, to knowing where it came from, who has had access to it, and how to use it.
Data virtualization is changing data integration, warehousing, and reporting, but it also illuminates data quality issues.
Constantly changing data integration, management and quality technologies, budgets, and skills requirements.
Big Data is a big deal. It is changing everything data related from the infrastructure through to the analysis.
Analytics are creating business value by finding hidden, and unknown information buried in big structured and unstructured data.
Big skills are in high demand, but short supply.
Are You Ready?
Not doing data architecture and master data management? You’re not prepared for what’s coming.

11. Don’t lose control of your data in a cloudy IT environment
Sending your data into the cloud does not remove the challenge of managing it, it just changes the nature of that challenge.
Many organizations are persuaded by the perceived value of cloud computing.
Lower implement time.
Less technical complexity.
Increased flexibility.
Reduction in cost.
Cloud brings standards, best practices, and control.
Standards can ease integration among applications and with partners.
Cloud communities bring best practices to light.
Vendors control database schemas and maintain data integrity constraints.
Cloud needs governance.
Delegate and govern the responsibility for managing the integrity, accessibility, and security of cloud data.
Weather the transition with documented metadata, systems of record, accountable data owners, integration processes, and established governance practices.
Value
Migration to the cloud will require a modification of data architecture to enable a single view of accurate data.
Integration processes between cloud and on-premise, and cloud-to-cloud are more complex than traditional approaches.
Data quality issues are prevalent between cloud and on- premise data transfers.
Cleansing and regular synchronizations must be performed to manage data quality and integrity.
Existing user access and authentication policies must be refreshed and updated.
Current access levels may not adequately secure your data in the cloud.
Different security architectures and mechanisms are required to protect data in the cloud.
Data at rest in the cloud should be encrypted to protect it from unauthorized use and/or attacks.
Data in transit between on-premise and clouds must be encrypted.
Impact

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