Data Architecture
Manage valuable data assets
RETIRED CONTENT
Please note that the content on this page is retired. This content is not maintained and may contain information or links that are out of date.Non-existent or initial approaches to data can cause:
- Low data quality, which can lead to inefficient operations.
- Increased risk of data loss or data breaches.
- Low data trust throughout the organization, which can lead to business decisions being made based on feeling rather than empirical data.
- Increased instances of rogue data being used.
Treating data as an asset results in:
- Transparency about where data sits, how it is used, and who is using it.
- Increased data trust, which improves decision making.
- Improved availability – data is available to the right people at the right time.
- Tight data lifecycles.
- A thorough understanding of any gaps or issues that exist, and the steps needed to mitigate them.
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Onsite 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 onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
Case Studies and Deliverables
Data Architecture Case Study of a Large Hospital
A large hospital with a rich and time-honored history was well-known for its innovation and academic research activities. IT needed to ensure that its data architecture could support both the hospital’s day-to-day patient care and ongoing research mandates. The hospital recruited Info-Tech to guide them through a one-week data architecture workshop.
Data Architecture Case Study of Olmsted Medical Center
Olmsted Medical Center provides healthcare to communities in southern Minnesota via a centralized hospital and 13 clinical locations. Olmsted has recently implemented an Electronic Health Record, and wants to combine clinical and ambulatory data to give a single view of patient information. Representatives from the technology and finance teams participated in an Info-Tech workshop to develop a process for reviewing and refining data architecture principles and processes.
Module 1: Perform a Current State Assessment
The Purpose
- Establish the organization’s approach to data and its perceived data maturity level.
- Identify the business process that will be used in the data audit.
Key Benefits Achieved
- Issue identification.
- Prepared for the data audit, validating the scope, stakeholders, and participants prior to implementation.
| Activities: | Outputs: | |
|---|---|---|
| 1.1 | Determine the organization’s data value and risk. |
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| 1.2 | Establish maturity level. |
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| 1.3 | Determine what data sources contribute to a particular business process. |
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| 1.4 | Review and assess the IT reports. |
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| 1.5 | Identify data audit participants. |
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Module 2: Perform the Data Audit
The Purpose
- Establish a data audit framework.
- Understand how to effectively communicate with audit participants to obtain valuable information.
- Ensure internal policies are implemented to help minimize compliance issues.
- Identify where there are gaps in your data.
Key Benefits Achieved
- Focus your efforts on fixing major gaps in your organization’s data.
- Properly identify key data stakeholders and establish data ownership and responsibility.
| Activities: | Outputs: | |
|---|---|---|
| 2.1 | Create a data audit interview guide. |
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| 2.2 | Create a data source inventory. |
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| 2.3 | Conduct data audit interviews. |
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| 2.4 | Identify gaps in the data and perform a root cause analysis. |
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Module 3: Develop Data Architecture
The Purpose
- Set architectural principles for the target architecture.
- Select new building blocks for your target architecture.
- Prioritize the building blocks.
- Reconcile the new building blocks and their ability to solve data issues.
Key Benefits Achieved
- Selected building blocks to solve the issues uncovered in the audit.
- Reconcile the solution against the problems uncovered in the audit.
- Refined the target architecture.
| Activities: | Outputs: | |
|---|---|---|
| 3.1 | Develop a target architecture. |
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| 3.2 | Reconcile architecture. |
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Module 4: Create a Data Architecture Implementation Plan
The Purpose
- Define dependencies among building blocks.
- Group building blocks into initiatives.
- Draft a high level plan to implement the initiatives, taking cost/value and dependencies into consideration.
Key Benefits Achieved
- Establish initiatives, taking cost and value into consideration.
- Tackle the initiatives that have been identified with a realistic and manageable approach.
- Determine if the target state is going to meet the data asset management goals and objectives.
| Activities: | Outputs: | |
|---|---|---|
| 4.1 | Plan initiatives. |
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| 4.2 | Develop a strategic roadmap. |
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Module 5: Establish Metrics for Success and Communicate the Plan
The Purpose
- Set initiative benchmarks to track success.
- Determine what initiatives need to be communicated and to whom.
- Have a plan to communicate initiatives to the organization.
- Communicate the results of the data audit, along with the short and long term plans, to the organization.
Key Benefits Achieved
- Avoid creating a document that is never used.
- Workshop summary.
- Defined metric and communication goals.
| Activities: | Outputs: | |
|---|---|---|
| 5.1 | Establish metrics. |
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| 5.2 | Create a communication plan. |
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