Your team is divided on data architecture scalability. How do you choose the best approach to move forward?
When your team is split on data architecture scalability, selecting the right path forward is critical. Here's how to make an informed choice:
What strategies have worked for your team when deciding on data architecture? Share your experience.
Your team is divided on data architecture scalability. How do you choose the best approach to move forward?
When your team is split on data architecture scalability, selecting the right path forward is critical. Here's how to make an informed choice:
What strategies have worked for your team when deciding on data architecture? Share your experience.
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Create a "Collaborative approach" by: Aligning data initiatives with business priorities Engaging stakeholders across departments to gain insights into their data needs and challenges Choose technologies, platforms that support horizontal and vertical scaling Consolidate data from various sources by implementing centralized data repositories or data lakes Provide context and improve data discoverability by using "Metadata Management" Simply data management, adopt data visualization Enhance data accessibility, governance and security by implementing a Data Fabric Architecture Improve responsiveness and agility by implementing Event-driven architecture (EDA) Limit data access by implementing Role Based Access Control (RBAC)
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📊 Assess Current and Future Needs: Evaluate immediate requirements and projected growth to ensure the architecture will scale effectively over time, balancing short- and long-term goals. 🔍 Compare Different Models: Analyze multiple architecture models, focusing on performance, cost, and implementation ease to choose the best fit for scalability. 🤝 Engage Stakeholders for Collaborative Decisions: Facilitate discussions with key stakeholders to gather insights from diverse perspectives, helping the team reach a consensus on the most viable approach. 🧪 Run Pilot Tests: Conduct small-scale tests of top models to observe scalability impacts, allowing an evidence-based decision without full commitment.
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Before fully committing, run pilot tests to see how different scaling strategies perform under load. This can help identify potential issues and refine your approach.
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Promoting a modularized approach to architecture is something I consistently advocate, as it simplifies accommodating changes. Periodically revisiting the architecture is essential to enhance it, make it more comprehensive, and align it with advancements in technology or tools. In cases of differing views on the architecture, it is important to first establish a baseline and then collaborate with teams to understand various perspectives, assess them individually, and implement relevant changes. Assessments should be done point by point, with your viewpoints added, followed by a discussion with the person who raised the point to incorporate necessary adjustments.
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