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What do you do if your Data Architecture project is exceeding budget constraints?

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Data Architecture is the design and implementation of data systems that support the business needs and goals of an organization. It involves planning, modeling, integrating, and governing the data sources, structures, and flows that enable data-driven decision making and insights. However, Data Architecture projects can be complex, dynamic, and costly, and sometimes they may exceed the budget constraints that were initially set. What do you do if you find yourself in this situation? Here are some tips to help you manage your Data Architecture project and keep it within budget.

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Biswadeep Sen

Senior Manager @ Axtria | Azure, Product Management

1 Assess the situation

The first step is to assess the situation and identify the root causes of the budget overrun. Is it due to scope creep, inaccurate estimation, unexpected changes, technical issues, or other factors? How much is the project over budget and how much time is left to complete it? How does the budget issue affect the quality, performance, and value of the data architecture? You need to have a clear and realistic picture of the current state of the project and the implications of the budget problem.

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Sumit Verma

Principal Data Engineer | Gen AI | 14x Azure, 5x Databricks, 1x AWS,1x GCP
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To control cost, we need to first identify the root cause. Is the high cost occurring during DEV or in PROD. If DEV, then it can be mostly due to a greater number of resources, improper task allocation, high time for development, taking more work outside of scope which may escalate cost. To address this, define the scope and adhere to it. Onboard skilled engineers. Be transparent with client about it to gain their trust. If the cost exceeds in production, then most probably the issue is of high compute utilization. So, design the proper way of autoscaling. Implement better caching and fine-tuning techniques to reduce compute load. Add monitoring capability to monitor the production to get insight of issue.

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2 Communicate with stakeholders

The next step is to communicate with the stakeholders of the project, such as the sponsors, clients, users, and team members. You need to inform them about the budget situation, the reasons behind it, and the potential risks and impacts. You also need to listen to their feedback, expectations, and suggestions, and negotiate with them on possible solutions. You may need to adjust the scope, timeline, or deliverables of the project, or seek additional funding or resources. You need to maintain transparency, trust, and collaboration with the stakeholders throughout the process.

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3 Prioritize and optimize

The third step is to prioritize and optimize the tasks and components of the data architecture project. You need to focus on the most critical and valuable aspects of the project, and eliminate or defer the less important or nice-to-have ones. You need to review and refine the data architecture design, data models, data sources, data integration, data quality, and data governance, and ensure that they align with the business requirements and objectives. You need to leverage the best practices, standards, and tools that can help you optimize the efficiency, scalability, and quality of the data architecture.

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4 Monitor and control

The final step is to monitor and control the progress and performance of the data architecture project. You need to track and measure the actual costs, time, and results of the project against the planned budget, schedule, and scope. You need to identify and resolve any issues, risks, or deviations that may arise during the execution of the project. You need to report and communicate the status and outcomes of the project to the stakeholders on a regular basis. You need to ensure that the data architecture project delivers the expected value and benefits within the budget constraints.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Biswadeep Sen

Senior Manager @ Axtria | Azure, Product Management
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If your data architecture project is exceeding its budget, promptly identify the root causes, reassess and adjust the project scope, communicate openly with stakeholders, and prioritize essential deliverables while trimming non-critical features. Implement robust risk mitigation strategies, consider contract renegotiation, optimize resource allocation, explore technology solutions, and continuously monitor expenses. If applicable, seek additional funding and document lessons learned to improve future project estimations and management strategies.

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What do you do if your Data Architecture project is exceeding budget constraints?

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5

1 Assess the situation

2 Communicate with stakeholders

3 Prioritize and optimize

4 Monitor and control

5 Here’s what else to consider

Data Architecture

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What do you do if your Data Architecture project is exceeding budget constraints?

1

2

3

4

5

1 Assess the situation

2 Communicate with stakeholders

3 Prioritize and optimize

4 Monitor and control

5 Here’s what else to consider

Data Architecture

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