How do you change your data architecture to meet new goals?

1 Assess your current state

The first step to change your data architecture is to assess your current state and identify the gaps and issues that prevent you from achieving your new goals. You need to document and evaluate your existing data sources, data flows, data models, data quality, data governance, and data usage. You also need to understand the business requirements, expectations, and pain points of your stakeholders and users. This will help you to prioritize the areas that need improvement and define the scope and objectives of your data architecture change.

2 Choose your target state

The next step is to choose your target state and design your new data architecture that aligns with your new goals. You need to consider the trade-offs and implications of different data architecture patterns, such as centralized, decentralized, federated, or hybrid. You also need to select the appropriate data platforms, tools, and technologies that support your data architecture pattern and meet your functional and non-functional requirements. You should also define the standards, policies, and processes for data management and governance in your new data architecture.

3 Plan your transition

The third step is to plan your transition and devise a strategy and roadmap for changing your data architecture. You need to identify the dependencies, risks, and challenges that may arise during the transition and prepare contingency plans and mitigation measures. You also need to estimate the time, cost, and resources needed for the transition and allocate them accordingly. You should also communicate and coordinate with your stakeholders and users and get their feedback and buy-in for the transition.

4 Implement your change

The fourth step is to implement your change and execute your transition plan. You need to follow the best practices and methodologies for data migration, integration, transformation, and testing. You also need to monitor and measure the progress and performance of your transition and ensure that the quality and integrity of your data are maintained. You should also document and validate your new data architecture and verify that it meets your new goals and expectations.

5 Train your users

The fifth step is to train your users and educate them on how to use and benefit from your new data architecture. You need to provide them with the necessary documentation, guidance, and support to help them understand and adopt your new data architecture. You also need to collect their feedback and suggestions and address any issues or concerns they may have. You should also encourage and incentivize them to use and leverage your new data architecture for their tasks and goals.

6 Evaluate your results

The final step is to evaluate your results and measure the impact and outcome of your data architecture change. You need to compare your new data architecture with your old one and assess how well it meets your new goals and requirements. You also need to analyze the benefits and drawbacks of your new data architecture and identify the areas that need further improvement or optimization. You should also celebrate and acknowledge your achievements and learn from your experiences and lessons.

7 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?