First understand why people are divided on data sources. Is it because one source contains needed data that's not in the other source? Is it because one source is better than another, or is it just perceived as better with no proof? Understanding the real issue is the first goal. If you're working in a governed environment, it's about collaboration, not single ownership. Many people use the same data for different purposes and need to work together to pick the right data source for the company as a whole. The solution can be multiple data sources when there are different needs, but for identical data, you can collectively pick a single source.

This question risks tripping out my AI (Artificial Incoherance) #DataNinja sense, but I'll play. Whether my team is the "data team" or the "business team" or the "app team" or "any team", and there is a lack of clarity or concensus on what data sources are Relevant, Additive, Redundant, or Conflicting then this isn't going to be solved by a navel gazing Data Source bingo game. Back to first principles. Where are your Data Flow Diagrams (DFD's), Where are your SME's, What is the business outcome or benefit at hand? Do you have a specific use case example? Crack open your data pipelines, do some profiling, and walk the data flow and process tree back to confirm the sources and data that matters? Work IT. Do IT. Document IT. Know IT. Ok?

When teams disagree on data sources, it's often a sign of deeper issues, such as unclear goals or differing interpretations of data quality. Beyond governance and standardization, it's essential to foster a culture of collaboration. Start by clarifying the purpose behind the data – what business objectives are we driving? Encourage open discussions to address any concerns or biases around certain data sets. Integrating feedback loops also ensures ongoing alignment. By creating transparency and shared accountability, you don't just align on data sources; you build a stronger, more unified approach to data-driven decisions.

Ensuring team alignment on data sources is vital for consistency and efficiency. Beyond establishing clear data governance and standardizing sources, consider implementing collaborative data workshops. These sessions can foster a shared understanding and encourage open dialogue about data challenges and solutions. Additionally, leveraging data visualization tools can help team members intuitively grasp data insights, promoting a unified approach. Regular feedback loops and cross-functional meetings can further enhance alignment, ensuring everyone is not only informed but also engaged in the data strategy. This holistic approach can significantly boost team cohesion and productivity.

To unify the team on data sources, facilitate a collaborative discussion to outline each source's benefits and drawbacks. Establish clear criteria for data selection and create a centralized documentation repository. Regularly review and update this information, ensuring everyone understands the chosen sources and their relevance to project goals.