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Collaboration in Big Data Projects: 16 Recommendations for Your Business
- Collaboration and innovation are key to navigating the complex landscape of big data projects.
- Establishing cross-functional “data squads” is a practical strategy for ensuring that everyone’s perspective is heard and that the data insights directly serve the organization’s broader goals.
- Every Big Data project should have a well-defined purpose, and kick-off meetings should clearly align the project goals with business priorities.
- Using shared tools eliminates confusion about the validity or accuracy of data and ensures everyone is working from the same baseline.
- Periodic “data debriefs” create a collaborative environment that fosters innovation and prevents bottlenecks.
- Companies can focus on creating “data translators” – team members who bridge the gap between technical and business teams.
- Keeping everything in one shared workspace makes collaboration easy and transparent.
- Building mutual respect and trust is crucial when it comes to fostering collaboration between teams working on big data projects.
- Standardizing data practices can dramatically improve collaboration and communication in Big Data projects.
- Establishing a shared data dictionary and centralized knowledge hub reduces silos and miscommunication.
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