Here's how you can mitigate the risks of poor collaboration in data architecture projects.

Definitely an important step - in understanding who does what and having a RACI to enable transparency & easy access to each other. Agree on the RACI upfront and divide the work break down of tasks amongst relevant roles.

Ideally, you're working in a governed environment, so there's been an identification of who's involved and what everyone does. That's important to make sure that you're not working in isolation. It can be easy to think that it's complex and you have the expertise, but if you haven't spent enough time reviewing the design with the business, you might not have accomplished meeting the business needs. You have to be able to clearly communicate so they understand and can point out any potential issues they see.

Très utile. Il faut aussi conna?tre l'expertise des différents intervenants et leur valeurs. Ceci peut permettre à mieux orienter les répartitions des r?les dans une équipe.

Roles are the building blocks of a successful data architecture project. They act like a blueprint, ensuring everyone involved understands their areas of responsibility (AOR) and how their work contributes to the bigger picture. No more stepping on each other's toes! Clear roles prevent wasted effort and duplicated tasks. Everyone knows who to turn to for specific tasks, keeping the project moving smoothly. Clear expectations lead to less friction and a more harmonious team environment. When assigning roles, consider each team member's unique skills and expertise. This allows you to align responsibilities for optimal project efficiency. By clearly defining roles, ensuring your data architecture project is a well-conducted masterpiece.

Think of SMART goals as guideposts on your data architecture journey. By setting clear goals, you create a shared vision for the project. Benefits of SMART goals: Everyone is working towards the same objectives, fostering collaboration and synergy. Clear goals with achievable targets keep the team engaged and invested in success. SMART goals help prioritize tasks and keep the project on track. Effective communication is key. Clearly communicate SMART goals to all stakeholders involved. Regularly revisit and discuss them as the project progresses to ensure everyone is on the same page and adjustments can be made if needed. With well-defined SMART goals, your data architecture project will have a clear roadmap to success.

Organization objectives percolate down to what each individual needs to do and get the organization there. SMART goals - (Specific, Measurable, Achievable, Relevant, and Time-bound) recorded in a place and measured on a periodic basis - may be quarterly. Data architects need to look at top down approach to supporting these goals. Data engineers will do the converse. All product managers for data products will look at multiple such goal cohorts and collaborate with other business units to revise, enhance the goals from time to time.

In my experience - JIRA, Trello, Git et al. are just tools to have transparent collaboration between people. Useful to help reduce the administrative overhead for each individual. Having the right SOPs in place to utilize these tools may be good way to start if its a large team i.e., > 50 people.