Here's how you can establish trust and confidence while delegating in Data Warehousing.

Encourage cross-functional collaboration, especially between data engineers, analysts, and business stakeholders. Offer training opportunities and provide support resources to help team members develop their expertise in areas relevant to their responsibilities, such as SQL, ETL tools, data modeling, or data visualization.

I think Data warehouse should be treated as a Data Product. Just like how Data Products have a clear roles as Data Owner, Data Product Manager , Data Stewards , QA, Technical Data Architect, Business Architect and Business Data SMEs , Data warehouse needs these roles in order for that journey to be successful. Based on these roles clear RACI has to be defined . Each interaction, roadmap and plan should follow this RACI. Each Leader here can have his/her leadership style and way of driving their effort, but it is key to have frequent and often interaction between these leaders to discuss inter-workstream dependancies ,priorities and other issues . They should begin with few use cases which will give good Technical ,Business Architecture

In every project, team member roles and responsibilities are to be briefed and encourage them to follow it. Establish a trusted relationship within team irrespective of roles. This prevents confusion and chaos when things didn’t go according to the plan.

Establishing clear roles within a data warehousing team is crucial for efficient delegation. Each member should understand their responsibilities, from ETL processes to analytics and reporting. Clear delineation prevents overlap and confusion, fostering trust and ownership of tasks. This enhances efficiency and harmony in operations. Effective delegation hinges on role clarity, empowering team members to excel in their designated areas.

This can include regular meetings or check-ins with team members, providing opportunities for feedback and suggestions, and being transparent about any issues or challenges that arise. It’s also important to create a culture of openness and trust, where team members feel comfortable sharing their ideas and concerns without fear of judgment or retribution.

Create a safe space where team members feel comfortable raising concerns without fear of judgment. As a leader or manager, lead by example by demonstrating open and transparent communication in your interactions with the team.

Create an environment to collaborate within team and foster them have an open discussion irrespective of roles. Situation can be handled very well with open talk when there is an issue with data handled by various teams. Team members feel safe to take risks and be vulnerable in front of each other, as part of psychological safety within the team.

Open communication is vital in data warehousing to build trust. Teams should feel free to share updates, challenges, and successes. Regular meetings and an environment where questions can be raised without fear foster transparency. This allows for intervention when needed, ensuring the health of data processes. Embracing open communication cultivates a culture of collaboration and accountability, enhancing overall efficiency and effectiveness in data management.

Foster a culture where team members feel safe to share challenges, successes, and innovative ideas. By creating transparency with regular meetings where team raise without fear ensures that you're aware of the health of your data warehousing processes.

Implementing comprehensive training programs is crucial for fostering confidence within your data warehousing team. Ensuring everyone is well-versed in the latest technologies and best practices enhances their ability to tackle complex tasks. Training should encompass technical skills, problem-solving, and communication, empowering team members to navigate challenges autonomously. Well-trained teams require less oversight, facilitating smoother delegation and bolstering overall efficiency in data management.

Some must have topics to include in training programs could be: * Introduction to data warehousing concepts and technologies * Data modeling and schema design * ETL (Extract, Transform, Load) processes * Data visualization and reporting * Data quality monitoring and maintenance * Data governance and security * Claims decisioning workflows * Feedback loop management

Encourage peer-to-peer mentoring, group discussions, and knowledge-sharing sessions to facilitate learning and skill development across the team. Encouraging collaboration enhances team cohesion and collective expertise.

Encourage teams to spent time (some hours) on training in every week and have informal demonstration what they have learned to team members. This will help the team to get a different perspective from other team members in any topic. Tasks can be done quickly with quality when the team aware of the tasks.

By providing comprehensive training, you empower your team to tackle challenges head-on, armed with the latest technologies and best practices. Effective problem-solving and clear communication are equally essential, especially when navigating complex data landscapes. Comprehensive training programs adds more value.

Set up alerts for predefined thresholds or conditions, such as system downtime, data quality issues, or performance degradation.

* Streaming dashboards / automation as much as possible * Built-in logging directly in the Spark UI as an example * Failure alerts on jobs running streaming workloads * System tables such as Audit Logs, Billable Usage System Table, and Lineage Sytem Table * Live Query Profile * Ganglia dashboard at the cluster level * Integrated partner applications like Datadog for monitoring streaming workloads * Also there are open source options like Prometheus and Grafana and several more that should be explored.

Establish a process to follow the timeline and raise if something goes outside the plan. Always have a dashboard to visualize plan, progress, defect status, servers’ availability, and team capacity as well.

Promote “Feedback as a gift” theme within the team and have the possibility to give and receive feedback. Setup a process to follow up whether the feedback improved their roles, tasks, and team togetherness.

regularly checking in with team members to gather their input and suggestions, as well as providing opportunities for them to share their concerns and challenges. By actively listening to the feedback of the team members, it allows you to identify areas for improvement and make necessary changes to ensure that everyone is working towards the same goals

Promote “Feedback as a gift” theme within the team and have the possibility to give and receive feedback. Setup a process to follow up whether the feedback improved their roles, tasks, and team togetherness.

Implement a 360-degree feedback mechanism where team members receive input from peers, managers, and subordinates. Timely feedback allows team members to address issues promptly and make necessary adjustments to their work.

* Identifying potential risks and threats to the data warehouse * Implementing security measures to mitigate those risks * Establishing a disaster recovery plan to minimize downtime and data loss in case of an unexpected event * Monitoring and "periodically testing" the disaster recovery plan regularly to ensure that it is effective * Conducting regular audits to identify any potential issues or vulnerabilities * Implementing best practices for data governance, such as establishing policies for data quality and accuracy * Providing training and resources to team members on risk management and security * Continuously reviewing and updating the risk management plan to reflect changes in technology or business requirements

Empower team members to identify, report, and address risks as they arise, and provide clear guidelines for escalation and decision-making.