Mosaic, a top artificial intelligence consulting firm, is uniquely qualified to support firms in the recommendation of a data architecture with our extensive knowledge of end-to-end analytics solutions. Mosaic understands that the analytics tools needs to support the use case and organization. Mosaic uses insights from various workshops, interviews and interactions to provide recommendations for a distributed data storage system that maximizes ease of use and increases time to insight. Mosaic can configure infrastructure for both BI and advanced analytics and provide self-service tools for business users. The data architecture will capture and share metadata & usage while showing value of seamless data integration.
The data lake/data warehouse process must take a holistic approach for all stakeholders, and this process requires collaboration between IT and business units, while requiring governance to ensure success. Timing and scheduling of operational workflows need to be designed with the end user in mind.
The analytics tool platform much match and support the entire data-to-analysis lifecycle. Analytics should be integrated into business process and workflows, with a documented use case identification process gated by a data custodian and steward team. A center of excellence (CoE) should standardize on a small set of analytics tools until use cases demand alternatives. Technologies should be selected with a growing user community. Best practices include starting small, staying the course with selected tools and continuing to grow. The platform should be able to support open source languages R and Python, and in some cases, a CoE can build momentum using various libraries in these tools. The CoE could, for example, adopt an open-source (R & Python) analytics engine based approach, plugging model outputs into a self-service dashboarding platform, allowing business users to dig into the data.
A CoE will need to manage repository operations such as backups, replication and recovery while planning and managing dynamic repository lifecycle, including scaling and performance tuning. This team will also be responsible to manage repository security, including user authentication, authorization and management.