Seneca College faced significant challenges with their existing BI reporting system, which was tied to their ERP implementation. The system had canned reports that were not relevant to their business needs, making it difficult to customize content. Creating and publishing a single report to production took days, which was inefficient. Additionally, executives frequently had ad hoc requests for information that required a fast way to analyze many data elements and explore different metrics on the spot. Each department had specific requirements for performance metrics, necessitating a flexible way to visualize data. Furthermore, data was located in multiple source systems, including their ERP, learning management system, cloud, and custom applications. Without a centralized data warehouse, their next analytics system needed to connect to all their data sources.

The law firm faced significant challenges with its data analytics environment. The firm used point solutions for every part of the business, resulting in a lack of a centralized ERP for operations or a data warehouse as a central repository. This made it difficult to incorporate data from third-party vendors into the analysis, which was crucial for having a unified view of data. Additionally, the existing analytical tools were outdated and overly complicated, requiring analysts to spend many hours manually manipulating data and creating reports and queries. This lack of self-service intelligence in their analytics portfolio further hindered the firm's ability to quickly gain insights and make informed decisions.

The data analytics team faced challenges with complex data and manual analysis, requiring examination of up to 300 variables. The manual process often focused on a subset of data, taking days to complete. The use of multiple discrete tools created friction, as data needed to be moved between applications, complicating workflows. Internal resources were bottlenecks, with some analyses taking up to 5 days.