Canner Enterprise Cloud Pros and Cons

The fact that its web based makes it difficult to access. The learning curve is not designed to provide an user experience. There are aspects of Canner Enterprise Cloud that are not good at all. Review collected by and hosted on G2.com.

The platform doesnt provide customization options, which limits flexibility for businesses with data requirements. The user interface feesl overwhelming for users at first as there is a bit of a learning curve involved. The pricing structure isnt as transparent as we would like making it difficult to plan for the cost of the service. Review collected by and hosted on G2.com.

Canner Enterprise Cloud has a web based interface, which makes it difficult to access. The user experience is obstructive making it difficult to navigate and get the hang of. Review collected by and hosted on G2.com.

It lacks features for cleaning up and removing data. This hinders decision making processes. The user interface of the platform isnt very intuitive which means new users face a learning curve when getting started. Review collected by and hosted on G2.com.

Canner Enterprise Cloud has been instrumental in helping us streamline our data management processes, by providing a centralized platform that enables us to unify data from different sources and eliminate data silos. As a result, we have been able to significantly reduce the time and effort required to access and utilize data across our organization. Review collected by and hosted on G2.com.

None!

This is a helpful data platform that our user or data scientist could save their time and effort to process or get correct data. Review collected by and hosted on G2.com.

Cross-departmental database pipeline integration and automation: Previously, data analysis required 1-2 weeks of preparatory work, with an additional week for data retrieval requests. With the improvements, we can now update and process data immediately without human intervention, shortening processes and reducing personnel costs.

Redefined responsibilities and working areas for data analysts and systems: Revenue data is highly confidential, especially in core systems' databases. By implementing the virtual hub, non-accounting personnel and systems can only connect through it (read-only), with separate working areas and records. This enhances data control and meets compliance requirements.

Established lightweight Data Marts: Creating Data Marts is critical for data analysis but traditionally involved complex integration and normalization operations. With the virtual hub, each unit's systems can build their own Data Marts within authorized work areas without impacting others. This reduces redundant databases and decouples data layers.

Accelerated data access speed: Legacy systems with outdated data structures only provided limited access and often caused delays. By redesigning the systems and structures and leveraging the aforementioned processes, we significantly improved the speed and scope of data queries, enhancing user experience and reducing development time. Review collected by and hosted on G2.com.

The interface can only be accessed through the web, and we aim to optimize the user experience and learning curve in terms of usability. Review collected by and hosted on G2.com.

Real-time data ingestion and simplify complex data structures. It also helps eliminate data pipeline. Review collected by and hosted on G2.com.

Nothing to say as of now.. it's amazing tool. Review collected by and hosted on G2.com.