What is Data Analytics Health Check?

Erroneous and untimely data can lead to reports that are not trusted and therefore rendered useless. By acting on this “dirty” data, organizations are setting themselves up for failure when it comes to data-based decision-making. A health check is a deep dive into the current data analytics state to identify gaps in the data feeds, source flows, data models, calculation, rules and methods applied against the data that impact reporting and dashboards.

Benefiting from Jump Analytics’ Health Check

Jump partners closely with clients to gain a deep understanding of their reporting goals and the current state. By analyzing the current data state, a health check highlights challenges and issues that may be leading to untrustworthy data. Following the health check, a blueprint outlining the next steps in filling the gaps is provided, and our team works closely with our clients to ensure a thorough plan is in place.

Our team has extensive expertise in being able to quickly identify and document root cause issues within data analytics architectures. This allows for a thorough and efficient process which results in a best practice plan that describes how an organization can correct their current state concerns and how they can implement an architecture to support their future data analytic needs.

Data Analytics Health Check