How to bolster asset management efficiency using analytics platforms

Industry has installed sensors everywhere, built data warehouses and established remote technical facilities for centrally locating engineers and other personnel, collectively subject matter experts (SMEs). [...]the company's grand idea of co-locating key SMEs panned out, but it unearthed a rampant issue in the interim regarding how data was collected and managed. Another occasional pitfall is deploying Python or another programming language to structure data, but this skillset is typically confined to data science groups. Because it is not readily available to all teams, this can lead to maintenance and sustainability challenges of the code as time goes on. Organizing data into an asset tree in these types of software platforms empowers users to: * Use asset swapping to rapidly create identical visualizations for different pieces of equipment. * Write high-value calculations for components, then scale them across all similar components in the tree. * Automatically generate scalable content and custom analyses. * Reference the tree as a starting point for roll-ups, calculations, displays, dashboards and reports.