Tidal Explorer™ is a powerful add-on optimization toolkit for the Tidal Automation™ platform. The optional toolkit collects and reports data in graphical representations to facilitate analysis and identification of conditions that can affect the optimal processing of high-volume, complex workloads.
Designed for advanced users, the toolkit’s powerful features can enhance your ability to optimize schedules by illuminating the complexities of workload design structures, schedule performance, and job stream interdependencies.
Transparently identifies changes to Tidal jobs, triggers, and node outages that directly reference a revised calendar. You can immediately see the potential impact of a calendar change on Tidal entities.
Helps you detect variations between schedule components and job structures quickly and accurately. You can see differences in job definitions, job dependencies, and job events. Easy-to-understand graphical views help to highlight differences between in-job structure and dependency chains.
Tidal Explorer™ supports Tidal workload automation database migrations with full-table comparisons of jobmst, jobdtl, jobbed, evntmst and usrmst tables between original and migrated Tidal instances.
Exports Tidal component definitions directly to Microsoft® Excel or XML formats. Adds job structures (including parent and child jobs) and export-related custom metadata to the export process.
Facilitates improved DevOps and controlled Change Management of mission-critical Tidal schedules. You can fast-track the analysis, planning, and communication of schedule changes and new schedule developments to accelerate time-to-value for new workflows. Build your change plans using job hierarchy data, and use our “Compare” function to verify that (1) all planned changes have been made, and (2) there are no unplanned changes.
A diverse suite of standard reports encompasses the breadth of our analytical and collection functions. Reports fall into three categories:
Fast Track Job Failure Analysis and resolution. Streamlines the diagnostic process by:
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