Major Release: OmniFi v9.1

Roundup of features and requested enhancements

OmniFi v9.1 introduces a wide variety of both technical and functional improvements across almost all OmniFi modules, rounded off with a number of requests that we receive from time to time

We know that small improvements can have a large impact, so with more significant changes like additional real-time updates to monitor task progress in Web, we have also included smaller quality-of-life improvements like a test function for email configuration, the ability to search for query types in Query Wizard and much more.

Read on to learn more about what is included in OmniFi v9.1.

Real-time updates of Access Endpoint and DataMart tasks

With v9.0 we introduced real-time updates in OmniFi Web to automatically show progress and status of report executions in web. This was well received, and with v9.1 we now extend real-time to include Access API endpoints and DataMart executions.

Whether you run tasks manually, log in to assess the progress of your daily scheduled runs or to monitor user activity on an API endpoint, the real-time updates lets you monitor the progress at a glance.

Navigation links to table and endpoint usage

Many of the collateral items in OmniFi are interconnected. Tasks run the ETL pipeline to update Tables, which are defined by Models using Data Sets provided by Report workbooks.

One of the core improvements provided by the new web portal in v9.0 was to make it easy to navigate directly between interconnected items. With v9.1 we further extend on this, adding Usage tabs to the DataMart Tables page and the Endpoints pages that lists the tasks related to the selected table and endpoint respectively.

Search for query types

In the category small but significant enhancements, Query Wizard now lets you search for query types.

OmniFi is often connected to several underlying systems, providing access to dozens of different query types. Navigating to find the correct query type can be a hassle, but now you can search for it instead.

Type what you are looking for in the search box, and the list of query types will be filtered to matching items.

DataMart ETL operations data view

For improved transparency into how the Extract-Transform-Load pipeline merges data into your data mart, we have introduced the ability to view data at different stages of the pipeline.

From the table history view or the DataMart task history view, you can navigate to the data view for the Extract/Transform or Load data views. The Extract/Transform data view displays the source data after transformation, and the Load data view describes how the data was merged into the table.

The ability to view data at different stages of the ETL pipeline adds transparency into how the ETL pipeline operates. It is very helpful when designing and testing new data mart models, as well as when validating data consistency of production models.

Full changelog