Who is this article for?Coruson administrators or data scientists.
Access keys for Galileo are required.
Users submit data into Coruson (such as completing audits or submitting reports) and so administrators or senior management will often require analytics to be performed. Coruson has a number of options available for retrieving data to perform analysis.
This article outlines the steps required to begin using Galileo, Ideagen's data warehouse, as part of your business intelligence, and also provides some initial steps on connecting via Microsoft PowerBI and Postman. This does not provide details on specific steps on how to perform the data analysis as these steps vary depending on the tools you use.
To make Galileo easier to learn, this article is split into 3 sections so that you can either walk through the steps in sequence or you can jump to the section relevant to what you are doing with Galileo:
1. Introduction to Galileo
Galileo is a Coruson data warehouse. It has been designed to surface the data in ways that help to provide good performance on complex queries and expose related data in an efficient manner.
Galileo uses database views to present the data to users. Some of these views may be able to provide all the data required by a user for their reports, while others will allow complex data to be pulled from multiple locations (e.g. fetching a unique ID from one view and using it to pull associated data from another).
The analysis can be performed by connecting to Galileo and performing your queries or you can load the data into a larger database system for more extensive querying or for integration with data collated from other systems.
Important: Galileo does not provide real time data from Coruson. However, the day refreshes frequently throughout the day so that the data will feel "fresh" when performing an analysis.
2. Galileo Vs Other Coruson Analytic Options
Galileo is one of many options available for performing Coruson analysis however it is the one that is most frequently refreshed with the greatest access to data:
| Galileo | Jaspersoft | Javelin | Data API | Platform API | |
|---|---|---|---|---|---|
| Refresh Frequency | Continually | Approx. 2-3 Time Per Day | Once Per Day | Approx. 2-3 Time Per Day | Live Data |
| Coruson Data Available | All Modules | All Modules | All Modules | Reports & Documents | Reporting and forms only |
| Connectable Tools | Power BI Postman Excel |
Jaspersoft Only | Any tool capable of injecting CSV exports | Any tool capable of API queries | Any tool capable of API queries |
| Connection Method | Dedicated API | Jaspersoft Web Interface | Daily download in CSV form | Dedicated API | Dedicated API |
| Cost | Free of Charge 1 | Daily Rate Implementation | Free of charge | Free of Charge1 | Free of Charge |
| Data Limit | 50Gb Daily 1 | No Limit | No Limit | No Limit 2 | No Limit 2 |
| Implementation Services | None | Construction of Views Updates for New Forms Updates for Form Changes |
None | None | None |
| Support Availability | Connection Bug Triage |
View Management | Export Management | Bug Triage | Bug Triage |
- Data usage limits apply. Additional data bundles can be purchased from your account manager.
- There is no limit to the amount of data that can be returned but poorly performing queries can lead to a query timeout.
3. Galileo Structure
Galileo presents the Data Warehouse as a collection of database views, formatted to match both the underlying tables, and through composite views that show the data pre-joined in useful, common reporting formats. As a result, it is possible to create more complex reports with little effort.
- Base table views: In Galileo, the base data is presented in views with the same names and definitions as the underlying base tables.
- Hierarchies: Hierarchies are presented to the user as views. They are easy to search and not restricted in depth. They can also be easily used in other queries to return data related to rows in the hierarchy.
- Fact views: Fact tables are the central premise of Data Warehouse designs and will likely be very large and complex. In Galileo, these Fact tables have been implemented as Fact views that, while still returning the same data, can be modified to make them less complex and more efficient.
In Galileo we have also created selective modular fact views that will allow users to create composite queries that only look at the parts of the main fact view that they are interested in.
Example: If the user wishes to look at workflow associated with a report, the query joining to the large Report_Fact table means that we are retrieving a lot more data than is needed to just analyse Workflow. The subset will still be returned but much more slowly than necessary. Instead, the user has access to a modular view (Report_Fact_Workflow) which returns only the data associated with Reports and the Workflow / Task tables and, as such, returns far fewer rows in a much faster time. This means that the same complex, composite queries can be created as before, returning the same data for analysis, but in much faster yet less complex queries.
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