From the post:
The first in our Centerprise Best Practices Webinar Series discusses the features of Centerprise that make it the ideal integration solution for the high volume data warehouse. Topics include data quality (profiling, quality measurements, and validation), translating data to star schema (maintaining foreign key relationships and cardinality with slowly changing dimensions), and performance, including querying data with in-database joins and caching. We’ve posted the Q&A below, which delves into some interesting topics.
You can view the webinar video, as well as all our demo and tutorial videos, at Astera TV.
Very visual approach to data integration.
Be aware that comments on objects in a dataflow are a “planned” feature:
An exteremly useful (and simple) addition to Centerprise would be the ability to pin notes onto a flow to be quickly and easily seen by anyone who opens the flow.
This would work as an object which could be dragged to the flow, and allow the user enter enter a note which would remain on-screen, unlike the existing comments which require you to actually open the object and page to the ‘comments’ pane.
This sort of logging ability will prove very useful to explain to future dataflow maintainers why certain decisions were made in the design, as well as informing them of specific changes/additions and the reasons why they were enacted.
As Centerprise is almost ‘self-documenting’, the note-keeping ability would allow us to avoid maintaining and refering to seperate documentation (which can become lost)
A comment on each data object would be an improvement but a flat comment would be of limited utility.
A structured comment (perhaps extensible comment?) that captures the author, date, data source, target, etc. would make comments usefully searchable.
Including structured comments on the dataflows, transformations, maps and workflows themselves and to query for the presence of structured comments would be very useful.
A query for the existence of structured comments could help enforce local requirements for documenting data objects and operations.