In this podcast Jeff Overton, the Shadow Product Marketing Manager from Progress DataDirect, explains how Shadow 7.2.1 helps the mainframe support new initiatives like next-generation business intelligence. This podcast runs for 2:52.
You may listen to the podcast here: http://blogs.datadirect.com/media/Shadow_7.2.1_Release_BI.mp3
Business intelligence or BI is an area that we’re seeing a lot of traction in the marketplace. Again, organizations are looking for one single source for the truth. They’re looking at how they can achieve the dashboards that they’re looking for to help them identify what’s going on in their business, both from an internal and an external perspective. But Shadow can help with business intelligence initiatives in a number of different ways. One way is if the organization is looking at low-latency data where they need the ability to provide real-time operational data, very quickly and that mainframe data resides in the mainframe, the ability to access it in one place provides significant advantages. And as we talked about before, the ability to do so through ANSI SQL92 expands the pool of available business intelligence solutions that can be used.
So, in one scenario business intelligence can benefit from 7.2 with our enhanced support for ANSI SQL92 access to mainframe data. Now, there are also real reasons why business intelligence initiatives may be using distributed data warehouses or operational warehouses, and, in that case, Shadow’s capabilities for Change Data Capture (CDC), what we call our Shadow z/Events products, can be a significant benefit. Why? Because with Shadow z/Events, it’s a noninvasive way to specify the data change events that we want to capture. And that can span whether it be Adabas or VSAM or DB2 or IDMS or even IMS DB. And so you can capture the events that occur in these critical data environments on the mainframe, and not only can you capture them but with persistence, to make sure all the changes are captured regardless of what’s going on, you then have the ability to inspect those change data capture events, look at them for context, enrich them if necessary, and then transform them into an XML representation, and then publish those out so that you can then load this into your operational data warehouse, or pass it onto some other downstream process that utilizes this data.
So, there are a number of key ways in which we can support business intelligence. Again, direct SQL access to relational and non-relational data on the mainframe, particularly attractive when you’re dealing with business intelligence initiatives that have low-latency and perhaps higher-volume requirements. And then the ability to capture mainframe change data events and propagate those out to a distributed environment.
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