InetSoft Webinar: Virtualized Data Warehousing

Below is the continuation of the transcript of a Webinar hosted by InetSoft in November 2010 on the topic of Agile Data Access and Agile Business Intelligence. The presenter is Mark Flaherty, Vice President of Marketing at InetSoft.

Mark Flaherty (MF): And that’s where you need to think through your metadata and semantic abstraction layers. What do you rollout that can unify at least there is a metadata for structured, semi-structured, unstructured information so you can, for example, access data not just at the records level, but also if it happens to be text, and if the sources are text, how can you access it through semantic approaches that allow you to determine the concepts and taxonomies and do searches and manipulation of information using that sort of metadata?

So in order to start, you need to think through the semantic abstraction and the approaches that help you to bring this all together. And really in terms of normalizing it and reusing it in a broad range of applications like BI, you start to need to think through the policies and rules governing how this information in various formats, implementing various schemas can be, what policies and rules are relevant to orchestration of the integrations and the transformations and the calculations and so forth.

View a 5-minute demo of InetSoft's business intelligence software, a small footprint BI platform with data mashup functions that permit virtualized data warehousing.

You need to think through the discrete rules that will govern the ongoing reuse of these data blocks throughout your architecture. Think through the requirements of our customers datasets, customer facing applications for keeping track of who the customers are, presenting a 360 degree view of them to drive and feed into customer service and sales and marketing and the like.

So as you are working through your agile data access strategy, you need to organize it and think it through by the subject areas essentially of the underlying data sets and applications and the underlying business processes. So think it through roughly the same way you traditionally thought it through in building out a multi-domain subject-oriented data warehousing environment. Think of it essentially as almost virtualized data warehousing and I am using in the loosest sense.

It’s very important as you build out these subject areas that all of these subject areas are leveraging common data, common schemas, common hierarchies, common calculations and so forth so that when you are building out these disparate subject areas, none of them are silos. They are all leveraging a common pool of agile data access artifacts and models, and fundamentally they are all leveraging a common set of source connectors and source applications so what you want to do is go towards agile data access.

More Resources:

		Data Mashups vs. Data Warehouses
		Business Intelligence without ETL or a Data Warehouse
		The Three Tenets of InetSoft's Agile BI Philosophy
		How to Create a Sound Business Intelligence Strategy