When, Where and One Unanswered Question on Data Virtualization

Loraine Lawson
Slide Show

Top 10 Benefits of Virtualization

Virtualization has taken a firm hold at most enterprises these days, but the fact is we've only just begun to unleash the true potential of the technology.

At a minimum, a journalist is supposed to answer four questions in every article: who, what, when and where. Yesterday, I looked at the who and what of data virtualization. Today, let's examine the when and where - and then look at one question I can't pin down.


When would you use it? Data virtualization comes in handy for all those pesky little integration projects you just can't seem to get to. In fact, Forrester Research says those projects are a great stepping stone for introducing data virtualization into your organization. If it doesn't require ETL, then you should consider data virtualization, according to a recent study by the research firm. Forrester sees it as a great alternative to both expensive data marts and ETL.


"Integration by ETL creates data quality problems and delays information delivery," wrote analyst Brian Hopkins in a recent study. "Integration by DBMS consolidation is high impact, expensive, and risky."


But data virtualization vendors - not surprisingly and without a hint of self-consciousness - advocate broader adoption. Why choose, questioned Robert Eve, vice president of marketing at Composite Software:

My answer often surprises them because this is not an either-or situation: data virtualization should be a ubiquitous layer in your infrastructure that all data consumers use to access enterprise data. ... In other words, the answer to the question is that you should (almost) always use data virtualization, and sometimes you may also need to use ETL and other data integration strategies.

So, apparently, when is somewhat open to interpretation. I think our next "W" can help shed more light on the general question of use.


Where do you use data virtualization? I haven't read anything that restricts where you might use data virtualization in terms of an organization's size or focus. I can tell you it seems to be best for those with business end users or analysts who need access to real-time data.


While I found no restrictions, I did find several examples of where it can really help with other tech-related investments. For instance, it happens to be a perfect fit for those organizations that have or are pursuing a service-oriented approach to architecture - that's right, I'm talking about SOA. Long, long ago, SOA and data integration expert David Linthicum wrote that he thought data integration was a problem area for SOA, but now he and other experts agree that data virtualization goes with SOA like peas and carrots.


"Data is more logically grouped to make that data more useful, which this has been the promise of SOA for years," Linthicum writes. "An SOA with a data services layer is a valid architectural approach to dealing with both underlying business processes as well as sets of services."


It also works well with master data management, cloud and increasingly, Big Data, according to a recent Composite Software whitepaper outlining the five most popular use cases for data virtualization.


It's apparently now popular in the life sciences field, where pharmaceutical companies are using it to gain insights into research data.


That's the who, what, when and where of data virtualization. You'll notice why isn't one of the four W's, but I think in this case, the four basic W's go a long way to explaining why you might pursue data virtualization.


So what's my unanswered question? Simple: What are the cons of this approach? Nothing is without tradeoffs, and while a recent TechTarget article briefly mentioned concerns about security, privacy and regulatory compliance, I couldn't find anything that really drilled down on these issues. That just doesn't sit well with the journalist in me. Hopefully, we'll soon hear more about the caveats to data virtualization as the hype cycle progresses, so you can go into it with not just the who, what, when and where, but an idea of the problems you might encounter.

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Add Comment      Leave a comment on this blog post
Jul 7, 2011 9:12 AM Ash Parikh Ash Parikh  says:


Great article

A key aspect that needs on-going clarification is that simple, traditional data federation is not data virtualization. Data virtualization is all about hiding and handling complexity. Dealing with enterprise data is a complex proposition which calls for rich transformations and not limiting the user to SQL or XQuery only transformations. Additionally, simple, traditional data federation assumes that the data in the backend data stores is ready for consumption - that it is of good quality, which is not the case. You cannot just propagate bad data in real-time and then loose the advantage gained to post-processing. You need to do these complex transformations including data quality on the fly, on the federated data.

As you know, Informatica recently released the latest version of its data virtualization solution, Informatica Data Services version 9.1, as part of the Informatica 9.1 Platform.



Key highlights for this release are:

The capability to dynamically mask federated data as it in flight, without processing or staging, just like what we were doing with the full palate of data quality and complex ETL-like data transformations before. This is helping end users leverage a rich set of data transformations, data quality, and data masking capabilities in real-time.

The ability for business users (analysts) to play a bigger role in the Agile Data Integration Process, and work closely with IT users (architects and developers), using role-based tools. This is helping in accelerating the data integration process, with self-service capabilities.

The ability to instantly reuse data services for any application, whether it is a BI tool or composite application or portal, without re-delpoyment or re-building the data integration logic. This is done graphically in a metadata-driven environment, increasing agility and productivity.

Here is a demo and chalk talk:




Ash Parikh

Jul 7, 2011 1:00 PM Suresh Chandrasekaran Suresh Chandrasekaran  says:


These articles shed light on the growing need to integrate with agility and across the full spectrum of data and information - internal and external to the organization.

Denodo Technologies, a Data Virtualization leader and also mentioned as  leader in Forrester Research 2010 Information-as-a-Service WAVE, finds that there are several use cases now for Data Virtualization beyond the traditional Agile BI and Data Warehouse extension to integrate Structured and Unstructured / Web / cloud data.

This conversation with analyst Robin Bloor highlights both the challenges of traditional data integration overcome by data virtualization and newer uses to integrate big data, cloud and social media with traditional enterprise data in a unified data services layer - http://www.thevirtualcircle.com/wp-content/uploads/downloads/2011/04/BR-10-10-Denodo.pdf

This series of short videos highlight several real-world customer uses of the Denodo data virtualization platform for call centers, agile BI, operational BI, virtual MDM, Web/SaaS integration and more http://www.denodo.com/en/resources/demos/index.php?n=l


Suresh Chandrasekaran, Denodo Technologies

Jul 7, 2011 7:01 PM Robert Eve Robert Eve  says:

Loraine -

Your series of three articles on data virtualization are a good service to the ITBusinessEdge community.  Not only did you provide a high level perspective via the Forrester Data Virtualization research report, your who, what, when and where approach provided the 360 degree view your readers appreciate.

For those interested in reading the Forrester report "Data Virtualization Reaches Critical Mass, Composite Software has secured reprint rights and have made it available as part of the Data Virtualization Leadership Series. http://www.compositesw.com/resources/data-virtualization-leadership-series/

- Robert Eve, Composite Software


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