How Do We Know If We Are Ready for Data Virtualization?

Since helping launch the data virtualization market in 2006, I have interacted with thousands of organizations. A common question across these conversations is “How do we know if we are ready for data virtualization?”

What these organizations are really asking is: “When do we know if our existing data integration tools are holding us back?” Socrates and other great philosophers encourage us to “look within to find our answers,” however, I’ve found the best way to answer this question is by asking another – in fact, several.

I would argue that data virtualization adds a key set of missing capabilities to an organization’s data integration toolbox, and without it, chances are your organization is not reaching its full potential. A claim like this requires deeper questioning, wouldn’t you agree? Let’s explore further.

First Principles of Data Integration

We all understand the first principles of data integration: data exists in silos; integrating it adds value; but integrating it is difficult. It requires business and technical understanding, skilled resources, infrastructure, tools, and time – all of which are dear in today’s competitive environment.

As such, organizations are smart to consider anything that reduces data integration time and resources. Forrester conducted a Total Economic Impact study to evaluate the financial impact of investing in the Cisco Data Virtualization solution, and concluded organizations can achieve up to 346% ROI. Let’s take a look at some common situations that lead teams to data virtualization and its benefits.

Your (Seemingly) Endless Data Integration Backlog

You know you’re ready for data virtualization when your data integration backlog is delaying realization of your business opportunities.

To better understand the impact your existing approaches are having on your business, ask:

What revenue enhancement, cost & risk reduction, and/or compliance opportunities are being delayed due our data integration backlog?

Which opportunities are we bypassing altogether for the same reason?

What more could we do if we could accelerate data integration development by 3-4 fold?

How much faster might we realize M&A synergies if we could integrate both organizations’ data sets sooner?

To the Hammer, Everything Looks Like a Nail

For dimensioned data sets, large-scale historical analysis, and a myriad of other data integration challenges, the tried-and-true ETL/Data Warehouse-based approach to data integration is a perfect solution.

But should every data integration problem require the same solution? You know you’re ready for data virtualization when you wisely consider that data virtualization takes a far less resource-intensive approach to appropriate integration problems.

As you look at your upcoming projects, ask:

Are your requirements firm or are you actually operating in rapid-prototyping mode?

Will most of your queries be wide and shallow resulting in light loads on source systems?

Are your source data sets already too large to physically integrate?

Does your data reside outside your firewall (SaaS apps, third party data services, etc.) and thus preclude physical integration?

Is some of the data changing so rapidly that the batch ETL runs can’t keep pace?

Taking Advantage of Data Infrastructure Opportunities and Data Governance Mandates

You know you’re ready for data virtualization when your existing tools are keeping your organization from leveraging new data infrastructure opportunities and data governance mandates.

Ask your organization:

How can we gain by mixing and matching lower-cost big data infrastructure, high-performance analytics infrastructure, traditional ETL, the cloud, and more?

What could we save from a reduction in rogue, replicated, dependent data marts?

How might we better comply with regulations that limit data replication and crossing of national borders?

From Philosophers to Physicists

Albert Einstein once said, “The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.”

Answering these questions will help your organization change its thinking about data integration. Your organization will be ready for data virtualization when you do.

Do you think you’re ready for data virtualization? Take our short assessment to find out.