Key Considerations When Deciding on Data Virtualization

Key Considerations When Deciding on Data Virtualization Reading Time: 2 minutes

As you modernize your data architectures, you must consider these two truths.  First,  today’s diverse, distributed data environments are the new normal. Second, trying to centralize all their data in a single location is a fools’ errand.

How can you modernize your data architecture to turn these truths into your advantage?

Today’s Data Topology 

• On-premises, cloud, hybrid, and multi-cloud are just some of the locations where your data is now stored. Each provides value in an increasing data driven business climate. 
• Today’s best compute and storage options will be surpassed tomorrow. But the long tail of your legacy data silos will continue far into the foreseeable future.
• On the consumption side, your demand for data has never been higher. Reports, dashboards, self-service analytics, data science, and more are nothing without data. And preferably data that has already been integrated across these increasingly siloed environments.

To keep pace, you need agility and flexibility in your data architecture. You need to mix and match data integration styles to bend and blend their data for each unique business need. And you need to meet your organization’s growing demand for data quickly and reliably. 

Data Virtualization Rises to The Challenge

Data virtualization provides a comprehensive approach to managing, accessing, integrating, and providing data to drive the insight required to delight your customers, optimize your business processes, and accelerate your innovation. It has become a critical element in your modern data architecture. And it is essential in speeding up development, increasing data reuse, reducing data replication and movement, and breaking down data silos. 

The agility and flexibility of data virtualization combined with the reliability of traditional forms of data integration such as ETL, enables you to derive higher value from your data and meet a wider range of use cases.

Data virtualization provides a comprehensive approach to managing, accessing, integrating, and providing data to drive the insight required to delight your customers, optimize your business processes, and accelerate your innovation. Click To Tweet

Getting Started with Data Virtualization

Sounds good right! But does data virtualization make sense for your organization?

To answer this question, you would need to understand:

• Business problems data virtualization best addresses
• Data integration use cases where data virtualization is the best match
• And technical considerations that data virtualization newcomers must address

This whitepaper will provide data architects, data engineers, business analysts, and developers with guidance they can use to gain the required data virtualization understanding. And this blog provides the guidance they can use to fund their data virtualization investment.