How to Choose the Best Data Virtualization Solution For Your Enterprise

As more and more companies work to future-proof their operations, data virtuality is becoming increasingly important. This is because data is the backbone of a strong organization, providing analytics and business intelligence insights in myriad ways. Your business data may come from a variety of databases and disparate sources, and data virtualization can help you add a virtual layer that increases access to your data sources with minimal overhead. This can ultimately help you use your enterprise data in exciting and dynamic new ways since unstructured data or disparate data sources just make leveraging big data much more difficult.

 

What should you look for in a data virtualization solution, though? Of course, every business will have its own needs, so it’s a good idea to consult with any data scientists you employ to learn more about what they’re looking for from data virtuality and upgrading your architecture. That being said, if you’d like to spend less time comparing vendors and more time focusing on getting your source system set up with a data virtualization platform, there are a few different features that you should look for as part of your baseline research. Keep the following features in mind as you’re looking for the best data virtualization tools for your enterprise business.

Look for data virtuality tools that eliminate data silos.

Look for data virtuality tools that eliminate data silos.

A major component of data integration is having a repository that has all of the correct data in real time. Data virtualization tools can help with this by getting rid of duplicate data or disparate data sources and unifying your system. From connecting data lakes to connecting cloud sources, the best data virtualization solutions will enable you to connect your data while providing real-time access that helps organizations of any size improve their business processes.

Find a data virtualization solution that offers a powerful user interface.

Find a data virtualization solution that offers a powerful user interface.
It doesn’t matter how powerful your data virtualization tool is if it’s not easy to use. Evaluating user interface may depend on having a team of staff members who can speak to how different features intersect with their unique use cases, but there are a few key features that you should look for as you shop around for the right data virtualization tool. A graphical modeling environment for developers and a self-service web-based user interface are two things that the best data virtualization tools offer in order to ensure their platforms are easy-to-use and effective.

Embrace a data virtualization tool that gives you control of security.

Security is becoming a hot topic as of late, especially as it relates to data. Customer data, in particular, requires a lot of different layers in terms of governance and security, particularly if you store sensitive information like credit card numbers or medical details in a data lake or a data warehouse. As such, anytime you’re introducing a new layer into your data architecture, it’s crucial that you find tools that give you features like traceability and robust authorization or authentication tools. Having these features enabled can ultimately help you prevent bad actors from accessing your data, and allows you to trace problematic data pulls to a source user, too. The result is a much more secure approach to your data than you might get through traditional data integration.

 

Picking the right software is important for your success, whether you’re evaluating a social media management tool or enterprise-level data virtuality. As such, it can be helpful to have guides to help you narrow down your search. Spending less time looking at different vendors means you’ll ultimately get more insight into the data virtuality services you’re evaluating, meaning that you can get started with virtualization much sooner. Keep the above features in mind, and your data management will be quite streamlined.

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