Data Made Visual With A Data Virtualization Tool

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Data virtualization is becoming more important as companies transition to work in today’s fast-paced, cloud-based economy. Having a data virtualization tool means that you will have a way to access your data sources virtually no matter where you are or when you’re looking to pull specific datasets. This can be particularly powerful if you currently have lots of disparate sources of data in different data silos or data lakes.

When your data is spread out, you don’t get the full picture, which can be detrimental to your overall business practices. Think about a puzzle that your company is trying to solve, but the picture on the box has been cut up and put in five different places. That analogy perfectly exemplifies why data silos can be harmful to the way your business operates, and why adding a layer of data virtualization is so important to unifying your data from disparate sources.

Beyond improving your business intelligence efforts, data virtuality has other benefits, too. One great thing about getting your data source virtualized is that it allows for different kinds of queries and analytics to be leveraged within your overall source system. This means that data virtualization tools have a lot more to offer than just connecting various data sets, which, in turn, means that the data virtualization software you select as the foundation of your business actually matters quite a bit. Learn more about data virtualization and how it can even add a visual element to your business’ data warehouse below.

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Graphical modeling helps developers better use your database.

Especially when dealing with business data, the insights that various analysts can glean from your data tools are crucial. Unstructured data can be overwhelming, and data virtuality helps to put all of that data in the right place; however, you still need data services that add a visual element to big data if you want to be able to fully leverage different data models.

A good data virtualization tool will thus add a visual component via graphical modeling so that organizations of any size can have real-time access to develop and optimize different queries. If you don’t have knowledge in SQL, XSLT, or different Java functions, many times the graphical tools will allow you to create different data services and views without even having the coding knowledge to do so. This means that business users don’t need to be experienced data scientists or developers with coding knowledge in order to get the most out of your data virtualization platform.

Intuitive user interfaces ensure everyone can benefit from data virtualization software.

Having an intuitive user interface goes beyond graphical modeling, too. When data virtualization users are able to use a data virtualization solution, that’s when digital transformation can really start to occur. If the platform you’re using is confusing, then it doesn’t matter that you’ve linked up disparate data sources in a virtual layer on top of the architecture of your traditional data integration. However, when users of all backgrounds and in a variety of roles is able to search, browse, and preview specific datasets, your tool becomes infinitely more useful.

As such, it’s important that the visual user interface for your virtual data integration software really helps users visualize and work with data if you want to make the most of your data virtualization solution Without an intuitive visual way to work with available data, you increase your risk of data errors and reduce the likelihood that an employee will take advantage of the self-service access your platform offers. To fuel your digital transformation, you need to ensure that everyone’s workload can embrace the insights offered by data virtuality.

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Source@techsaa: Read more at: Technology Week Blog