Today, companies of all sizes and industries have to work with data. Both structured and unstructured. They have to capture, store, process and analyze them. Therefore, the fewer points they have for viewing and management, the better. Especially if they can see and work with them from a single console, and do it in real time. Only then can they achieve a higher level of efficiency. In addition, they have to be able to translate that data, once processed and analyzed, to obtain information that is useful to them. How can they get it? For example, through the data virtualization.
What is data virtualization and how does it work?
Data virtualization is a data management system which refers to compilation of all the information of a company from a single point. Regardless of the source or sources from which they come. For this, a virtual data layer is used that is responsible for aggregating all the data that reaches the management point from its different sources.
The procedure that is followed for the virtualization of data begins with the access to them when they are in their original format and in their source of origin. Unlike the typical processes of capturing and processing data, which go through its extraction, transformation and loading; virtualization does not need to move data to a data warehouse or data lake before starting its process.
Instead, the data is aggregated at a single point, which is the virtual data layer just mentioned. Using this layer, companies can develop simple and customizable views. These views are known as dashboards, and they are used to access the data and discover what makes sense. With these control panels, users can get, in addition to easy access to data, real-time reports, manipulate data and even perform advanced data processing. For example, predictive maintenance tasks.
To make things easier, according to eWeek, there are specific software tools, and platforms, for data virtualization. Many of the major enterprise technology companies, such as IBM and Oracle, have their own data virtualization platforms.
Advantages of data virtualization
The benefits of data virtualization are many. Especially for companies that are in the growth phase. data virtualization enables IT teams to access data in real timeregardless of their source, to improve decision making, increase productivity and reduce overall costs.
The data that is saved in various sources, as we have said, can be structured and unstructured. While the former are generally numbers and other values, the latter are more complex. They can be from video files to data files from Internet of Things sensors, for example.
Analyzing unstructured data can be problematic, but in return, it provides a pretty useful amount of useful information. But the best way to move forward and get information is to combine structured and unstructured data, a process that software and data virtualization platforms are responsible for facilitating.
Data virtualization also eliminates replication, which is necessary when using traditional processes and methods to analyze data. Data replication is an expensive procedure, and requires an increasing amount of storage. Also, it can lead to duplicative data, and even getting bad data, which can screw up any data set.
No replication is needed for data virtualization. The data is kept in its original source, in a virtual layer. This leads to faster access to high-quality data and lower costs to be incurred in achieving it.
On the other hand, this data collection process improves decision making, since it allows obtaining higher quality data. In other words, data virtualization allows for accurate, up-to-date, and logical data. They should also be displayed in such a way that all parties who have to work with the data, or get information, can understand it. This should be so, regardless of your level of technology. Well, data virtualization allows access to the specific data that each person needs and when they need it.
The data they obtain is also accurate and in real time. This leads to complete visibility of the business, and to having data that allows those in charge of making decisions to have the necessary bases and information to be able to do so with confidence. In short: When integrated with data virtualization tools, virtualization software allows users to view real-time data in a way that is easy for them to understand.
Improvements in productivity and cost reduction
Another advantage of data virtualization that improves productivity. And he does it in many ways. The first is the improvement it achieves in terms of access to data. Users do not have to access multiple applications or servers to get them. They have a single resource to view them, get the data they need, and continue working.
In addition, it simplifies the process of data analysis. To do this, it offers a user-friendly interface, which allows even those who are hardly familiar with data analysis to use them, and make business and company decisions quickly. In addition, these self-service capabilities will reduce the workload on IT and data teams.
All of this improves productivity, and makes businesses move faster. In addition, other areas, such as product development, will also benefit from the agility it offers. Infrastructure costs are also lowered thanks to data virtualization. As we have seen, due to the disappearance of the need for data replication. And it reduces the time and effort it takes to make a decision, since there are fewer data sources to manage.
This also leads to more ease in governance and data security. Data virtualization simplifies data governance by offering a single data source, integrating all sources into one, and allowing IT teams to only have to enforce security at a centralized point. In addition, data virtualization platforms include features ranging from access control to the ability to integrate with other data security tools.
Data Virtualization Issues
Not all are advantages or facilities when it comes to data virtualization. It also presents difficulties. To get started, you have to make an investment economical of a certain depth to start using it. You need to invest in data virtualization software, train the staff who will need to work with data, and purchase or subscribe to other items and services.
Virtualization itself is complex, and modernizing a data infrastructure with it is not easy. It is not enough to buy software and implement it. In many cases, virtualization tools must be implemented in conjunction with other tools, and virtualization itself can be complicated.
In addition, to take advantage of data virtualization personnel with specific experience are needed in this field. Both to implement it and for its current and future management. And some companies may not have, at least for the moment, access to them. Companies may need to hire someone specifically for data virtualization. They can also order it from third parties. In either case, this will drive up your costs.
Finally, it is necessary to take into account that obtaining data depends on whether the source from which they are obtained is up and accessible. Not all of them are in operation 24 hours a day, and to get the data you need the source to be active and available. If the source is not, there will be no data retrieval, and this can delay the process or falsify it if a source crash goes unnoticed.
