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This article will explain in detail how to solve the big data problem of migrating to the cloud platform. The content of the article is of high quality, so the editor will share it with you for reference. I hope you will have some understanding of the relevant knowledge after reading this article.

Alberto Pan, chief technology officer of Denodo, explained how enterprises overcome big data's difficulties when migrating their business to the cloud platform.

It is still not without obstacles for enterprises to use big data. For many enterprises, cloud computing has become a reality. Over the years, it has enjoyed a reputation as the key to achieving maximum agility, flexibility, and scalability. The benefits of cloud computing technologies such as big data have been fully proven. Enterprises that adopt them can expand and reduce their data storage and computing capabilities as needed. This provides a new level of flexibility for dynamic workloads, allowing enterprises to take advantage of new data types or new business opportunities without making a significant commitment to infrastructure.

Recent research shows that 42% of companies operating in the UK deploy some kind of cloud computing service, an increase of 18% over 2014, so adoption will not decline any time soon.

And while many companies are already experiencing the benefits of migrating data to cloud platforms, some are considering how to improve their competitiveness by introducing big data into the hybrid cloud.

When considered separately, cloud computing and big data are both powerful advances in technology. When they are combined, they can give enterprises a competitive advantage.

However, while the benefits may be huge, moving big data to the cloud platform is not without challenges.

Big data = big problem?

For many enterprises, big data may cause big problems when migrating to the cloud platform.

Because of the need for more processing power, big data is traditionally dealt with internally. Its complexity means that it is still hard for enterprises to imagine starting to migrate to other environments.

The first challenge for enterprises is the transition from physical infrastructure to virtual infrastructure. In order to do this effectively, connections between different data sources are critical. Companies need to ensure that they can migrate their big data to the cloud platform while running their local systems as efficiently as possible. They also need to ensure that different systems and applications can be connected after migration to ensure the smooth flow of data, otherwise they may affect overall business productivity or even downtime.

Once this step is completed, organizations often face another problem. For many people, moving to a cloud platform can feel out of control. Especially compared to internal deployment. This is usually because enterprises have less direct contact with data, and the problem is usually magnified when considering big data. Big data usually contains sensitive information, such as employee personal information, including employees and customers. Because of regulations such as GDPR, ensuring that this data is protected has never been more important to avoid fines or reputational damage.

While these two challenges should not hinder big data's migration to a cloud platform, the concerns often associated with them mean it is difficult to get companies involved. In general, some members of senior executives need to safely accept the idea of migrating this information.

Release income

Data virtualization has the potential to help organizations overcome the fears that often arise when moving big data to a cloud platform.

By generating a single logical view of all business data, no matter where it is located, without having to repeat information in the physical repository, it enables organizations to overcome connectivity and security challenges.

This single view enables organizations to monitor connectivity and performance between different sources during the migration phase. For example, when the data source is moved to the cloud, the virtualization layer will provide redirection by reconfiguring the virtual layer, which means there will be no need to manually reconfigure the application. This saves resources and ultimately saves financial expenses.

Similarly, from a security perspective, when big data is in a cloud environment, this single layer will grant a complete view of the data source, which can help enterprises better protect their most confidential information and comply with the latest regulatory standards without affecting overall operational performance.

Big data = Great opportunity

Moving big data to the cloud platform has many benefits. The scalable environment of cloud computing is more cost-effective and can be used to improve the speed, performance, and scalability of business operations.

Data virtualization is becoming the key to helping organizations realize these advantages. By providing a single logical view of all the data, no matter where it is located, it enables enterprises to move big data to the cloud, while still ensuring that they can manage connections, respond to security concerns and compliance requirements, and eventually find any information they need.

In terms of cloud migration, data virtualization can turn big data's problem into big data's opportunity.

On how to migrate to the cloud platform to solve the big data problem is shared here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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