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Advanced Data Analytics In Hybrid Environments: Leveraging Colocation And Cloud
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Advanced Data Analytics In Hybrid Environments: Leveraging Colocation And Cloud

Hybrid environments are often the ideal solution for businesses that regularly need to undertake advanced data analytics. The combination of real-world infrastructure (on-premises or via colocation) plus the cloud offers control, cost-effectiveness, and scalability. Here is a quick guide to what you need to know.

Understanding advanced data analytics

The term “advanced data analytics” refers to a sophisticated approach to examining large sets of data to uncover patterns, correlations, and insights that go beyond the capabilities of basic analysis. It involves using advanced algorithms, statistical models, and machine learning techniques to extract valuable information from complex datasets.

Advanced data analytics can deliver massive overall value for businesses. It does, however, also present technical challenges. In particular, it requires businesses to provide the resources necessary to deal with analyzing huge volumes of data at reasonable speeds. Moreover, this data can be in diverse formats and may be produced at a high velocity.

Understanding hybrid environments

Hybrid environments are IT architectures that combine two or more different environments. At least one of these environments is real-world (and hence private). At least one of the other environments is virtual (this may be private or public). Modern hybrid environments often contain a lot more than two environments.

The headline benefit of hybrid environments is that they allow businesses to leverage both the individual and collective benefits of all the different environments contained within them. For example, businesses can use private environments for maximum security and public environments for maximum scalability.

The main drawback of hybrid environments is that they are more complex to implement than single environments. There are, however, solutions that can help address this. Colocation is one of them.

Understanding colocation services

Colocation services are services that lease and/or rent space in data centers. The colocation service provider manages all the data center infrastructure (physical and digital). Clients install their own equipment in their allocated space and manage it themselves.

There are two main reasons why colocation facilities have been key to the growth of hybrid environments. Firstly, colocation has made real-world infrastructure a viable option for businesses of all sizes. Few small businesses can afford to tie up their money in on-premises data centers. Larger businesses might be able to do so but may not want to.

Secondly, colocation vendors typically do everything possible to make their services convenient to use. In particular, they will generally support integration with multiple public cloud services. Now, it’s increasingly common for them to support edge computing as well. In fact, they may even offer edge colocation services.

Understanding the cloud

A cloud is a collection of computing resources that deliver services and resources over a network. Clouds may be private or public. Private clouds are used exclusively by one entity. They often operate over private network connections although they may use the public internet (or both).

Public clouds are available to anyone who wants to use them. They deliver their resources over the public internet. Public clouds are almost always incorporated into hybrid environments to expand the capabilities of real-world infrastructure.

Leveraging colocation services for advanced data analytics

Colocation services offer three main benefits for advanced data analytics.

Guaranteed uptime: Businesses do not appreciate disruptions at any time. They especially do not want disruptions when they are undertaking advanced data analytics. With colocation, businesses are guaranteed a certain level of uptime. This is usually at least 99.999%.

Fast processing: Businesses can leverage colocation facilities to situate data centers near the users they serve. This minimizes the time required for data to cross a network. Also, businesses can have confidence that their equipment will always be kept in optimum conditions. This improves both its performance and its reliability.

Cost-effectiveness: Colocation facilities tend to be much more cost-effective than public clouds for processing large volumes of data. This is highly relevant in the context of advanced data analytics.

Leveraging public cloud services for advanced data analytics

Public cloud services offer three main benefits for advanced data analytics.

Guaranteed uptime: As with colocation facilities, public cloud service providers (CSPs) also tend to offer guaranteed uptime. This is also likely to be at least 99.999%.

Scalability: Public clouds are unlikely to be a cost-effective choice for processing large quantities of data. They are, however, a great option for quickly scaling up infrastructure to cope with temporary upturns in workload.

Ease of configuration: As public clouds are virtualized infrastructure, they can be configured and reconfigured with just a few clicks. This means that environments can rapidly be adjusted to cope with any specific requirements of particular data sets.

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