Redundancy With Data Segmentation Cloud Computing

Data segmentation, when done correctly, can reduce the need for data redundancy. This, of course, directly impacts costs and the necessary technological structure.

Today, we talk a lot about Big Data and the amount of data processed daily in all market sectors. According to some research, there is an estimate that by 2025 there should be around 175 zettabytes in the world.

And this is just an estimate; after all, with the arrival of 5G, the increasingly recurrent use of the internet of things, and machine learning, the production, and availability of valuable data can be even greater.

Although we consider the data as the “new oil,” an item of extreme value, the high volume brings some problems to the point that some more innovative companies are choosing to focus on Small Data to optimize data capture, processing, analysis, and storage.

After all, the high volume demands that companies have robust technological structures for processing. As well as good information security techniques and efficient availability strategies. Many perform data redundancy to minimize interruptions, but did you know that you can make this process more efficient?

To facilitate the understanding of these two terms and the relationship between them, it is necessary to analyze each one separately. Below is a simplistic explanation of how redundancy and data segmentation works:

What Is Data Redundancy, And How Does It Work

Data redundancy is a widely used availability security practice in IT. It is about duplicating or sometimes tripling data to ensure it will be available even in case of bugs, instabilities, and attacks compromising the information saved in a specific location.

Redundancy is also used in other technological tools, hardware, and software. In such cases, the components are duplicated to ensure that the device or system continues to operate even if one of them fails. It’s like the second parachute of technology; if the components or mechanisms of the first fail, the skydiver still has the second.

Therefore, data redundancy is to avoid interruptions and the unavailability of information as a security and stability measure.

Companies that use an older technological structure used to save data and information in several places, such as pen drives, on the desktop, and in the cloud. Thus keeping several copies of the same data set.

As you can imagine, this process of data redundancy requires companies to have a more significant technological structure. Moreover, the team must manually update the databases if the tools and systems don’t fully integrate, which is most common for redundancy to succeed.

This context hinders the mobility required today, especially when dealing with remote or hybrid work.

When talking about a few channels and a small volume of data, redundancy can be efficient but not scalable. To help optimize this strategy, we have two solutions: more efficient data segmentation and cloud computing.

What Is Data Segmentation?

Data segmentation can be used in two different ways. The first of these, and perhaps the best known, is to categorize documents of the exact nature or applicability.

Many companies perform this process automatically through systems; others use Excel filters. This segmentation is beneficial for grouping data that can be used together to meet a common goal.

For example, imagine a spreadsheet with the call history of a telecommunications company. If the company needs to categorize complaints to analyze churn rate, it segments related data.

The other way to use data segmentation is in operating systems. In this case, the objective is to protect the memory by dividing the programs into logical segments so that the operating system can distribute them in memory. In this way, in addition to generating smaller sections, it is possible to categorize the information according to the need for security and manipulation.

In both uses, we can say that data segmentation seeks to group similar elements into smaller groups, to facilitate analysis and protection or to make data manipulation more efficient.

But what is the link between data segmentation and redundancy? Without a strategy, companies perform data redundancy with all the information that enters the most diverse channels, systems, and business sectors.

Thus generating an accumulation of data and inefficiency in handling them. After all, many captures will not be interesting for the company. By performing data segmentation, managers can identify which ones need backups and where they will be stored.

How Can The Cloud Make Redundancy And Data Segmentation More Efficient?

Imagine a telecommunications company that needs to handle customer data, on and offline channels, suppliers, employees, and all company processes. And we’re not just talking about customer service, but financial, commercial, sales, marketing, etc.

Performing data segmentation manually and then opting for redundancy categories, following the availability demand of each one, would not be efficient. Mainly for companies with physical files in Excel spreadsheets and existing systems.

Without the integration of automated systems and processes, the company will become increasingly inefficient, with expenses that do not return, rework, and a more overloaded environment. After all, instead of employees focusing energy on their ultimate goal, they perform actions that could be easily discarded or optimized.

Cloud computing, or cloud computing, can be a great solution to increase the efficiency of data segmentation, reduce the need for redundancy, and optimize investments in technological structure.

After all, the company can count on a secure platform with numerous automation features, ensuring the storage and availability of data anywhere and at all times.

And the best, there are technology and innovation giants that guarantee the efficiency and security of your data! Like Google, like Google Cloud Platform, check it out:

Google Cloud Platform

Google Cloud Platform is Google’s IaaS system, with which your company has access to numerous products and infrastructure from the pioneering technology companies in the world.

With a focus on innovation and cutting-edge technologies, such as artificial intelligence, the platform offers flexible possibilities, adaptable to the company’s demand, secure, and integral.

Also Read: Types Of Clouds And The Differences Between Them