IS CLOUD THE NEXT BIG THING FOR DATA RETENTION AND ARCHIVING?

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Enterprises are dealing with a surge of data from varied sources, and the data has become a critical part for the business applications and operation. The enormous amount of data that has been produced by different sectors is disrupting the current cloud technology when dealing with different enterprise problems education, healthcare, finance or manufacturing. Enterprises are looking towards the data as an application for future IT infrastructural development.

Data is not used as an active application, but it’s imperative when it comes to developing a better decision-making process based on meaningful insights. Enterprises that use data to gain insights into customer behavior need to store the data structurally and comply with security requirements that protect the data nature. Data Security is one important feature that needs to be added with applicability for any enterprises that want to make effective use of data.

Enterprises are currently leveraging the data to provide an analytical edge in decision making but it can also lead to cost saving for the data storage with new innovations. The CAPEX and OPEX are two financial factors that are being looked as the imperative for technology development of any data storage. Technology is the fundamental tool that would be developing the data storage, and it’s imperative that enterprises are able to innovate and introduce better data storage technology.

DATA STORAGE TECHNOLOGY FOR BETTER DATA STORAGE:

Containers:

Containers are just better ways to package the applications. The expectation to see the modern software getting defined into different containers based on their applicability. Containerization helps in delivering the dynamic APIs and delivers a programmable infrastructure. Containerization is able to deliver the packaged applications that can be redeployed, can be made editable or the files can be manifested

Machine learning:

The data won’t make any sense until we make the data structured. Carefully applied machine learning will significantly add value to the application. Machine Learning technology that deals with a huge amount of data usually forms a recognition pattern or structure derived from the data sets. The technology is used to find complex data patterns that reduce the time and effort to target a given consumer segment. Machine learning would mostly identify and create a new algorithm that can help in better data management.

Management as a Service (MaaS):

Getting an overview of the recent technology in data storage Management as a Service (MaaS) acts as built-in home support for data management. The cloud-based offering combined with hybrid architecture will replace the on-premise management solutions. All data management providers are shifting towards the cloud-hosted MaaS offering.

HERE ARE SOME MAJOR DATA SOLUTION PROVIDERS:

Cohesity Solutions:

Cohesity will help in leveraging cloud data and data in the on-premises environment. The Cohesity solution provides the archival possibility for the on-premise data, cloud-public and private, Amazon S3-compatible devices and QStar libraries. The solution provides data management to define the workflow for automated back-up and archiving of the data. Cohesity helps in using the cloud as an option to leverage retention and protection with a model “pay as you go”.

Rubrik:

Rubrik provides solutions to the enterprises that deal with the hybrid cloud environment. Rubrik supports the following storage and architectures: Archiving to the cloud storage using Google, VMWare, vSphere, Nutanix, AHV, and Microsoft Hype-V. The enterprises can use predictive analysis to access different types of archived data. Data reimaging is used to access the data that further reduces the cost of transfer and storage. Rubrik provides data encryption before the data is being transferred from different sources.

CONCLUSION:

There are many data storage solution providers that offer different solutions for different data load. While organizations adopt the new storage technology, they should keep in mind the modern development that might disrupt the data market in next few years like IoT and machine learning. As the enterprises are curating different technologies to deal with data, it’s important that the past data is also archived using proper technology that also helps in the retention.

The long-term focus should be to deal with on-premise data, cloud and modern data generating sources. The Return on Investment (RoI) will help them decide the investment options to deal with data solution providers. 

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