A Downstream Approach for Your Cloud Migration
Delving into the downstream approach for information governance and eDiscovery needs when migrating to the cloud
The Commercial Division of the State of New York has consistently led the way as an innovative forum, proposing policy modifications. During the last few years, discovery difficulties involving electronically stored information (ESI) have taken center stage in most cases before the Commercial Division. The Commercial Division Advisory Council submitted a proposal on September 7, 2021 that contains numerous potential adjustments to the present e-discovery laws bringing hope for attorneys, companies, and eDiscovery professionals alike.
However, as every organization's eDiscovery needs come with unique challenges, companies must consider their approach towards their information management and data retention techniques. For example, a financial services company will need to deal with its records and data differently from a manufacturing industry company for several reasons, including varying regulatory compliance regulations.
Despite the difference, when it comes to eDiscovery solutions, the most common approach that organizations carry out is they move all their data to the cloud at once, leaving minimum to no scope for information governance. This can be considered an upstream approach as companies are going through their data upwards from the bottom. This makes all the data, even the redundant, obsolete, and trivial data (ROT), blockading the eDiscovery team's search missions. As a result, the eDiscovery teams are compelled to spend the same amount of time, if not more, searching for files despite the convenience of the cloud solutions.
That is why the ideal downstream approach to moving your company's data to the cloud is by proactively deciding which data to move to the cloud and leaving or deleting files that are of no value to the organization, thus reducing the likelihood of upstream issues. In other words, before moving any data, it is critical to categorize and assess it in place of origin, which may help you figure out what data you don't need, what's redundant, and what's sensitive, so that you can purge, archive, or split it before moving. Doing an unstructured analysis of your data before cloud migration will help you figure out what data you need to retrieve and progress, such as what's important now or will be in the future, so you can move only the relevant data to the cloud.
Going Downstream with Information Governance
Going downstream for your Information Governance can also help prevent your downstream eDiscovery and compliance solutions since it is still about data management.
Since many are keen on maintaining a hybrid information governance solution, preferring to keep specific data on their local systems while moving others to the cloud, you require an IG system that sits in the cloud and reads all cloud repositories as well all their file systems. This single interface approach for cloud and on-premises systems will help implement information governance to its fullest and secure all your data. Consequently, you will have a single view of all the data you need for more accurate and efficient reporting and eDiscovery.
A Downstream Approach for the Future
Just because your company has file analysis software in place to handle its on-premises data today does not ensure it will be relevant in the cloud tomorrow. Moreover, with the big data expected to reach a 175 zettabytes mark by 2025 globally, it is only fair to say there will be a change in the way we handle data. Therefore, companies considering moving to the cloud or a hybrid solution in the near future must consider each procedure they perform today and how it will be implemented in the cloud. For some regions, you may also need to create new processes.
Organizations must also consider their procedures from the beginning. You must consider each procedure you perform today on the on-premises solution and how it will be implemented in the cloud. For some regions, you may also need to create new processes.
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