The vast majority of organizations now utilize the cloud in some form or another, yet there is no single process data teams follow when migrating data to their cloud platform. This may not seem like a red flag on the surface — if all the data gets from point A to point B, why have a specific process?
Two-thirds of organizations name data security the biggest obstacle to cloud adoption. This could be because it’s often difficult to understand the whole picture: Data teams know the business needs, but not necessarily the security requirements; IT teams know the data, but perhaps not the data governance process; legal and compliance teams know the regulations, but not the technical requirements. However, anticipating these potential obstacles and incorporating data security into your cloud migration plan early on can help streamline the process.
Here are four reasons incorporating data security early in your cloud migration plan can set you up for success.
You wouldn’t invest in a cloud service provider without knowing its capabilities. Why would you do the same for a data governance tool?
Unfortunately, many data teams inadvertently make this very mistake for a simple reason: They don’t know exactly what they’re looking for. Unless you know the scope of what’s needed to fully protect your data, it can be hard to understand the necessary tools and features in an automated data access control solution. For instance, if a cloud service provider offers fine-grained access controls but not sensitive data discovery, how confident are you that you’ll be able to adequately scan new data sets and data sources without overlooking any potentially sensitive data? Based on your organization’s growth, do you anticipate feeling differently a year, two years or five years down the road?
Taking your various data sources, users, subjects and use cases into account can help formalize a data protection plan and determine the data governance tools to execute it. A plan for data protection that’s implemented early in your cloud migration process can help assess data governance solution options based on your specific cloud environment, platform architectures, anticipated use cases, future cloud migrations and anticipated growth. As organizations continue to rely on data analysis as a competitive advantage, having a scalable automated data access control solution that can be deployed across cloud providers is key for companies planning to acquire data sources and/or grow in size.
At the end of the day, sufficient data access control measures rest on the shoulders of the data architects and engineers. But as any data team knows, it takes a village to ensure “sufficiency.” When legal and compliance teams become involved in the process too late, it can cause confusion, rework and delays to data access and usage.
This is generally the case when there is no clear review process or accountability. If data is found to be noncompliant, is the data engineer or the legal advisor accountable? Developing a RACI model that assigns specific roles to each function involved in data protection early in the cloud migration process can make these questions easy to answer and avoid frustration in the review process.
For instance, as a data engineer, you need to know the fundamentals of regulatory requirements, in addition to organizational contracts, industry standards or employment clauses. While legal and compliance teams may not be able to apply the policies to ensure compliance, they can provide the necessary inputs to develop a strategy, classify data and write appropriate policies to protect it. The RACI model can help define these roles so the process is collaborative and efficient.
Waiting until the end of the cloud migration process to involve the legal and compliance teams runs the risk of scrambling to understand regulations and rewrite policies accordingly at the last minute. Not only does this delay speed to data access and use, but it also erodes collaboration and accountability. On the other hand, when clear roles and responsibilities around data security are in place going into the cloud migration and the legal and compliance teams are involved early on, you’re more likely to have collaboration and consistent alignment from start to finish.
It seems like new cloud data platforms are emerging — or in many cases, merging with existing providers — on nearly a daily basis. While it’s true that some cloud data platforms offer data governance or protection features, they exist in a silo: In a multi-cloud hybrid environment, those data access controls can’t be applied uniformly across platforms. That means with each subsequent cloud migration or for each individual cloud platform, data teams essentially start from square one to protect sensitive data.
Migrating to the cloud increases the number and variety of places you store data. Without a standardized approach to data governance, managing policies consistently across each of those systems can quickly spiral out of control and create hours of added work. Therefore, after assessing the data landscape and data users, many data teams develop a standardized strategy for sensitive data discovery and classification. This also is an opportunity to consolidate data sets and clean out old models, which reduces the overall number of personal data copies that exist.
Rather than waiting to implement these controls until data has already started to be transferred, creating a taxonomy for sensitive data and writing policies with permitted use cases accordingly can greatly reduce backend work. This helps ensure data policy enforcements are well-defined and organized consistently and securely across all of your cloud data platforms.
It’s no longer sufficient to apply data access rules to a data set and check the box on compliance. That’s in part because the very notion of compliance has evolved. In addition to federal data privacy laws like GDPR and HIPAA, data engineers and architects now must also be able verify compliance and protections for industry standards, employment clauses, contractual agreements and internal misuse, among others.
With the proliferation of sensitive data in today’s environment and the increasing tendency of organizations to use it to personalize the consumer experience, data audit reports are more important than ever. Delays or gaps in reporting and auditing can result in legal enforcement, which can be costly to organizations and worse, have personal implications for data engineers who could be held liable. Deferring the development of a plan for data reporting and auditing until the end of the cloud migration process can cause those lapses, as well as create a last-minute scramble to put appropriate, comprehensive mechanisms in place.
Conversely, implementing a data access control plan early in the cloud migration process creates a continuous line of sight into who accessed specific data, when they requested access and how they used it, without any time gaps. Additionally, having consistent policies in place from the start removes any guesswork from when and how access control policies were applied.
Data security is a critical part of the cloud migration process, particularly due to the separation of compute and storage. Including it in your cloud migration plan from the start can avoid insufficient, inconsistent and unscalable implementation. It goes beyond that, though; incorporating data security early in the cloud migration process can improve your ability to adequately assess data governance solution options, collaborate cross-functionally with accountability and produce data usage audits and reporting.
Simply devising a data security plan that’s implemented early in your cloud migration will save your data team time and accelerate the speed to data access for consumers across the enterprise. Immuta’s SaaS deployment option allows for businesses to facilitate quick, scalable, and secure migration to the cloud with a fully managed and easy to apply instance of our platform. Check out a free trial below!
