Last updated on January 6th, 2023
Almost every business is proceeding towards the migration of technical services and platforms to the cloud platforms for leveraging various business advantages using one of the three or all three cloud services- IaaS, PaaS, and SaaS.
The landscape of benefits includes the following but is also not limited to cost reduction, scalability of economies, quick deployment of information systems, agility, and better processing speed.
However, subscribing to cloud services does bring compliance and security challenges for which enterprises are usually unprepared.
A few of the frequently occurring security challenges are credential and access management, vulnerabilities of the system, data breaching, and insufficient identity, which must be addressed by the enterprise owner while switching to a cloud environment.
A business may lack a proper operating model, enforcement of procedures and policies, organizational functions, or operationalization for managing cloud security. The unaddressed business problem leading to these security breaches is the unavailability of efficient cloud governance.
Did you know?
As per the Javelin Strategy and Research, the estimated loss of identity fraud was tallied to be $56 billion.
Hence, it becomes imperative for a business to know whether the cybersecurity and data governance strategies match their business goals or not.
This article covers the objectives and challenges of cybersecurity and the implementation of data governance in a cloud environment. Have a read!
The Focus Objectives of Cyber Security Governance
In the cloud, the security initiatives should be in accordance with the measures taken to mitigate the risks for the businesses effectively. The initiatives taken should also be capable of reducing the risks over the period of time for the associated enterprises.
The security measures in the cloud should be evaluated based on results yielded, value and risk to the business, performance, and the ability to achieve the desired objectives in the times to come.
Every business should focus on the projects, services, and security investments in the cloud to be in the league to achieve the business goals.
The Correct Use of the Resources
It becomes imperative for the enterprises to develop and deploy an operating model that manages and performs the security initiatives on the cloud, which should include the right operationalization of the needed processes, the execution of proper responsibilities and roles, and the usage of required tools for better efficiency and effectiveness.
Every enterprise should have a properly defined, operationalized, and maintained security function and strategic representation. Security aspects should be such that it brings value to the business along with their deployment and execution.
Also Read: What is Public Cloud
Challenges faced by Cloud Computing Security Governance
Non-involvement of senior management
Cloud customers face a significant challenge when no policy is influenced or endorsed by the senior management. The security policies are to set the executive tone, expectations, and principles for security operations and control.
However, many enterprises implement security policies burdened with content and lack executive influence.
Embedded management controls unavailability
One major challenge in cloud security procedures and processes is the unavailability of embedded management controls. This situation can lead to operational risks, which will not be ideal for any business.
Steps for Implementing Data Governance in Cloud Computing
Single point of control for cloud-based and on-premise data
In recent times, most businesses have deployed hybrid cloud architecture in which data is stored in both public and private clouds and on-premise data centers.
To have an effective data governance strategy, it is essential to have centralized data governance to control every data set irrespective of its location.
Having central control over the data helps in reducing the need to rework along with enabling the data engineers to execute data governance policies better across the associated IT infrastructure.
The implementation of one platform for the access of every data assists the data engineers in processing the data access requests accordingly while modifying the data access policies using only one interface for every data set.
The issues of contradicting authorizations and policies or metadata, which lead to compliance lack, get eliminated with the use of a centralized platform for data access.
Also Read: Hybrid Cloud Vs Multi Cloud
Implementation of globally scalable policies to save time
With organizations improving their data storing and capturing abilities, it becomes extremely time-consuming to govern the data using manual methods. In addition, manual processes are more prone to errors, thereby enhancing the risk levels.
The enterprises which have implemented a central data governance platform can save their efforts and time by involving globally scalable policies that are ideal for regularizing the usage and availability of data not only within one application but all throughout the network.
Automatic detection of sensitive data
A few data governance platforms can automatically detect, tag, and classify sensitive data across various interfaces. Automated sensitive data discovery helps the designated data teams save their time, which is usually involved in manually categorizing the data.
Also, it reduces the risks and errors involved with manual entries of data. After the sensitive data is detected, it is automatically tagged for executing the right access control policies.
Self-Service Access for data consumers
The recent data catalogs compile the required data into an integrated and searchable platform which enables the data consumers to explore, access, discover, and analyze it quickly.
With the self-service access feature, the authorized data consumer can access the present data sets without having to request its access manually from different data owners.
Though the data consumers will have access to the catalog, the engineers and data architects can restrict specific data sets per the permissions to reduce the risk of data misuse.
Smooth certification of sensitive data workflow
Only the automated discovery of sensitive data is not enough. The data team should be able to certify that the sensitive data has been detected, tagged, and classified.
For fulfilling these requirements, the data architects and engineers should implement the right workflows for reviewing, approving, and inspecting the discovery of sensitive data.
There is no doubt about cloud computing being the future and cybersecurity being a concern.
It is crucial for a business to not only implement cloud infrastructures but also be aware of the measures required for the security and governance of data while tackling the cybersecurity issue. So, it is better to trust but best to trust and verify.
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