Modern businesses are always concerned about ensuring the formal management of data assets within the enterprise. Therefore, organizations aim at deploying a responsible system that can boost their productivity and competency. Data governance is an exercise that deals with protection, privacy, integrity, accessibility, compatibility, enforcement, functionality, roles and obligations, and overall management of the organization’s internal as well as external data flows.
Some of the latest buzzes in the big data world are focused around on-premises sophistication, deployment of Hadoop technology, and so companies are getting restless and moving into the cloud. Serverless computing is more promising than retrofitting Hadoop in an increasingly cloud-friendly business environment. Several global firms are turning into the cloud and the implementation of serverless architecture for distributed computing is a solid, viable choice.
But, in a serverless environment, the extremely valid concerns about data security and data privacy will cause companies to pause and reconsider their IT infrastructure frameworks.
The concern with cloud computing is that it generally has much greater control over data access, data auditing, or security concerns than data storage facilities on-premise. Business operators who switch to cloud services will also need to enforce their own data governance practices or data protection policies as they do on-premise.
The Forbes post-Data Protection and The Cloud: A Hybrid World Deserves Hybrid Security describes this well and points out the value of a single security infrastructure covering on-premise and cloud data stores.
In article 5 Cloud Trends to Watch in 2020, the author states that as cloud storage providers come under new Data Governance regulations, especially as a result of GDPR, cloud storage suppliers are likely to move to a business model of supporting larger numbers of small data centers rather than supporting fewer large data centers. One of cloud storage’s benefits has been the pay-per-use consumption model.
An example of Amazon AWS, the special configuration guidelines are used to automatically search for encryption of volumes of data. The author of the Amazon post Automating Governance on AWS recommends that you can combine in-built config rules with custom rules for managing data volumes. This post emphasizes the fact that system administrators don’t need to remember every control with AWS, as security monitoring tools and real-time dashboards disclose security threats and status.
The storage infrastructure options have always been a key concern for companies concerned about data governance, data protection, and user privacy issues in moving big data to the cloud. The IT solution providers have built a path for using big data on the public cloud through Insight PaaS since big data on the public cloud suddenly increased worldwide spending on hosting infrastructure in comparison to on-premise spending.
Serverless architectures maintain ample servers and storage spaces to allocate third-party networks to accommodate all applications, so business operators don’t need to manage complicated and expensive IT infrastructures on-premise to meet their business needs.
Serverless computing allows organizations to operate at a highly scalable and efficient speed, thereby increasing overall operating performance.
