Secure Data Ingestion and its Impact on Cloud Modernization
Secure data ingestion is an essential component of cloud modernization—and an essential next step in the broader effort to extend your data handling practices into the cloud. A solid foundation will set you up for success for broader digital transformation efforts, including data and analytics solutions.
Maximizing the business benefits of cloud adoption means getting set up in a way that’s sustainable over time, so you’re able to rapidly and consistently roll out new features that follow business, regulatory and architectural rules.
Secure data ingestion—a key component of an enterprise data platform—provides a staging area in the cloud that isolates raw data so that its owner(s) can use cloud data platform tools and services to prepare the data for release into the general data platform environment.
This approach plugs into the concept of a data mesh, data lake or data mart, extending information security best practices into the data platform by providing an isolated zone where data owners can process their raw data for consumption without exposing it across the organization.
That means when you’re ready to share data or run analytics, it will be done consistently and securely, respecting regulations, guidelines and budget rules.
Creating a foundation for digital transformation
Private, sensitive or confidential data is subject to data handling policies as part of most information security practices. Uploading raw data to a shared platform before these handling policies are properly applied is a common violation of those same policies.
Isolating raw data that arrives on the platform allows its owners and custodians to process it before releasing it for general access. By separating data and processing services, data owners have full control over access to their data—even from platform developers and administrators.
Data masking, cleansing, classification and tagging processes should remain separate from business data transformations to ensure that data handling requirements are met. Field-level transformations such as type casting are also best done in this zone, so that published data is interoperable with other sources published on the platform.
Secure data ingestion not only helps to satisfy data handling policies, it also sets the stage for business transformation, such as the use of Google Analytics—a cloud-native analytics platform based on Google BigQuery. This provides the ability to scale while ensuring strong security controls and governance, so you can turn your data into insights.
Get started with Pythian
Pythian can help you extend your information security best practices into the cloud and establish an isolated zone to process raw data for consumption—without exposing it across the organization. Data zoning architecture and processing methods are platform-specific, so we apply data handling principles to each platform’s specific architecture.
Our infrastructure, zoning and identity and access management service extends your information security policies into your cloud platform, so you can create tools and architectures that enable safe handling practices.
And with our Secure Data Ingestion QuickStart, we can kick-start this process with a fixed-fee, two-week sprint that will help you develop a pilot project that establishes the data ingestion infrastructure needed to underpin data and analytics solutions.
Why Pythian? We have multiple specializations—Google’s highest technical designation—including Data Analytics, Machine Learning, Infrastructure and Data Management. And, as a certified Google Cloud MSP, we’ve delivered thousands of professional and managed services data and applications projects in the hybrid and multi-cloud world.
To find out more about secure data ingestion and how we can help, email us at email@example.com.