Artificial Intelligence (AI) and Machine Learning (ML) are transforming business practices – but only if organizations can conquer the challenge of accessing and aggregating data across their various siloes and sources into an accessible data lake. ETL – extract-transform-load – is the industry acronym for this activity, but the processes behind it cause significant friction. While this is particularly significant in large organizations, even the smallest organizations leveraging AI and ML solutions will encounter some of the same issues.
Leveraging a Zero Trust remote access solution eliminates that friction in three key areas: in-house data extraction, how outside vendors are securely leveraged, and cloud-native AI and ML solutions. We’ll explore each in more detail below.
In-house data extraction
Even when customers retain the bulk of their data in-house, many of their data siloes exist for a purpose. There are often very valid reasons why only certain individuals have access to specific databases and attributes – granting persistent access without controls creates business issues. Through a Zero Trust deployment, conditional access can be granted to only specific users, for specific timeframes, and even specific apps, so they are only extracting data to which they should have access.
Organizations that leverage outside ETL vendors – a common scenario, especially in smaller organizations – have a major challenge. They must open up firewalls and provide persistent access to data for these outside ETL vendors because data lakes aren’t static – new data must consistently flow into and through the ETL process to make ML and AI truly effective.
By providing persistent access to outside vendors, these vendors become a threat vector, and if those vendors are compromised, so is the customer. Zero trust access can ensure that, even if the ETL vendors were compromised, the customer is not. With a zero trust implementation, persistent and unfettered credentials simply aren’t available to attackers even if vendors are compromised – they still can’t get to the customer’s data.
Cloud-native solutions AI and ML solutions
The portfolios of AI/ML technology in both Microsoft Azure and Amazon Web Services (AWS) are broad and have countless applications to commercial and public-sector workflows. Within Microsoft, there are four basic service groups: Azure Applied AI Services, Azure Cognitive Services, Azure Machine Learning, and Azure AI infrastructure – all of which are designed to interoperate together as customers build AI and ML-powered solutions.
AWS offers a similarly broad range of AI and ML solutions, including Amazon SageMaker, Intelligent Document Processing (IDP), Contact Center Intelligence (CCI), and AWS Glue, all of which can factor significantly in AI/ML initiatives.
As valuable as these services, can be, organizations must first figure out how to provide conditional access across their various and often siloed data sources before they can deploy any of them. A Zero Trust solution streamlines how organizations can operationalize data access – providing connectivity and providing security to move these siloed bits and bytes through all of these cloud-native services.
Zero trust network access is the most straightforward way organizations can ensure data access is secure and targeted. Cloud-specific VPNs are inflexible and costly, and in-house tools are hard to maintain. Container-based deployments like Kubernetes compound these issues, but Zero Trust network access can help you avoid all of them.
For an effective and easily-maintained ETL initiative – which is vital to any organization’s AI and ML efforts – zero trust is really the only option. Visit our website for information about Barracuda’s Zero Trust solution – CloudGen Access – or contact us directly. There’s also a free 14-day trial. CloudGen Access is cloud-agnostic, so it can provide secure remote access to both on-premises and in-cloud workloads and data sources.
ETL should be part of a transformative initiative for your organization, not initiate new security challenges. Zero trust remote access is a way to keep your focus on AL and ML and leverage all the power that ETL can provide.