
How to drive trusted decisions without changing your current data infrastructure.
Learn more about DataOS® in our white paper.
In an ambitious effort to reduce the threat of cyber attacks on critical infrastructure in the United States, President Biden signed an executive order to improve cyber threat information sharing between the government and the private sector. Signed in May, the order aims to fill gaps in the public and private sector approach.
This move highlights how critical advanced cybersecurity is to US infrastructure. The community talks a lot about how digital transformation is a crucial part of creating a disruption-proof supply chain. However, one downside is that with increased connectivity comes more responsibility to stay ahead of threats. The executive order can guide companies on how to protect their supply chain and what a next-gen cybersecurity approach can look like.
The government’s approach to cybersecurity has been patchy and with little guidance for the private sector. However, an increase in cybersecurity threats to the private sector from government sources of other nations has changed the game.
Biden plans to increase support for new cybersecurity measures and approaches and to explore bold changes to the government’s entire infrastructure to protect assets. If the government plans to follow through with these actions, the private sector can’t help but follow.
The supply chain can expect more guidance from governmental sources in the coming months and years as the executive order takes effect. However, reciprocal communication will be a priority, so companies will need to structure the data ecosystem to account for this information sharing.
Section two of the new order requires that IT service providers — including cloud providers — share data breach information liberally with government departments and agencies tasked with fighting cyber threats. Until this point, providers could choose to withhold information from certain departments.
Service providers will be supplying more information about breaches and potential threats, making it easier for the government to adjust responses. This could be very good for private sector companies looking to move their own cyber threat responses to a more proactive approach.
Other sections in the executive order aim to fully modernize the government’s approaches and tools in the realm of cybersecurity. The executive order outlines:
Again, this is a coordinated, proactive approach to cybersecurity. The government wants to monitor and respond early to nation-state attacks on both public and private sector assets and is willing to make big investments for the tools to make that possible.
Supply chain companies will need a new approach to cybersecurity to remain in compliance with the executive order and to prevent another SolarWinds-style attack. Threat actors tend to attack the following when trying to breach a supply chain:
Companies can better address these threats by unifying their data ecosystem under a single roof. This doesn’t have to be a rip-and-replace approach. Companies can create an operational layer that allows them to take the following steps towards protecting the supply chain.
Companies need to understand the five Ws of their data: who, what, when, where, and why. Therefore, implementing a single data ecosystem with central, native governance and full visibility is essential. A data operating system can tell decision makers where their data comes from, who has access, when data was used, and for what task. It also could provide context for all dependencies. This observability helps companies quickly sort out their data parameters.
There are many moving parts: companies sharing data, workers performing tasks remotely, partners reporting, audits. It’s a long list. Zero trust assumes all network activity is malicious by default, which reduces common cyber attack weak points — emails, logins, and other access points. In addition, threat actors know that third-party vendors are a potential weakness because they often have access to a company’s sensitive data but may not have the same security protocols.
Shadow IT, or IT products and tools deployed without the knowledge of major decision makers within the IT department, can be another serious weakness in security. These products have access to the network, but IT may not know it, leaving them outside the range of normal observability. Instead, implementing integration products that connect legacy systems with modern tools without patchwork solutions can reduce the risk that shadow IT will provide a loophole.
Data should be available to all stakeholders for decision-making. This is the primary goal of digital transformation within any organization. However, freeing data may improve predictive analytics and operational automation, but it opens the supply chain up to greater risk. Native ABAC governance controls enable the organization to make data available appropriately for stakeholders without creating many different data copies or introducing inconsistencies in the security policy.
The government’s executive order is clear: it’s time to take better care of cybersecurity policies and treat threats more efficiently. With a data operating system, companies can still leverage the full power of their data and its ecosystem while building secure frameworks like ZTA. It can automate reporting to share with public entities and create a layer of observability into the data ecosystem and all its dependencies. The executive order may start another cybersecurity transformation, but the data operating system will bring it all together.
Learn more about security and governance with DataOS.
Be the first to know about the latest insights from Modern.
In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions, we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Remember to read part one if you need a quick refresher. ...
Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Each has unique advantages and drawbacks, and the right...
What is a data operating system? On the surface, it's an operating system designed specifically for managing and processing large amounts of data. It typically provides a scalable and flexible infrastructure for storing, processing, and analyzing big data and should...
Prevention and early intervention are essential to building an effective healthcare approach that supports patients from start to finish. The critical component of this approach is predictive analytics — analyzing big data gathered from patients, consumers, and...
Technical debt is something that many companies are aware of and are attempting to address. It is a big enough issue that several of our recent blog posts (Lessons in Technical Debt from Southwest Airlines, Start Paying Down Your Technical Debt Today, and A Better Way...
Data Mesh + Patient360: A Modern Revolution for Healthcare DataHealthcare organizations are sitting on a treasure trove of customer data. Operationalizing that data makes it actionable and usable, helping improve services, costs, and patient outcomes. However,...
The Modern Data Company BriefThe Modern Data Company is radically simplifying data architecture with its paradigm-shifting data operating system, DataOS. We're replacing overwhelm with composability, reinventing governance, and connecting legacy systems to your newest...
DataOS® – The Fastest Path from Data to DecisionDataOS is the world's first fully-integrated data operating system designed to move from companies from data to decision in weeks instead of months. Discover what makes DataOS different from the competition and how...
Not Getting Value from Your Data Transformation? Fix itImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV. In the past, organizations have struggled...
DataOS® Solution:AI/ML 70% of AI initiatives fail and teams spend the vast majority of their time simply prepping data for platforms, leaving very little left over for gaining insights and driving business value. But an AI/ML platform powered by DataOS can achieve...