Data utilization is no passing fad as public sector organizations increasingly realize that information is the new lifeblood of the mission. Like oil, gold, and land before it, data has taken on new characteristics as it has become a sought-after commodity. One characteristic of data is the ability of malicious actors to steal it with ease. Whereas oil and gold must be physically heisted, or land grabs conducted in a courtroom, data is easy to access if you know where to look, especially if the organization has fallen into the habit of forming data silos.
In a recent webinar, Snowflake’s Head of Platform Strategy, Kyle Rourke, noted that “the biggest problem in data today is that data is everywhere. It is stuck in a million different places and it’s really hard to get access to.” Segmented sections of an IT network with minimal oversight are fertile ground to be forgotten with outdated security policies remaining in effect, leaving an organization vulnerable to attacks that could otherwise be prevented.
Instead, organizations must look for solutions that prioritize security and efficiency. One such solution is the data lake model that sees an interconnected IT network based around a central repository that contains structured and unstructured data. Utilizing such a model allows organizations to easily use new types of analytics including machine learning (ML) and AI to bolster cybersecurity and data processing.
At its core, the data lake model seeks to simplify the data storage and analysis process, simplifying an otherwise convoluted process. Snowflake’s Mark Kochanski once noted that “historically, data sources flow through several different stops within an organization before they reach their ultimate consumer,” ultimately causing a loss of fidelity and a decrease in data security policy adherence.
However, organizations using a data lake architecture can eliminate security data silos by removing limits on ingesting and retention, achieve automation with powerful security analytics, and gain security capabilities through interoperability with other cybersecurity approaches and solutions.
By removing limits on ingestion and retention, organizations can achieve their digital transformation goals and effectively store and analyze security data without breaking the bank or sacrificing performance. “[Using secure cloud-based technology], we can provide more services and features to the people that we serve for either the same or lower cost,” the Massachusetts Office of Education’s Program Manager, Integrated Digital Data Services (IDDS), Danielle Norton, said in a recent webinar. Snowflake’s data lake architecture separates compute and storage data, allowing security teams to remove many of the limitations of traditional SIEM architecture.
Automation will continue to play an ever-increasingly significant role in the future of cybersecurity. Leveraging data analytics, a modern data lake architecture approaches automation as a way to bring greater fidelity of information. As part of the evolution of the industry, applying automation helps analysts and security teams to apply complex detection logic and data management policies that can prevent and document any intrusions, helping to create a more robust incident response.
Finally, something that should be a priority for any organization is finding solutions that play well with others. Utilizing the extensive cybersecurity ecosystem around data lakes will help organizations create custom-fit solutions that meet whatever needs they have. As organizations look to utilize the most cutting-edge solutions to bolster their IT networks, having interoperability as a core requirement is a key to future success.
Data is the most important commodity in the world today, but as the world continues to grapple with the evolution of hybrid work and the ongoing digital transformation, the best ways to secure and manage data will continue to evolve. For now, the best way for public sector organizations to store, utilize, and protect their data is to reach out to their IT partners and learn more about what a data lake model can do for them, now and into the future.
Continue reading about how your organization can utilize Snowflake’s data lake architecture to overcome your data silos, here.
