What is Access Control?

Summary

Jared Hillam discusses the evolution and importance of access control in data security. As organizations grow, access control becomes crucial for managing who can see what data, reducing irrelevant information and ensuring sensitive data protection. With the rise of cloud data platforms, centralized data requires flexible access control, necessitating a shift from traditional BI tools to embedding security in the data architecture itself. This approach allows for consistent access across various tools and ensures data is relevant to the audience, promoting a loosely coupled architecture for independent upgrades and business continuity.

Takeaways

• 🔒 Data security is not only about external threats like hackers but also about internal access control to ensure sensitive information is protected and irrelevant data is not unnecessarily exposed.
• 📈 As organizations grow, access control becomes increasingly important to manage the visibility of data across different segments of the organization.
• 🚧 The traditional approach to access control, which was tied to business intelligence (BI) tools, is no longer sufficient for modern, large-scale data architectures.
• 🗂️ The shift towards centralizing data in data warehouses and data lakes has necessitated a reevaluation of where and how access control is implemented.
• 💡 Access control should be an integral part of the data architecture itself, not just an afterthought in the BI layer, to ensure flexibility and scalability.
• 🔄 The move towards cloud data platforms has enabled scalable querying of centralized data sets, which in turn requires a more dynamic and decentralized approach to access control.
• 🔗 Loose coupling is a key architectural principle that can be facilitated by embedding access control in the data architecture, allowing for independent upgrades and interchangeability of analytics tools.
• 🛡️ Deep access controls are essential for ensuring that data is segmented and relevant to the audience consuming it, regardless of the tool used to access the data.
• 👥 Large organizations may have multiple BI tools and diverse audiences interacting with data, necessitating a more granular and centralized approach to access control.
• 📝 Active governance, auditability, and sustainable standards are crucial for managing roles and data segment grants in complex cloud data architectures.

Q & A

What is the primary concern with data security beyond hacking and theft?

The primary concern with data security beyond hacking and theft is access control, which defines what segments of data internal parties can see.

Why is access control important in large organizations?

Access control is important in large organizations because it not only protects sensitive data but also minimizes noise by ensuring that only relevant data is accessible to specific organizational parties.

How has the approach to data consumption changed over the past 20 years?

Over the past 20 years, data consumption shifted from one-off business intelligence reporting applications to more centralized data warehousing, and then to cloud data platforms that allow scalable querying of centralized data sets.

What was the traditional location for access control in data architectures?

Traditionally, access control was located in the business intelligence layer, even after data had been centralized in a data warehouse.

Why did the approach to access control need to change around 2015?

The approach to access control needed to change around 2015 due to the advent of cheap storage methods, which led to further centralization of data and a need for more flexible data access across a growing number of tools and audiences.

Why can't access control be tightly coupled with reports and dashboards in modern data platforms?

Access control cannot be tightly coupled with reports and dashboards in modern data platforms because organizations may use multiple business intelligence tools and have various audiences interacting with data directly, necessitating a more flexible and decentralized approach to access control.

Where should security be implemented in modern data architectures to ensure flexibility and consistency?

Security should be implemented back into the architecture as an aspect of the data itself, ideally at the data lake level, to ensure that any access to the data can be segmented and relevant to the audience consuming it.

What is the benefit of pushing access control back to the data lake?

Pushing access control back to the data lake allows every point of data to be served to every user with no concern about the tool issuing the query, meeting the expectations of business stakeholders for a flexible data architecture.

What is the key to successfully implementing deep access controls in a data architecture?

The key to successfully implementing deep access controls is active governance, auditability, and sustainable standards, with administrators being highly aware of roles and grants for data segments.

What is the title of the white paper mentioned in the script that discusses potential issues with access control?

The title of the white paper mentioned is 'How to Botch Your Snowflake Deployment in Three Easy Steps.'