Role Based Access Control for Data Teams- An A to Z Guide


Role based access control FI

Are you planning to expand your data team? Then, you should definitely anticipate some daunting challenges during the process. One of the most important among them is ensuring your data is secure in all the stages of integration. Controlling access to the pipelines can help to achieve this security. It can prevent intentional data access for the sale or unauthorized sharing of sensitive information. 

There are also chances of someone from your team accidentally deleting or editing an existing pipeline which is very likely to happen without an internal regulation in place. Hence, the importance of role based access control—it enables you to control access to pipelines based on job role.

In this blog, I will walk you through the details of role based access control. 

What is Role Based Access Control and How to Implement in Your Data Teams?

Let’s start from scratch.  

What is Role Based Access Control?

Role based access control (RBAC), commonly referred to as Roles, is a technique for limiting access based on the roles of people inside an organization. When it comes to data teams, it implies limiting access to the data pipelines.

Account owners could limit team members’ access to specific actions by using roles. Teams can limit access to particular entities using RBAC. Only those who have the necessary access would thus be able to carry out activities like creating, deleting, or editing.

Additionally, the security of the data is increased because Observers are not permitted to examine the raw data. Distinct team members may have varying levels of access to the data pipelines. 

You can configure the customization for each user. Because of this, some employees typically do not have access to sensitive information if they do not require it to carry out their duties. This is especially useful if you have a large workforce and interact with contractors and outside parties, which makes it challenging to carefully monitor access to the pipelines. RBAC will assist in protecting sensitive data for your business.

With this approach, you don’t need to record every single employee’s access; all you have to do is keep lists of which team members are on which teams. Access is related to a role, which is then linked to users, instead of being linked to the user directly.

Let’s take a role based access control example from Hevo Data’s feature to understand how RBAC works. 

How Does RBAC Work?

Hierarchy of Roles in Role Based Access Control
Hierarchy of Roles in Role Based Access Control in Hevo Data’s Feature

In Hevo Data’s role based access control feature, the entities defined are,

  • Data pipelines
  • Models and workflows
  • Team billings

There are four levels in accessing data pipelines. 

  • In Level 1, the people in the team administrator role can create, edit, and delete all four entities. 
  • In Level 2, team collaborators can perform these actions for the entities except billing. A billing administrator can access the actions related to billing. 
  • In Level 3, pipeline administrators can create, edit or delete pipelines. And, there is another role defined to carry out these operations on the models and workflows.

And, the hierarchy goes on to the fourth level of collaborators as given in the diagram. Now, let’s get into how to implement role based access control in your data team.

Steps to Implement RBAC in Your Data Team

  1. Understanding your requirements: Before implementing RBAC, conduct a thorough analysis to look at job functions and current processes in place for access control. Assess your data team’s current state in data security and any regulatory or audit needs. 
  2. Planning the scope of implementation: Now, plan the implementation of RBAC to meet the needs of your data teams. Focus on systems or applications that hold sensitive data to limit your scope. This will also assist your company in managing the change brought about by RBAC.
  3. Defining roles: Once you complete the analysis of requirements and figure out how individuals in your data team carry out their responsibilities, it will be simpler to define your roles in RBAC. Avoid issues while defining roles like,
  • Role overlap
  • Excessive or inadequate granularity
  • Allowing too many exceptions to RBAC permissions
  1. Implementation: Rolling out the role based access control is the final phase. To minimize an excessive workload and business disturbance, complete this task in stages. Address a core group of users in your team first. Before granularizing access control, start with coarse-grained access. Gather user feedback and keep an eye on your environment as you prepare the next steps in the implementation process.
Steps in Implementing role based access control
Steps in Implementing Role Based Access Control

Benefits of Implementing RBAC

There are mainly three benefits. 

1. Contributes to Data Governance

  • An important aspect of data governance is limiting access to different entities for security reasons.
  • Role based access control prevents intentional data access for the sale or sharing of sensitive information including client or internal financial information. It also prevents accidental changes to data such as inadvertent deletions of pipelines.
  • An added advantage of limiting access is preventing legitimate analysis of incorrect data. For example, a data analyst might mistakenly believe that a table with the ambiguous name “hubspot_data” refers to customer data from HubSpot. But, that person might go ahead and create incorrect reports based on that. 

2. Lightens the Cognitive Load

The goal of developing a role based access control system should be to reduce the cognitive load on users and maintainers. You create a limited number of roles for maintainers with the defined scopes. Roles can be iterated based on the defined principle. 

You can use the user feedback, and documentation to create roles as and when needed. When working with a team, you can initially create a simple role that just has access to high-level metrics. When the team expands, you can create new roles or grant them more access. It’s minimal risk to increase access and documentation if the team is small and highly engaged.

3. Provides Structure

Role based access control will only be one of the many parts that make up your data infrastructure. But it is a fantastic opportunity to establish guidelines and get your team thinking along these lines. The interaction with data can be just as significant as the data itself, just like your goods, services, marketing, and other business operations. 

RBAC can act as a structure for data teams. So, the RBAC feature comes in handy when you opt for a third-party data integration tool like Hevo Data. What if you are building your own data pipelines? 

Role Based Access Control Best Practices

You need to do the provisioning of data infrastructure written down in code that a system or an individual should be able to execute. And, you need to abstract the configuration for this system into logical components and concepts with modularity in mind. 

That means you should keep in mind each part of the integration process. The code should be,

  • Version-controlled– so when someone leaves the company, others can take it over from code hosting platforms like Github, and Bitbucket
  • Maintained using merge request and code review system
  • Provisioned to be non-destructive– this will be helpful when someone removes access. The restoration will be smooth and won’t affect other modules
  • Idempotent– it can be executed multiple times without fear of overwriting or colliding with the current system
Pro tip: You can use tools like Airflow that can help you write codes, and set up role based access control manually when you have in-house data pipelines.

Wrapping Up

Role based access control helps data teams to expand without data security issues. The issues could include accidental deletion or editing of a data pipeline, or even a data breach. Using RBAC, you can limit access to data pipelines based on the roles of people in data teams. 

With RBAC, the billing information and critical actions like creating or editing pipelines can be made accessible only to data practitioners who carry out the task. When you choose a third-party tool like Hevo for data integration, RBAC feature comes in handy. Otherwise, you would need to configure the system by coding manually. Always make sure that the code is version-controlled and idempotent. 

That’s about RBAC of data teams! Now it’s your turn to get benefitted from the feature provided by third-party tools like Hevo Data. You can weigh the advantages and disadvantages of role based access control when you opt a tool and decide. 

If you want a high-performing ELT with low latency and accurate replication, you should try Hevo Data’s Data’s no-code, zero-maintenance data pipeline solution. It supports both pre-load and post-load transformations.

With Hevo, you can integrate data from 150+ sources into a destination of your choice. ELT your data without any worries in just a few minutes.

Visit our Website to Explore Hevo

It has pre-built integrations with 150+ sources. You can connect your SaaS platforms, databases, etc. to any data warehouse of your choice, without writing any code or worrying about maintenance. If you are interested, you can try Hevo by signing up for the 14-day free trial.

Anaswara Ramachandran
Content Marketing Specialist, Hevo Data

Anaswara is an engineer-turned writer having experience writing about ML, AI, and Data Science. She is also an active Guest Author in various communities of Analytics and Data Science professionals including Analytics Vidhya.

No-code Data Pipeline For your Data Warehouse