Navigating Data Access Management Strategies: Build Vs. Buy
In today’s data-driven world, effectively managing access to a growing volume of cloud-based data is an ongoing challenge for most companies. With over 60% of all corporate data now stored in the cloud, it is a delicate balance to keep sensitive information safe while simultaneously making it accessible for decision-making.
When it comes to data access management, enterprises have two main options: (a) build a platform in-house or (b) buy a solution from a vendor or managed service provider (MSP). Each approach has its advantages, as well as its drawbacks. Building a data access platform allows for greater customization, but requires an immense amount of time and internal resources. On the other hand, purchasing a platform offers access to expertise, ongoing support, and scalability, yet you sacrifice some control.
Regardless of which route a company takes, data access management is usually a shared responsibility between IT, security, and data teams, which can further strain already tight resources. When weighing the options, it’s critical to fully understand the implications of each.
Pros of Building Your Own:
- Complete control over features and functionalities
- Easier to make changes on the fly with an in-house development team on hand
- Lower upfront costs compared to purchasing a commercial platform
Cons of Building Your Own:
- Requires significant time, resources, and in-house expertise in software development, security, and data management
- Integrations and implementations may be complex and lengthy
- Risk of greater security and compliance issues
- The danger of becoming locked into your current data platform(s)
- Requires continuous updates, bug fixes, and support, which can strain IT and development teams
- Potential to be more costly long term
Pros of Purchasing a Solution:
- Access to a trusted vendor with specialized expertise
- Dedicated teams to ensure successful integration with other systems
- Faster implementation and scalability as your company grows
- Ongoing support to oversee functionality, security, updates, and maintenance
- Saves significant time and effort compared to building one from scratch. This accounts for the initial project, but more importantly for planned and unplanned additions that will be done as requirements shift, and the tech stack changes.
- Allows organizations to focus on core business functions instead of investing heavily in development, yielding a greater ROI in the long run
Cons of Purchasing a Solution:
- Need to research the right vendor
- Possible customization limitations
- Adapt internal processes to fit the features and capabilities offered by the platform
- Involves upfront costs, licensing fees, and potential ongoing expenses for maintenance and support
Regardless of which approach you choose, it’s important to have a well-defined roadmap and involve the necessary stakeholders, including IT, security, and data teams, to ensure a smooth decision-making and implementation process. The shared responsibility can strain resources, so planning and coordination are crucial to minimizing any potential challenges.
Your Roadmap to Success
Whether building your own or buying a complete solution, having a roadmap in place can help you determine the best approach for your unique needs and ensure that implementation is as fast and painless as possible.
It’s important to conduct a thorough evaluation of your organization’s data access needs, available resources, expertise, timelines, and cost considerations. Consult with relevant stakeholders to gain insights and develop a list of criteria to make the project successful.
Five capabilities that organizations should not compromise on when it comes to a data access solution include:
- Continuous data discovery and classification: A data access strategy won’t be successful if you don’t first have a clear understanding of where your data lives, what kind of data it is, and who needs to use it. Continuous data discovery and classification capabilities eliminate the need for manual data mapping and automatically scan all structured and semi-structured data across different types of databases, data warehouses, or data lakes. Once data is discovered, it is then classified into categories and flagged as critical or sensitive to apply appropriate controls.
- Customizable access controls and security policies: The right access control capabilities keep sensitive information safe but easily accessible to the right people for decision-making. It’s important that the tool includes granular security policies such as dynamic masking and row-level security. Access controls that are role-, context-, and attributed-based ensure that sensitive data never gets into the wrong hands. Look for tools that automatically set up and apply access and security policies universally across any data store, customize access to sensitive data for different audiences based on needs, and revoke access when it’s no longer needed.
Self-service data access: The amount of data that organizations store on the cloud grows exponentially daily, and managing access to it all while keeping it secure and compliant is challenging. Often, this job falls to IT or data teams, pulling them away from other more business-critical tasks. Self-service data access capabilities relieve the burden by empowering data users to take control of their own access, which results in faster completion of data projects. Look for an easy-to-manage interface that automatically reviews requests, grants temporary access to the specific data required for that specific user based on their unique attributes, roles, and business needs, and revokes it when it’s no longer needed.
- Scalable, seamless integration: Define the implementation. If needed, develop a data migration plan and determine what other systems and infrastructures to integrate with the data access solution. Tools that can continuously scan new data as it is introduced and automatically apply policies will best scale with an organization as its data footprint grows.
- Comprehensive governance and compliance support: Dealing with sensitive data means dealing with regulations and privacy concerns. Tools with advanced reporting and monitoring capabilities that provide audit trails and continuous visibility into data access and usage can help companies maintain regulatory compliance requirements.
Explore Build vs. Buy Scenarios
Once you have your criteria checklist, it’s time to determine whether to build your own data access tool or buy one. This decision ultimately comes down to various factors and considerations specific to your organization.
Start by evaluating internal resources: Do you have in-house IT, security, and data teams with the bandwidth to build and maintain a custom solution? Do you have these resources and are they strapped, but willing to be involved peripherally? Or do you not have any resources to spare and need to outsource it all?
Next, conduct vendor evaluations to see how many boxes they check off your list, then perform a cost-benefit analysis. Building your own tool may be cost-effective if you can allocate the necessary resources and plan for ongoing maintenance and support. However, even though purchasing a solution may involve upfront costs and ongoing support expenses, it may still be the most cost-effective option. Weigh the cost of purchasing a solution against the potential costs and resource allocation required to build and maintain your own tool.
The bottom line is, if time is a crucial factor, you need a solution quickly, and your organization lacks the specialized expertise required to build and maintain a solution in-house – whether on the software development side or the data and security side – then purchasing a commercial solution can save significant development time, allow for faster implementation, and provide access to dedicated support and expertise.
However, if your organization has specific and unique requirements that cannot be adequately addressed by an existing solution and you have available software development, security, and data management resources in-house already, then developing your own custom solution may be worth exploring.
About the author: Ben Herzberg is the Chief Scientist of Satori Cyber. The Satori data security platform seamlessly integrates into any environment to automate access controls and deliver complete data-flow visibility utilizing activity-based discovery and classification. Prior to Satori, Ben was the Director of Threat Research at Imperva, leading teams of data scientists and security researchers in the field of application and data security.