There is a plethora of challenges associated with today’s data landscape, and an untold number of reasons why more and more organizations need an automated data discovery solution to address those issues.
The ever-increasing amount of data being processed, the evolving regulatory landscape, and the variety of technologies (legacy systems, data lakes, SaaS tools, etc.) that store and process data are just a few of the challenges organizations face when it comes to their data security.
Organizations take varied approaches based on a variety of factors to address data challenges. While the right approach may vary based on internal and external factors, there are a few common mistakes organizations make when trying to know and govern their data:
- Locking down and over-governing: Many organizations live in fear of misusing their data, resulting in fines, data breaches, or loss of trust from their stakeholders. A typical response to ensure this doesn’t happen is the locking down or over-governing of data. This might mean only giving data access to a limited number of individuals or data scientists to try to meet the entire business’s needs or putting lots of approval processes and red tape between the company and the data they need. In a data-driven economy, where data is an asset and a competitive advantage, this is not a solution that can scale for most businesses.
- Relying on manual data discovery processes: Organizations may choose to forgo deploying automated data discovery solutions in favor of a manual approach that may seem cheaper and quicker to implement. Manual approaches to data discovery typically involve sending surveys or questionnaires to IT owners that ask questions about the types of data, how the data flows, and why it is used. While surveys and assessments play a key role in privacy, security, and data governance programs, using surveys as the sole method for data discovery can be tedious and a drain on resources. This tactic often provides an outdated and inaccurate reflection of what data you have and how it is governed.
This webinar will help you understand the full breadth of OneTrust’s Data Discovery solution and why a single tool can de-risk your organization’s data.
While restricting access to sensitive data and keeping a watchful eye on discovery processes are key to privacy, security, and data governance programs, these methods should be leveraged in tandem with an automated data discovery solution to address modern security challenges.
Essential elements of an effective data discovery solution
A truly automated data discovery solution helps organizations understand their data across their business and third-party relationships as well as in the context of today’s complex regulatory landscape. This is done by connecting to and scanning IT systems, leveraging AI, machine learning, and other technologies to classify, tag, enrich the data, and then inventory and take action on that data in different ways. Almost all data discovery solutions accomplish these key elements in some way, shape, or form, so an organization must dig deeper when evaluating the tool that is the best fit for them. A few essential capabilities to look for in a data discovery solution include:
- Discovery in the systems you know about and those you don’t: Many data discovery tools require the organization to know all of the IT systems they want to connect to and scan. In modern organizations, data is often sprawled across hundreds or thousands of systems, and shadow IT is almost always present in some form. Therefore, it is key for your data discovery solution to also help identify all of your systems by referencing existing sources of this information in the business like CMDB, IAM, CSPs, and CASB tools to ensure you have an accurate inventory of all data assets.
- Going deeper than the metadata: Some data discovery solutions only scan at the metadata level and attempt to give you information about the data you have without analyzing the actual data. Often the sensitive data you want to know about won’t be found in this manner. This can be the case with structured data — maybe credit card data was mistakenly entered into a field called “Phone Number” — and mostly unstructured data such as files, emails, and free text fields structured systems.
- Scaling across large volumes of data: Today, most organizations have petabytes of data. It is not scalable to have a discovery solution scan every piece of data every time a scan runs. While it is critical to go deeper than the metadata, it is also key to take a scalable approach that balances scanning full data sets with scanning smaller samples of data where appropriate.
- AI trained on the correct data: AI, machine learning, and other similar technologies used for data classification and enrichment are only as good as the data on which they are trained. Look for discovery solutions that train their technology on the most up to date regulatory requirements, frameworks, and data definitions to ensure the proper governance context is applied to your data.
- Regulatory intelligence: A worthy data discovery solution will have automated regulatory intelligence built in, so your organization can remain compliant with privacy and security mandates within specified timeframes. This will help your teams to accurately discover, inventory, and classify sensitive and regulated data as well as respond to requests for information.
The final critical element to consider is once you know your data, what do you do with that information? Many data discovery solutions are just that — data discovery solutions. Once the data is discovered, these tools need to integrate with other solutions to help your privacy, security, and data governance teams act and govern the data. Each of these teams has different use cases when it comes to actioning this information.
Security teams need to not only comply with frameworks and regulations to keep the company and its data safe but build out processes around de-risking that data from the moment it enters the organization’s ecosystem through its lifecycle.
OneTrust not only helps you discover, classify, and know your data but also provides the full platform to help privacy, security, and data governance teams operationalize the downstream actions, governance processes, and compliance reporting that need to occur after discovery.
Gain visibility and take action to de-risk your organization’s staggering amount of data. Learn how to implement those strategies in this infographic.