Data Discovery Best Practices in 2024
Harsh Sahu
CTO
April 2024 | 15 mins
There has never been a better time to achieve impact with your data. More and more data is available, which means organizations are getting hungrier to get more insights from data.
Data has not only increased in volume; it has also gained tremendous richness and diversity. Proprietary information, sensitive business data, critical business assets, confidential data; you name it, it has increased over time.
But one question haunts organizations the most: “How do we bring the best out of our data?”.
In this blog, you’ll understand why data discovery is a non-negotiable for businesses to get the best out of their data, and also understand the top 8 data discovery best practices.
Data discovery is a process in data security framework where organization’s data is used for business intelligence by collecting, cleaning, and analyzing data from various sources, which may be structure or unstructured, to identify meaningful patterns, trends, and insights.
The goal of data discovery is to make data more accessible and understandable, allowing business users and decision-makers to gain actionable insights without needing a deep technical background in data science or analytics.
While traditional data discovery tools gives visibility into sensitive data, they are not agile enough to accurately detect data at petabyte scales, which is often the case of modern cloud environments.
Shadow data refers to information that is collected and stored by an organization but exists outside of the management and control of its centralized IT department.
Data discovery will aid in shadow data discovery, which according to Gartner could save upto 40% of IT spending.
Data discovery helps organizations locate and classify sensitive data, such as personal identification information (PII), financial information, health records, or intellectual property. Knowing where sensitive data resides is the first step in protecting customer trust.
According to McKinsey, 71% of consumers say they would stop doing business with a company if it mishandled their sensitive data
Many regulations, such as the GDPR, HIPAA, and CCPA, require organizations to know precisely what data they have, where it is stored, and who can access it. Data discovery enables compliance with these regulations by providing visibility into data assets.
By understanding the types of data they hold, organizations can tailor their data protection strategies to fit specific needs. For example, highly sensitive data might be encrypted, access to certain types of data may be restricted, and more rigorous monitoring systems can be applied to critical data sets.
Data security platform like OptIQ, has built in feature of data discovery (data inventory), which include monitoring capabilities that can detect unauthorized access or abnormal data usage patterns, which are indicators of a security breach.
Early detection of malicious activities is important as data breach costs $4.45 million on an average globally in 2023.
In many organizations, data tends to proliferate across various storage systems and devices, often without proper oversight. This sprawl makes it difficult to apply consistent security policies and can lead to increased risks of data leaks or losses.
Data discovery helps organizations gain control over sprawl by identifying and consolidating redundant, obsolete, or trivial (ROT) data and applying uniform security measures.
Data discovery provides essential insights that help in assessing and managing risks associated with data.
Understanding where data resides, how it moves, and who accesses it helps in identifying potential vulnerabilities and threats, thereby making it easy for data security posture management.
A principle of many data protection regulations is data minimization — the practice of limiting data collection and storage to what is directly relevant and necessary to accomplish a specified purpose.
Data discovery enables organizations to identify and safely delete unnecessary or outdated data, reducing the risk surface for potential security incidents.
While organizations need a hold of what data they contain and where it is located, it is also essential to properly catalog them for better management of personal data breaches.
Growing concern over privacy breach and regulatory non-compliance makes data discovery an absolute necessity for fast-moving organizations.
Here are 8 best practices to aid in a proper data discovery:
A key feature of an effective data discovery solution is its ability to comprehensively identify and catalog every data asset within an organization. This includes both officially sanctioned data and shadow data — the information that might be stored outside of approved channels.
By creating a central catalog of data available across on-premises and multi-cloud environments, organizations can gain a full overview of their data landscape. This complete visibility is crucial for the first step in data security: tracking where your data resides.
For a complete understanding and streamlined management of your data assets, sensitive data catalogs employ advanced native connectors and REST-based APIs.
These tools are designed to efficiently scan and extract metadata from a diverse range of data repositories, including data warehouses, cloud data stores, and non-relational data stores.
Metadata, a crucial component in managing and safeguarding your data, can be broadly categorized into three types:
With increasing data, not only the volume, but also the diversity of data has grown. Traditional data discovery tools allows security administrators to only discover limited categories of sensitive personal data, such as
Modern data security platform like OptIQ allows businesses to identify:
Mastering the management of sensitive data begins with an effective sensitive data catalog, an essential component of any good data security platform.
Essential features of Sensitive Data Catalog:
Sensitive data sprawl can violate many data privacy regulations when its exposure is unknown. Data security platform should give an overview of the quantification of the records at risks, enabling organizations to not only locate but also evaluate the scope and potential impact of exposed data.
This assessment helps in prioritizing security measures and compliance efforts. Businesses can efficiently allocate resources towards securing vulnerable data points, mitigating risks, and ensuring compliance with regulations such as GDPR, HIPAA, or CCPA.
Access graph provides the relationship between data and its owners, especially in the context of fulfilling Data Subject Rights (DSR) requests under privacy regulations.
Here’s how an access graph looks like in OptIQ Data Security Platform:
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Access graph provides security teams will the ability to answer the following questions:
As data volume reaches the petabyte scale, the security and privacy risks associated with managing such massive amounts of information also escalate significantly.
Here’s why:
To effectively manage petabyte-scale data volumes, organizations need a solution that not only scales efficiently but also optimizes the following aspects:
In privacy regulations such as GDPR and CCPA, organizations must document and furnish a record of all their data processing activities or Article 30 reports.
With a robust data discovery tool, administrators can build a centralized catalog of their data assets and discover sensitive data stored in them. Using automated discovery mechanisms, organizations can ensure their data maps and Article 30 reports are up to date.
Data discovery is a major challenge for organizations who are dealing with huge amounts of datasets. To reduce compliance burden, manage sensitive data effectively and monitor data usage patterns it is essential to choose the right data discovery tool.
OptIQ data security platform begins with data discovery of all your on-premise and cloud data assets. This includes both structured and unstructured data.
Once the data is discovered, classifying them and tagging according to your business use cases makes the process streamlined. To discover your sensituve data and reduce blast radius of any threats, request a demo to experience OptIQ Data Security Platform.
Data discovery is important for regulatory compliance because it enables organizations to identify and categorize all data they hold, particularly sensitive data subject to specific regulatory requirements.
Data discovery improve decision-making by ensuring that the data used is accurate, complete, and timely. By implementing practices such as maintaining a clean, well-organized sensitive data catalog, organizations can trust the data at their disposal for making strategic decisions.
