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AI-based solution designed to automate personal data discovery and classification
Discover personal data across multiple systems in the cloud or on-premise
Harbor cooperation between DPO, Legal Services, IT and Marketing
Turn data subject request into an automated workflow with a clear insight into data every step of the way
Collaborate with stakeholders and manage DPIA and LIA in real-time with Assessment Automation
Guide your partners trough vendor management process workflow
Identifying the risk from the point of view of Data Subject
Quickly respond, mitigate damage and maintain compliance
Consolidate your data and prioritize your relationship with customers
Privacy portal allows customers to communicate their requests and preferences at any time
Introducing end-to end automation of personal data removal

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General Data Protection Regulation

Here you can find the official content of the Regulation (EU) 2016/679 (General Data Protection Regulation) in the current version. All Articles of the GDPR are linked with suitable recitals.

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Starting with the Data Discovery [What you need to know]

Starting with the data discovery

Companies today operate in an environment where they need to quickly grasp the sheer volume of data and the importance of the data they collect and process.

With an increasing number of real-life use cases for new groundbreaking technologies, like AI, Fintech, DNA sequencing, and autonomous vehicles, everything is digital and generates a lot of data.

The fact is, you cannot create a competitive digital product without having enough data to start with. Unused, unmanaged, and unprotected data, on the other hand, can lead to additional expenses and pose financial, legal, and privacy-related risks.

What can you expect

Advancing your privacy program begins with understanding how your company handles personal data, a task achieved by creating a comprehensive data map.

During this process, you can expect to discover significant volumes of personal data in unexpected locations.

Data may range from ancient and forgotten to heavily used but inadequately protected. Regardless, the goal is to discover as much as possible and chart a data map.

The ultimate objective of the privacy program is to optimize your privacy practices. To achieve this, focus on identifying areas of access to personal data and the types of personal data being collected, then work towards minimizing them.

Starting with the Data Discovery

When starting with data discovery, focus on usual suspects like Marketing, Sales, or Human Resources. You will want to look at the applications they use and examine how their processes work.

For B2C companies, a significant portion of personal data may reside within core business systems. Those relying on data-driven strategic decisions may find extensive amounts of data in their data lake or data warehouse databases.

Open yourself to the experience of learning about different types of data structures, databases, applications, and data archives.

For you, the fun can start once you have the complete and very inclusive list of systems.


DPM data discovery

Choosing the right approach

Selecting the appropriate approach for data discovery is a pivotal decision, and its significance cannot be overstated. Take the time to thoroughly evaluate various options, as the chosen method will play a crucial role in the effectiveness of your data discovery efforts.

1. Decentralized approach

With a decentralized approach, you will delegate discovery to different owners.

Different owners will be in charge of managing the inventory of personal data under their jurisdiction, and you will always have up-to-date information about the data types they process.

This is a very elegant approach to data discovery, especially if you have clearly defined data ownership.

The owners can be in-house for systems managed by your company or third parties for systems managed externally.

2. Centralized approach

An alternative approach involves empowering your privacy team to conduct data discovery independently, requiring adding technical experts such as data protection engineers to the team.

Regardless of the approach chosen, it is crucial to ensure:

  • You can trust the information you receive, and
  • All personal data is discovered

Additionally, it is essential to get notified when new types of personal data are discovered, and new systems are introduced to the company’s IT landscape.

Discovery and classification can get very technical very fast, and automation of data discovery can prove to be the only reliable option.

Besides, we live in a time of accelerated AI application, so it would not make a lot of sense to have people swipe through large volumes of data and manually label personal data types.

Outdated methods

The conventional method of personal data mapping involves using surveys directed at employees and vendors to gather details about data types and their locations.

This kind of information flow can often be slow and unreliable, as there are no guarantees that the provided information is correct.

Information system owners may not have complete or up-to-date information about which types of data are stored and used in the systems they manage.

They may resort to manual analysis or outdated discovery tools, leading to numerous false-positive and false-negative discoveries.

Moreover, these owners may be engrossed in high-priority projects without enough resources to provide necessary information to the Privacy team.

Opt for a privacy-centric solution

We have experienced a multitude of problems when mapping personal data for our clients.

Even when using existing data discovery solutions, we could never fully trust the information they provided. The existing software could not scan both structured and unstructured data or could not label personal data in other languages or scripts.

That would result in an incomplete and erroneous data inventory, which would prove detrimental to the privacy program’s success.

That is why we have invested in building privacy-centric data discovery software you can trust.

DPM Data Discovery specializes in discovering and classifying personal data, providing privacy data intelligence, and allowing companies to monitor the sensitive data they process continuously.

Through automation, privacy teams eliminate the need to rely on internal sources for accurate information about the types of personal data stored and used. This ensures a more trustworthy and efficient data discovery process, establishing a robust governance framework and mitigating privacy risks.

data discovery

DPM Data Discovery

DPM Data Discovery focuses on the precise classification of personal data using bleeding-edge technologies that work for all types of textual data. It can connect to all your data stores, scan it regularly, and report the discoveries.

Furthermore, it can combine the information from the Data Privacy Manager platform with the data discovery results, providing a trusted source of information and answering questions such as:

  • What special category data is not encrypted?
  • How many occurrences of a credit card number do we have in System X?
  • What personal data is hosted in country Y?

Using this information, the privacy team can identify privacy risks, get a deep insight into the company’s data flows, and often uncover dark data and shadow processing.

What makes DPM Data Discovery unique?

  • DPM Data Discovery connects to all standard databases, file share locations, SaaS applications, and other types of data sources
  • Works with all file types like text, Excel sheets, PDF, CVS, e-mails, log files, social network interactions, and others
  • Labels personal data in any language and any script
  • Works with structured and unstructured data
  • No third parties, no personal data in the cloud
  • Automatically searches for personal data
  • Uncovers dark data and shadow processing
  • Independent of privacy software in use

Request a Data Privacy Manager demo

Let us navigate you through the Data Privacy Manager solution and showcase functionalities that will help you overcome your compliance challenges.

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