Technologies

Data Clean Rooms: Secure and Private Data Collaboration

Where privacy, security, and collaboration converge for next-gen insight and next-level action.
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Data is the fuel of digital transformation, but it also comes with challenges of privacy, security and trust. How can you share and analyze data with your partners, customers or competitors without compromising your data assets or exposing sensitive information? How can you mitigate risks of data security and confidentiality?

Data clean room technology is a potential solution that enables secure and privacy-preserving data collaboration across multiple parties enabled by the functions and features of the software. Data Clean Rooms are a trending topic in the technology industry, gaining traction due to their ability to facilitate privacy-preserving sharing of data and data collaboration between multiple parties. They are used in various sectors, including advertising, marketing, healthcare, and financial services.

According to Lynne Schneider, research director of IDC’s Data as a Service and Data Marketplaces area, 88% of data buyers are at least somewhat familiar with the concept of Data Clean Rooms.

However, there are challenges associated with data clean rooms. One of the challenges comes from the term itself, as there is not a clear-cut definition, leading to confusion among vendors and end users. Another challenge is that because data clean rooms are purposefully opaque, it is imperative that the parties participating carefully establish data models, cleanse their data sets, and do other relevant prep work.

IDC estimates that there are more than 500 data clean room instances currently deployed across the globe. IDC has conducted a series of two MarketScapes on this topic, evaluating more than a dozen vendors including Acxiom, AppsFlyer, AWS, Decentriq, Epsilon, Habu, Helios Data, InfoSum, LiveRamp, Optable, Pyte.ai, Snowflake, TransUnion and TripleBlind.

What is Data Clean Room Technology?

Data clean room technology is a software solution that creates a virtual environment where multiple parties can combine and analyze their data without sharing or copying the underlying data. The data clean room technology ensures that each party maintains control over their data and can set rules and limits on how it can be used. The data clean room technology
also protects the privacy of the data and the algorithms that are used to generate insights. The data clean room technology can use various techniques to achieve this, such as encryption, hashing, pseudonymization, noise injection, synthetic data, secure enclaves, or secure multi-party computation.

Data clean room technology can be used for a variety of use cases and industries, such as advertising, marketing, healthcare, life sciences, financial services, public sector, and more. Some of the common applications of data clean room technology are:

  • Data enrichment: You can enrich your data with external data sources to gain more insights about your customers, markets, or competitors.
  • Audience creation and activation: You can create and activate audiences based on shared attributes or behaviors across multiple data sources, such as web, app, phone, and physical traffic.
  • Measurement and attribution: You can measure and attribute the impact of your campaigns or actions on your business outcomes across multiple channels and platforms.
  • Fraud detection and prevention: You can detect and prevent fraud by collaborating with other parties to identify and block suspicious activities or transactions.
  • Research and innovation: You can collaborate with other parties to conduct research and innovation projects that require access to sensitive or proprietary data.

What are the Benefits of Data Clean Room Technology?

Data clean room technology can bring many benefits to your business, such as:

  • Enhanced data value: You can unlock the value of your data by combining it with other data sources and generating new insights that were not possible before.
  • Improved data privacy: You can protect the privacy of your data and your customers by ensuring that your data is not shared or copied by other parties or by the data clean room provider.
  • Increased data security: You can secure your data from unauthorized access or misuse by encrypting it, hashing it, or using other techniques that prevent data leakage or exposure.
  • Reduced data risk: You can reduce the risk of data breaches, compliance violations, or legal disputes by following the rules and limits that you and your data collaborators have agreed on.
  • Accelerated data innovation: You can accelerate your data innovation by collaborating with other parties that have complementary data, expertise, or resources.

How to choose the right data clean room vendor?

Some of the key dimensions to consider include:

  • The scalability and performance of the solution. You need a solution that can handle large volumes and variety of data, and provide fast and reliable results. You also need a solution that can scale up or down as your business needs change, and offer flexible pricing models.
  • The functionality and usability of the solution. You need a solution that can support various types of analyses, such as descriptive, predictive, and prescriptive, and provide actionable insights and recommendations. You also need a solution that is easy to use and integrate with your existing systems and tools, and that offers a user-friendly interface and dashboard.
  • The security and compliance of the solution. You need a solution that can ensure the privacy and security of your data, and that complies with the relevant data protection regulations. You also need a solution that can offer different levels of access and control, and that can audit and verify the data processing and outcomes.

Action Items

  • Assess your data collaboration needs and opportunities, and identify the use cases where data clean room technology can help you.
  • Review the IDC MarketScapes and compare the data clean room technology vendors based on their capabilities and strategies.
  • Contact the data clean room technology vendors that match your requirements and preferences, and request a demo and client references. Ask questions, give feedback, and explore the possibilities and limitations of each solution. Find out how each vendor can support you throughout the implementation and integration process, and how they can help you achieve your desired outcomes and ROI.

Lynne's core research coverage in DaaS includes data sourcing and delivery services from traditional and emerging data providers, along with evolving data aggregation and dissemination platforms. The breadth of coverage includes services that enable an organization to externally monetize data generated as part of the organization's ongoing operations, value-added information derived from this data, and the marketplace for combining data with other solutions. This research analyzes the supply and demand side business and technology trends of this emerging category.