Habu, a Leader in Data Clean Room Software, Announces New Capabilities to Deliver Enhanced Functionality for Privacy Safe Collaboration and Business Growth
Flexible Framework Enables Product and Data Teams to Unlock The Full Power of Data and Insights
Habu, the Global Innovator in Data Clean Room Software, announces multiple new capabilities and integrations to further help companies democratize data in light of increased privacy regulation and the depreciation of identifiers. Habu is designed to make data collaboration safe and easy by supporting the dual requirements of flexible, multi-cloud infrastructure and automated intelligence. This helps companies leverage analytics and insight for secure privacy-first data collaboration and maximum performance.
Built for both data scientists and business users, Habu accelerates time to value while also surpassing the most exacting standards for privacy and security. By utilizing no-code modules, a library of pre-built queries, and marketer-friendly visualizations, the solution expands the universe of users who can extract value and use cases that can be unlocked, including profile enrichment, journey analysis, measurement, activation, distributed machine learning, and more. As data clean rooms rise in popularity, Gartner predicts that by 2023, 80% of advertisers with media budgets of $1 billion or more will utilize data clean rooms with tech giants, brands, and startups alike hastening the adoption curve across use cases beyond marketing.
“These are incredibly exciting times for our industry,” said Matt Karasick, Chief Product Officer at Habu. “More and more teams are accepting and embracing the reality of a world where the data that can create value will remain decentralized. These teams are seeing that with the right technology-enabled governance and automation, distributed data is not a blocker, but rather an opportunity to use more data than ever before to unlock even greater insights and outcomes.”
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“These are incredibly exciting times for our industry”
The new capabilities include:
Enterprise Management & Integration:
Enterprises are asking their clean room platforms to have the ability to be embedded into their existing platform, processes, and protocols. Data owners and data seekers alike are achieving success with clean rooms to develop, deploy, and use automated insights and outcomes based on distributed data. As such, Habu has released the following to facilitate seamless integration across our client and partner organizations.
• Data Out (“Use your BI tool of choice”
• Insights automated via the Habu platform can now be integrated into enterprises’ BI environments, increasing the scale and velocity by which those insights can be unleashed throughout the organization.
• SSO & Granular Roles/Permissions
• Companies can now benefit from enhanced ease of use that enables users to access and use clean rooms using the authentication tools and protocols they are already using today.
Habu for Industry Clean Room Automation:
With more than 70% of advertising spend going to Google, Facebook, and Amazon, it’s critical for companies to maximize the return on their investment in the channels where they invest heavily. In this world of distributed data, Habu helps you connect to these disparate channels and unlock the granular data and insights available within and across their clean room environments.
• Amazon Marketing Cloud
• Automated provisioning of AMC instances, templated analyses, and democratization of intelligence empowers all users across an organization to leverage the data and insights available to better plan, optimize, and measure investment in Amazon.
• Google Ads Data Hub (Enhanced Google conversions)
• Enhanced Conversions now deliver a more complete view of ad conversions within the Google ad system to better optimize and measure campaign performance.
• Facebook Advanced Analytics
• Expanded intelligence applications for Facebook data clean rooms can better unlock the potential of data and accelerate insights.
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Habu for Product, Data, & Technology Teams:
More and more, product & data teams are looking to create and deploy clean rooms to automate insights and outcomes to their business user constituents, at scale. Using clean rooms, these teams can author and distribute insights and outcomes powered by distributed data, without clients and/or their partners needing to move or centralize their data. The result is end business users having these insights and outcomes at their fingertips in privacy and governance safe ways without having to worry about how the magic happened to produce the results. Product & Data teams are looking to Habu to be able to create and achieve roadmaps and innovation on the art of the possible with distributed data, thus removing the ceiling on what they can innovate and templatize.
• Easily generate sandbox datasets of a variety of common types (e.g., CRM, transactions, segment maps, user lists, ad exposure) to:
• Quickly conduct proof-of-concepts
• Develop prototypes
• Collaborate with potential partners
• Clean ML / Clean Compute
• Increase productivity with more sophisticated use cases involving distributed data, models, and/or code to produce new models, inference, or data via machine learning models or containerized code environments.
• Python API
• Integrate outputs from Distributed Join, CleanCompute, and/or CleanML flows via a Python API wrapper. Data scientists can now access these APIs directly from their workbench tools (e.g., Jupyter Notebooks). Product and Data teams can now integrate Habu flows into other applications or systems.
• Convert analytical outputs to inputs into subsequent clean room analytical processes.
• Leverage new data and/or models for newly formed outputs for use in the same or different clean room analytics.
“Habu is proud to have earned the business and trust of so many category leaders across many industries including Automotive, CPG, Financial Services, Media & Entertainment, Retail, and Travel,” stated Matt Kilmartin, Co-Founder, and CEO of Habu. “The organizations that have chosen Habu validate the flexibility and superiority of our technology. As privacy-safe collaboration emerges as a core component of data strategy, we’re excited to work with such industry leaders.”
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