Deliver Next-Generation Customer Experiences with Habu and Databricks

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Deliver Next-Generation Customer Experiences with Habu and Databricks

In today’s highly competitive and fast-paced business environment, your organization needs to drive meaningful differentiation, engagement, and retention by enabling exceptional customer experiences across channels and touchpoints. To do that, you need to efficiently analyze your own data AND access and analyze third-party data to enrich your data and models.

With the Habu and Databricks data clean room solution, you can do all that and more.

The Databricks Data Lakehouse provides a unified analytics platform for data engineering, data science, and machine learning. Databricks helps thousands of customers make the most of their data by accelerating data science workflows around analytics, AI, and machine learning (ML). The company offers a collaborative workspace in which teams can work together on data processing, analytics, and model development.

Habu is a global leader in data clean room software, enabling companies to benefit from the value of data without the risk. Habu transforms how organizations approach data science workflows with unique features and capabilities that enable data scientists to dramatically simplify the process of securely accessing and analyzing data from multiple sources. 

The clean room platform for next-generation customer experiences

Together, Habu and Databricks power best-in-class data clean rooms that support advanced analytics, AI, and ML use cases. The partnership delivers Habu’s industry-leading multi-cloud, multi-party data clean room orchestration and automation capabilities within the Databricks Lakehouse — providing data collaboration at scale across clouds, without use case limitations and without the need for upfront or ongoing technical resources.

Here’s what that looks like:

As you can see, Habu builds on the power of Databricks Delta Sharing in the Lakehouse, enabling data science teams to collaborate with partners on any cloud. Partners can provide distributed raw materials — such as a model, model-training code, or dataset — with the confidence that each asset remains safe in the protection of its own clean room. The combination of Databricks’ powerful data and analytics capabilities and Habu’s advanced data collaboration features provides a unique and comprehensive solution for data scientists.

As Jay Bhankharia, Sr. Director of Data Partnerships at Databricks, notes, “The native integration of our platforms will allow for seamless collaboration without moving or copying data through Delta Sharing, while ensuring that our customers are able to honor their commitment to user privacy.”

Data clean rooms drive business value

Adopting a data clean room for data collaboration can have a profound effect on a company’s bottom line. Analyst firm Gartner recently identified a 3x greater economic benefit for firms that share data externally, and IDC predicts that by 2024, “65% of Global 2000 enterprises will form data-sharing partnerships with external stakeholders via data clean rooms.” So, there’s plenty of incentive for Databricks customers to seek access to external datasets. And, across industries, data-driven enterprises have got the message: nearly 80% of organizations want to collaborate with other businesses to share data in the next 12 months, and almost 70% want to expand their current data collaborations. 

By adopting Habu data clean room software, Databricks customers significantly accelerate and simplify their DataOps workflows while gaining access to vastly more data in a secure, privacy-preserving environment. 

Let’s dig a little deeper by considering five critical capabilities of the Habu and Databricks solution:

    • Fully interoperable, with no data movement. Databricks Delta Sharing makes data available across clouds, across regions, and even across data platforms. Habu leverages the power of Delta Sharing to connect to wherever data lives and orchestrate workflows for secure collaboration. Besides being a requirement for many data owners, no data movement reduces latency and the risk of potential data leakage.

    • Flexibility for collaborative data science. Habu’s CleanML capabilities are specifically built for machine learning tasks, such as training a model on a combination of first-party and third-party data. Or, one collaboration partner can provide a pre-trained model while another brings data to run through the model for inference. Habu’s CleanCompute expands on these capabilities to provide a secure environment to run any containerized code, including SQL, Python, R, Spark, Scala, and other data science tools and libraries. In both cases, neither partner has to send their contribution to the other, and the opposite party cannot access the proprietary model or see the underlying data.

    • Enterprise-grade privacy and governance. With a Habu data clean room, one partner is designated as the “owner”, and they define the questions to be answered and the data that is required to answer each question. Habu’s adaptive governance framework ensures that both parties have full control over how much data is shared, how it’s used to maintain data privacy and security, and how it works within evolving regulations.

    • User experience for any use case. Pre-written analytics for common business use cases speed time to insight. Habu’s built-in, enterprise-grade BI tool allows users to visualize and analyze data without needing additional software. Data science teams can utilize powerful APIs and code in multiple languages to develop advanced analytics and integrations. This flexibility ensures that as your organization’s data needs grow, Habu can accommodate those needs without significant overhead or complexity.

    • Multi-party collaboration. Databricks Delta Sharing allows partners to simultaneously work with multiple data and service provider partners. Queries in Habu can be templatized for reuse across multiple clean rooms, organizations, and accounts to avoid manually repeating your work. Habu’s Question Builder uses a natural language framework, making it easy for business users to find the reports they want and insert their specific parameters, enabling a high degree of customization.

    Seamless data collaboration to power data science

    A modern data clean room enables organizations to derive valuable insights from a much broader universe of data. Habu data clean room software is a particularly powerful tool for optimizing data science workflows, and ideally suited to the data collaboration needs of Databricks customers. Secure and easy-to-use, Habu seamlessly empowers data science teams to streamline and accelerate their analytic, AI, and ML initiatives.

    To learn more, sign up for our joint webinar with Databricks on May 17, “Unlock the Power of Secure Data Collaboration with Clean Rooms.” And, to experience the power of Habu for yourself, simply request a demo

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    Head of Product Marketing
    As the Head of Product Marketing at Habu, Bob is responsible for messaging and positioning, content strategy and execution, product launches, sales enablement, and more. Prior to Habu, he established the product marketing function at data science companies Domino Data Lab and DataRobot, and helped take Alteryx public in 2017 as their VP of Product Marketing. Collectively he has more than 20 years of product marketing, media/analyst relations, customer marketing, and competitive intelligence experience.
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