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Embracing Data Fabric for Building Effective Data Products – Industry Insights Hosted by Eckerson

Watch the Panel Overview The digital landscape is rapidly evolving, and with it, the way we approach data management and analytics....

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Overview

The digital landscape is rapidly evolving, and with it, the way we approach data management and analytics. During a recent panel discussion featuring experts in the analytics and data management industry, key insights were shared on the importance of data fabric and its role in the development of data products. Here’s a summary of the conversation, highlighting why those interested in building data products should consider a data fabric approach, like Promethium.

The Growing Importance of Data Products

Data products have become central to modern data strategies. As Matt Fuller, with experience in data analytics at companies like Starburst and Teradata, emphasized, the complexity and variety of data sources necessitate a move beyond traditional data management methods. Data products, treated with the same rigor as any other product, allow for better management and consumption of data.

Overcoming Challenges in Building Data Products

Rick Hall, with decades of experience in analytics, highlighted that developing quality data products is not without challenges. These include ensuring data ownership, traceability, and empowering business teams with the right tools. Data fabric can address these challenges by providing a unified layer that connects disparate data sources, offering a more holistic view and easier management of data.

Data Fabric as a Solution

Kaycee Lai, CEO of Promethium, discussed the role of data fabric in enhancing the relevance and accessibility of data for generative AI applications. Data fabric acts as a connective layer, bringing together various data sources and ensuring only trusted, curated data is used, thereby reducing the risk of data silos and inefficiencies.

The Future of Data Management: Data Fabric and Mesh

The discussion also dived into the future of data management, with data fabric and mesh being identified as key components. These approaches, as Rick Hall noted, are not competitive but complementary, offering a way to manage the increasing complexity and distribution of data.

Promethium: A Unique Approach to Data Fabric

Promethium’s approach to data fabric stands out for its emphasis on collaboration and ease of use. As Kaycee Lai pointed out, Promethium recognizes data analytics as a team sport, catering to various personas in the data process. By incorporating natural language processing, Promethium simplifies the creation and management of data products, making it accessible to a wider range of non-technical business users.

Conclusion

The insights from these industry experts make a compelling case for the adoption of data fabric methodologies, like those offered by Promethium. In an era where data is king, the ability to efficiently manage, process, and draw insights from data is invaluable. Data fabric not only simplifies these processes but also ensures that data products are built on a foundation of quality and accessibility.

For those embarking on the journey of building data products, embracing data fabric technologies like Promethium could be the key to unlocking new levels of efficiency and innovation in data management.

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