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In July, we collaborated with ThoughtWorks at the annual CDOIQ Conference in Cambridge, MA to discuss real-world Data Products implementation and best practices for Data Mesh. The data community, especially CDOs, emphasized the importance of raising awareness and gaining clarity about data products.
Surprisingly, the focus was more on the underlying data stack rather than Generative AI, which has been a prominent topic in other conferences this year. The data stack is the powerhouse behind AI/ML stacks and data applications.
View the session: Shaping the Future of Data: Harnessing the Power of Data Products and Data Mesh with Unified Architectures
In the past decade, we focused on establishing data teams and processes, but amidst innovation, the business impact was sometimes overlooked. However, the truth remains that a data team’s primary purpose is to drive profits for the organization.
Like all good things, administering Data Products too is a combination of technology, culture, and process.
Data Governance emerged as a popular topic among attendees, even though not extensively covered in sessions. Many in-person and virtual discussions focused on establishing the governance aspect, considering the involvement of authorities and the introduction of laws, bills, and acts globally to ensure data and AI system reliability and governance.
While Data Product sessions didn’t delve deeper into governance, including our session, it’s essential to highlight that Data Product paradigm consistently addresses data governance as a foundational pillar. Unified governance, particularly challenging in fragmented data stacks with numerous tools and data assets, is addressed through the infrastructure piece of Data Products. Containerization or isolation of goal-driven verticals enables different tools/capabilities to interact and rely on a common governance engine that standardizes policies across the data stack.
AI is undeniably here to stay. While it may not have been the star of the show, its significance cannot be ignored. In the current ecosystem, AI has transitioned from a good-to-have to a must-have competitive feature. However, its true potential lies in the quality and reliability of the data that fuels AI models and applications. This is where Data Products play a vital role, empowering organizations to scale their AI initiatives with more dependable and consistent models.
DataOS, an integrated platform, streamlines and expedites data development cycles. Equipped with comprehensive tools, teams can easily build, manage, deploy, and iterate on data products while ensuring seamless compatibility with existing data infrastructure. This empowers businesses to maximize the value derived from their data assets without interruptions.
Thoughtworks, with its expertise in data strategies, has led successful data transformation initiatives. Teaming up with the technologically advanced Modern Data Company’s DataOS Platform, designed to streamline Data Products creation and management, forms the backbone of this partnership, crucial for a Data Mesh implementation.
“The partnership between Modern and ThoughtWorks marks a significant step as we transform how data is implemented and applied across an organization. We’re changing the game by moving from traditional tables to a Data Product approach, and this collaboration significantly advances our shared vision. At The Modern Data Company, we firmly believe that the future lies in viewing and treating data as a product. This reimagining enables rapid, comprehensive creation and management of data, accelerating innovation and unlocking its full potential,” said Srujan Akula, CEO, The Modern Data Company.
“The Modern Data Company and Thoughtworks have partnered to combine the world’s first data operating system, Modern’s DataOS, and Thoughtworks’ world-class data engineering and AI practices to help you thrive in today’s data-driven economy,” said John Spens, VP Data & AI Service Line, Thoughtworks. “Accelerate insights to drive your business by delivering transparent, trustworthy and accessible data efficiently and well.”
Read more about our partnership.
View the session: Shaping the Future of Data: Harnessing the Power of Data Products and Data Mesh with Unified Architectures
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