#156 - Mike Ferguson - Top Key Trends in Data Management and Analytics
Dec 21, 2023
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Mike Ferguson, industry expert in data management and analytics, discusses top key trends in data management and analytics, including GenAI, architecture modernization, and FinOps. Podcast explores the role of generative AI in improving productivity and automation, as well as natural language interfaces in data management. Trends in data governance, such as AI in data catalogs and labeled data policies, are also discussed.
Automation and second-generation tools have the potential to enable end-to-end data delivery and integration into business processes.
Closing the loop between analytical initiatives and strategic outcomes requires a holistic approach that encompasses the entire analytics value chain.
Automation and AI can enhance data governance by automating actions, ensuring compliance, and improving data quality.
Deep dives
Automation and end-to-end data delivery
One exciting trend for 2024 is the potential for automation to enable end-to-end data delivery. This includes the development of second-generation automation tools that can cover various aspects of data management and analytics, from data warehousing to machine learning models and AI bots. The goal is to automate the entire data delivery process and streamline the integration of data products and analytical solutions into business processes and applications.
Closing the loop between analytics and outcomes
Another area of excitement is the closing of the loop between analytical initiatives and strategic outcomes. This involves mapping data products and analytical solutions to specific business outcomes, and wiring them into processes and applications to maximize their impact. This last mile integration is crucial for achieving a fully data-driven enterprise and requires a holistic approach that goes beyond traditional metadata management and encompasses the entire analytics value chain.
Automation and AI in data governance
Automation and AI will also play significant roles in data governance, with the potential to automate governance actions and provide observability into data compliance and quality. AI-powered agents can enforce policies, identify data issues, and enhance overall governance processes. This level of automation will help organizations stay compliant, improve data quality, and ensure the effectiveness of their governance initiatives.
Data catalog integration and metadata observability
Data catalogs will continue to be central to data governance efforts, providing automated discovery, metadata management, and sensitive data identification. Integration between catalogs and other governance technologies will be crucial for streamlining governance processes and ensuring metadata consistency and quality. Additionally, metadata observability will become more important, allowing organizations to track and manage changes, enforce policies, and gain comprehensive visibility into data assets and their usage.
Scaling data governance and collaboration
As data continues to grow, scaling data governance becomes critical. Organizations will focus on automating governance processes, implementing policy-based governance, and enhancing collaboration between business and IT stakeholders. The aim is to streamline governance efforts, achieve alignment with strategic outcomes, and ensure data-driven decision-making across the organization.
Mike Ferguson (Managing Director, Intelligent Business Strategies, Chairman of Big Data London) joins the show to chat about the top key trends he's seeing in in data management and analytics - GenAI, architecture modernization, FinOps, and much more.
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