Predictions 2024 - Deciphering Gen AI’s Effect on Sata, Governance & Skills
Jan 6, 2024
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In this special Breaking Analysis, industry analysts focused on data platforms discuss predictions for 2024. They evaluate past predictions, discuss the growing popularity of SQL in the database space, explore the future of data analysis with generative AI, emphasize the importance of heterogeneity in data platforms, and highlight the role of Gen AI in increasing access to analytics.
The emergence of an intelligent data platform integrating infrastructure, storage, analytical engines, and foundation models will revolutionize data usage and analysis.
Generative AI will simplify database design, deployment, and operations, aiding in data modeling, testing, and governance.
Deep dives
Prediction 1: Rise of Intelligent Data Platform
Sanjeev Mohan predicts the emergence of an intelligent data platform that brings together data and AI. This platform will integrate infrastructure, unified storage, analytical engines, and foundation models, exposing them through APIs and SDKs. This integration will enable the creation of data products and AI agents, revolutionizing the way data is used and analyzed. The platform will also bring about converged governance, combining data and AI governance for better oversight of the entire data ecosystem.
Prediction 2: Simplification of Database Design and Management
Tony Behr predicts that generative AI (Gen AI) will simplify database design, deployment, and operations. Through generative AI, entities and relationships can be automatically suggested for data modeling. Synthetic data generation using generative AI will aid in testing. Additionally, generative AI will contribute to data governance by automatically generating documentation in plain English. While this transformation will not be completed in 2024, it will set the stage for future advancements in database management.
Prediction 3: Rationalization of Data Silos and Governance Challenges
Carl Olson predicts that the growing use of Gen AI and data combination will necessitate the rationalization of data silos. The combination of data from different sources will pose challenges in terms of data quality, confidentiality, and contextual use. Organizations will need to undertake the complex task of curating and governing data, ensuring that combinations are rational and comply with regulations. While this process may take several years, it is crucial for organizations to fully leverage the potential of Gen AI.
Prediction 4: Continued Need for Traditional AI and AI Skills
Doug Henschen predicts that Gen AI, while valuable, will not replace traditional AI in demanding use cases. Traditional AI will continue to be necessary for areas such as credit risk, fraud detection, and algorithmic trading. Furthermore, organizations will face a continued skills gap in acquiring and retaining AI expertise. Data analysts and professionals will still have a role in curating data, defining key metrics, and guiding users in their natural language query interactions. The transformation brought by Gen AI will augment rather than replace traditional AI and human expertise.
In this special Breaking Analysis we're pleased to host our third annual data predictions power panel with some of our collaborators in theCUBE Collective and members of the data gang. With us today are five of the top industry analysts focused on data platforms. Sanjeev Mohan of Sanjmo, Tony Baer of dbInsight, IDC's Carl Olofson, Dave Menninger who is with Ventana Research, now part of ISG and Doug Henschen with Constellation Research.
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