Industry executives and experts share their predictions for 2024. Read them in this 16th annual VMblog.com series exclusive.
AI/ML, Data 4.0, and Open Source
By Anil Inamdar is VP & Global Head of Data Solutions at Instaclustr (part of Spot by NetApp)
A new level of AI/ML maturity is reshaping enterprise environments-and in 2024 many more organizations will embrace new platforms to unlock competitive and operational advantages. But the pursuit of a competitive edge will also lead enterprises to modernize approaches to application development and data analytics, hone developer productivity with platform engineering, and tie it all together with fully open source technologies.
Specifically, I predict that in 2024…
1) Integrated AI/ML processing platforms will help enterprises accelerate AI/ML development.
2024 will really see the widespread start of enterprises leveraging integrated platforms for AI/ML processing. These comprehensive solutions will include everything from data-layer technologies to storage, infrastructure orchestration, and AI/ML frameworks-enabling organizations to streamline the development, training, and deployment and management of AI/ML models and applications. AI/ML processing platforms will provide collaborative environments, with the features and resources that data scientists, developers, and DevOps teams require to build effective solutions and continually optimize them in production.
2) Hybrid multi-cloud data platforms will rise in availability and popularity.
2024 will also see a notable ramp-up in the adoption of hybrid multi-cloud data platforms for both operational and analytical systems. These advanced data management solutions will make it simple to wield data technologies across hybrid infrastructure, including on-premise, private cloud, and public cloud options. Many enterprises without internal expertise will need to align with experienced cloud operations service providers, such as Spot by NetApp, to implement secure and efficient multi-cloud data platforms without hiccups. This strategy-gaining the capabilities to seamlessly store, replicate, process, and manage unified data across multiple infrastructures-will enable organizations to achieve unprecedented flexibility, availability, and scalability, while harnessing the unique strengths that each infrastructure environment offers.
3) Open source technology in enterprise architecture will run even deeper.
Accelerating a clear trend, 2024 will see key open source projects and technologies reach deeper within enterprise architecture. The increasingly stark advantages that enterprise-grade open source solutions hold over their proprietary counterparts-innovation, security, and development velocity spurred by community collaboration and support-only become more pronounced with each passing year. 2024 will be no exception.
4) More enterprises will implement platform engineering to improve developer experiences and productivity.
Platform engineering strategies, in which enterprises create internal developer platforms (IDPs) to empower their development teams, will grow in popularity as enterprises seek an efficiency edge in bringing application products and features to market. IDPs offer standardized frameworks that spare developers from tedious block-and-tackle tasks and let them get straight to innovative development work, while also providing flexible self-service capabilities that allow developers to be far more productive and effective.
I expect open source-based approaches to platform engineering will prove especially fruitful in 2024, as open source offers the freedom to start small, explore, and learn rather than force long-term vendor commitments. Open source also offers invaluable portability and flexibility in supporting developers’ preferences, while making an enterprise a more inviting destination for platform engineering teams and developer talent alike.
5) Enterprises will adapt their data analytics strategies for the “Data 4.0” era.
The latest AI/ML developments and data science techniques have ushered in a distinct new phase for data analytics. Companies launching today can harness AI/ML and generative AI technologies to implement data-driven decision-making from their beginning-leveraging customer and strategic insights like nothing available before. At the same time, legacy organizations will require digital transformations to adopt the latest technologies and remain competitive. Those enterprises with a strategic modernized data analytics vision and the bold and effective leadership to see it through will thrive in the Data 4.0 era, while those that cannot adapt will be left behind. (For more of my thoughts on this topic, read The Most Effective Enterprise Data Analytics Strategies Always Look Beyond Technology in TDWI).
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ABOUT THE AUTHOR
Anil Inamdar is VP & Global Head of Data Solutions at Instaclustr (part of Spot by NetApp), which provides a managed platform around open source data technologies. Anil has 20+ years of experience in data and analytics roles. Before Instaclustr in 2019, he held data & analytics leadership roles at Dell EMC, Accenture, and Visa.
