FEATURE: DATA STORAGE AND DATA ARCHITECTURES
Businesses are drowning in data but struggling to use it effectively. Teams need to be responsible for their own data, ensuring it is structured, governed, ready to be used. Data governance and data structure needs to be applied at the point of creation rather than cleaning up the mess later. Without this businesses will remain stuck while competitors move ahead. Executives from Confluent, Snowflake, Kingston Technology, NetApp,
VAST Data, share their perspectives. the mess later. Without these shifts, businesses are stuck in the past while competitors move ahead,” adds Galli.
AI impacts data management
Traditional storage tiers? Gone.
AI is changing everything, including how we store and manage data. Enterprises now need disaggregated, AI-ready architectures that handle massive datasets in real time. The shift to all-flash is accelerating, eliminating latency and inefficiency. Data-aware, software-driven storage is making automation, security, and cost control smarter.
CIOs need to stop thinking about data as something to be stored and start thinking about it as a product. That means breaking down silos, ensuring teams own their data, and putting a Data Streaming Platform at the heart of their architecture. AI, automation, and customer experiences all rely on high-quality, instantly available data. Without it, digital transformation efforts stall.
“ We are seeing storage, compute, and AI infrastructure merge, giving businesses a direct path to faster insights and better performance. Bottom line, if your data infrastructure and storage is not built for AI, you are already behind,” says Haider Aziz, Vice President META, VAST Data.
“ CIOs have one priority, get data infrastructure AI-ready or risk falling behind. The move to disaggregated, unified storage simplifies architecture and enables real-time data access,” adds Aziz.
We are currently seeing a huge opportunity in the trend towards Data Products. Gartner defines this as an urgent demand for self-service data integration and distributed, domain-oriented data consumption that has given rise to data delivered as a product.
“ Businesses are drowning in data but struggling to use it effectively because of silos. Data Products change that by making teams responsible for their own data, ensuring it is structured, governed, and ready to be used. It is both an architectural and a cultural shift, and it is what is enabling AI, real-time analytics, and nextgen digital experiences,” says Leandro Galli, Senior Solutions Engineer, Confluent.
“ A major part of this paradigm is the shift left approach – bringing governance and structure to data at the point of creation rather than cleaning up
All-flash eliminates silos, reduces cost, and boosts efficiency. Integrated AI analytics accelerate insights, and hybrid multi-cloud strategies ensure agility. CIOs must focus on scalability, resilience, and automation, future-proofing infrastructure to handle AI, deep learning, and HPC.
“ The right data foundation is not a luxury, it is a necessity,” continues VAST Data’ s Aziz. AI has already proven its transformative potential and further innovation in this field will increase this notion.
As organisations accelerate AI adoption, the complexity of managing data emerges both as a challenge and an opportunity. NetApp Data Complexity Report for 2024 shared invaluable insights into the challenges and opportunities presented by the AI era. It reveals that 40 % of global technology
Data delivered as a product equals speed
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