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2024 Research Themes and Methods

The team at theCUBE Research has a track record of identifying and anticipating emerging trends in enterprise technology markets, prior to being recognized in the mainstream. Our approach is video first and AI enabled. The research team’s methodologies combine supply-side data, primary research within our community, spending and drill down survey data with our partners from ETR and inputs from theCUBE’s Alumni Network including theCUBE Collective. We have made extensive investments in social media platforms, tools and AI technology such as retrieval-augmented generation (RAG) to drive automation and get research into the market quickly. Our private clients benefit from a high touch service approach to direct them to the key trends relevant to their respective businesses and strategies.

The following key research themes are major areas of focus for theCUBE Research in 2024.

Macro Customer Spending Patterns

  • IT decision makers’ expectations for annual and quarterly spending growth.
  • Top spending priorities
  • How AI and Gen AI are affecting budgets
  • Changes in sentiment by region, size of company, industry and role.

AI, Gen AI and Automation Trends

  • Customer spending patterns in AI.
  • LLM adoption.
  • AI beyond LLMs – How suppliers are infusing AI and how customers are adopting.
  • Beyond RPA to end-to-end enterprise automation.
  • The Gen AI Power Law and the long tail of smaller language models.

Next Generation Data Platforms

  • Trends in modern data platform adoption.
  • Competitive positioning.
  • Beyond separating compute from storage – what’s next in intelligent data platforms?
  • Unifying metadata, data types, query options and open formats to enable data-first applications.
  • Attacking the governance and compliance challenge.

The Rise of the XPU

  • The importance of alternative processors beyond the CPU…the GPU, NPU, LPU, accelerators.
  • Monolithic versus modular designs and the role of big chips.
  • Trends in training versus inference and the implications on spending patterns.

Cloud, Hybrid Cloud and Infrastructure Dynamics

  • Hyperscaler IaaS/PaaS market share and growth.
  • The shifting balance between public and hybrid cloud.
  • Cloud penetration and spending patterns by size of company and industry.
  • Repatriation or rebalancing?

The Evolving Cybersecurity Landscape

  • Customer priorities in security.
  • Architecting a zero trust security approach.
  • The crowded competitive landscape and consolidation trends within cyber.
  • How AI is changing the security operations center analyst experience.
  • M&A potential in cybersecurity.

Privacy-Enhancing Technologies for Data Security

  • Delve into the development and application of privacy-enhancing technologies (PETs), such as differential privacy and secure multi-party computation, in safeguarding user data.
  • Examine the balance between data utility and privacy, evaluating how PETs can enable data analysis without compromising individual privacy.
  • Public policy and the impact on organizations security strategies.

Networking Trends

  • Networking as the new bottleneck.
  • AI for networks and networks for AI.
  • The convergence of networking, observability and security.
  • Consolidation and the competitive landscape.

Developer Trends

  • How copilots are impacting developer productivity.
  • Security and the shift left trend in Dev/Ops.
  • Open source and projects beyond Kubernetes.
  • Adoption of open source platforms and tools.

The Role of Generative AI in Shaping Customer Data Strategies

  • Assess the implications of generative AI technologies on data collection, processing, and insight generation, with a focus on enhancing customer experiences.
  • Explore ethical considerations, privacy concerns, and the potential for bias, ensuring that AI-driven data strategies prioritize customer trust and transparency.

Also please check out our data research themes for 2024.

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