Select Page
14 November 2023


Gartner’s top trends in data & analytics for 2023

In 2023, the field of data and analytics shifted its focus from managing data and producing insights to delivering tangible value to organizations. Understanding the recent top trends in data and analytics technology and practices in 2023 can help anticipate change and transform uncertainty into opportunities for data professionals around the world in 2024 and beyond.

This blog post will discuss the key takeaways from the Gartner complimentary report “Top Trends in Data and Analytics for 2023,” an in-depth look into big data trends backed by industry evidence and insights from around the world. 

Access the entire complimentary Gartner report to uncover more information about these trends and what we can expect from big data & AI in 2024. 

Three main themes

In 2023, the field of big data, analytics, and AI shifted its focus from managing data and producing insights to delivering tangible value to organizations. This change has brought with it three main themes for organizations to follow to stay ahead of the curve.

Theme 1: Think like a business

Data and analytics leaders around the world are adopting a proactive approach to data management, emphasizing awareness and understanding across the organization. This shift frames data and analytics as a product that drives growth and innovation to manage risk and reduce costs.

“Thinking like a business” means data professionals should adopt a focus on balancing the cost of delivery with the value delivered – It’s crucial to take responsibility for data and analytics assets and outcomes, including avoiding improper use. 

Theme 2: From platforms to ecosystems

2023 saw a shift from siloed and disconnected components in data and analytics platforms to integrated data and analytics ecosystems to enhance agility and reduce information silos. This shift encompasses both technical and sociological considerations, including the role and interactions of humans and AI. 

Sharing resources and capabilities across the organization is vital for maximizing value. Integration into the broader organizational and societal ecosystem requires comprehensive and integrated data architectures to help facilitate the adoption of new capabilities and increase potential use cases throughout the big data and AI industry. 

Theme 3: Don’t forget the humans

AI, while powerful, often works best when combined with human involvement. Maintaining the human aspect while working with AI architectures can have several benefits for an organization, including in the decision-making processes, environmental impacts, and providing trust to customers and partner organizations.

Even the most automated decision-making process needs human involvement in its initial design and subsequent monitoring and evaluation. It’s important to consider various risks when including AI in data tasks, including sustainability, losing customer trust, and taking on unexpected biases.

2023 trending data topics

In addition to the above themes, the Gartner report further details several themes that gained popularity and notoriety in the last year. While this blog post is a high-level overview, the full complimentary Gartner report further highlights the importance, relevance, implications, actions, and further reading material for each of the following trends:

  • Value optimization – Identify and articulate stakeholder impact on processes, activities, and decisions from data and analytics initiatives in business terms.
  • Managing your AI risk – More laws and policies are regularly put in place to regulate the use of AI, leading organizations to start adopting guidelines, practices, roles, and tooling for AI governance.
  • Observability – Observability in a data and analytics system allows the users to monitor and comprehend its behavior across multiple components within the platform, including observing external outputs such as its activities, measurements, requests, and dependencies.
  • Data sharing is essential – Data sharing is an essential business capability that enables access to the right data at the right time to derive the right insight.
  • Data & analytics sustainability – Sustainability is always a hot topic in the big data industry, particularly concerning energy consumption, greenhouse gas emissions, and climate change.
  • Practical data fabric – Data fabric is a data management design pattern leveraging all types of metadata to observe, analyze, and recommend data pipeline actions used by organizations to capture data assets, infer new relationships in datasets, and automate data actions.


Access the entire complimentary Gartner report to uncover more information about these trends and what we can expect from big data & AI in 2024. 

Discover the DataGalaxy blog, organized by the most relevant topics in data management including data governance, data catalog, business intelligence, data people, and data glossary. Interested in learning even more about using your data as an asset to achieve higher levels of data governance and data quality? Book a demo today to get started on your organization’s journey to complete data lifecycle management with DataGalaxy!

Structuring a data-driven organization

Other articles